The influence of soft kernel texture on the flour, water absorption, rheology, and baking quality of durum wheat

Science.gov (United States)

Durum (T. turgidum subsp. durum) wheat production worldwide is substantially less than that of common wheat (Triticum aestivum). Durum kernels are extremely hard; leading to most durum wheat being milled into semolina. Durum wheat production is limited in part due to the relatively limited end-user ...

Effect of Protein Molecular Weight Distribution on Kernel and Baking Characteristics and Intra-varietal Variation in Hard Spring Wheats

Science.gov (United States)

Specific wheat protein fractions are known to have distinct associations with wheat quality traits. Research was conducted on 10 hard spring wheat cultivars grown at two North Dakota locations to identify protein fractions that affected wheat kernel characteristics and breadmaking quality. SDS ext...

Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

Science.gov (United States)

Kumar, Ajay; Mantovani, E E; Seetan, R; Soltani, A; Echeverry-Solarte, M; Jain, S; Simsek, S; Doehlert, D; Alamri, M S; Elias, E M; Kianian, S F; Mergoum, M

2016-03-01

Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools. Copyright © 2016 Crop Science Society of America.

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress.

Science.gov (United States)

Cui, Fa; Fan, Xiaoli; Chen, Mei; Zhang, Na; Zhao, Chunhua; Zhang, Wei; Han, Jie; Ji, Jun; Zhao, Xueqiang; Yang, Lijuan; Zhao, Zongwu; Tong, Yiping; Wang, Tao; Li, Junming

2016-03-01

QTLs for kernel characteristics and tolerance to N stress were identified, and the functions of ten known genes with regard to these traits were specified. Kernel size and quality characteristics in wheat (Triticum aestivum L.) ultimately determine the end use of the grain and affect its commodity price, both of which are influenced by the application of nitrogen (N) fertilizer. This study characterized quantitative trait loci (QTLs) for kernel size and quality and examined the responses of these traits to low-N stress using a recombinant inbred line population derived from Kenong 9204 × Jing 411. Phenotypic analyses were conducted in five trials that each included low- and high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49 QTLs for tolerance to N stress, 27 and 14 of which were stable across the tested environments, respectively. These QTLs were distributed across all wheat chromosomes except for chromosomes 3A, 4D, 6D, and 7B. Eleven QTL clusters that simultaneously affected kernel size- and quality-related traits were identified. At nine locations, 25 of the 49 QTLs for N deficiency tolerance coincided with the QTLs for kernel characteristics, indicating their genetic independence. The feasibility of indirect selection of a superior genotype for kernel size and quality under high-N conditions in breeding programs designed for a lower input management system are discussed. In addition, we specified the functions of Glu-A1, Glu-B1, Glu-A3, Glu-B3, TaCwi-A1, TaSus2, TaGS2-D1, PPO-D1, Rht-B1, and Ha with regard to kernel characteristics and the sensitivities of these characteristics to N stress. This study provides useful information for the genetic improvement of wheat kernel size, quality, and resistance to N stress.

Agricultural factors affecting Fusarium communities in wheat kernels.

Science.gov (United States)

Karlsson, Ida; Friberg, Hanna; Kolseth, Anna-Karin; Steinberg, Christian; Persson, Paula

2017-07-03

Fusarium head blight (FHB) is a devastating disease of cereals caused by Fusarium fungi. The disease is of great economic importance especially owing to reduced grain quality due to contamination by a range of mycotoxins produced by Fusarium. Disease control and prediction is difficult because of the many Fusarium species associated with FHB. Different species may respond differently to control methods and can have both competitive and synergistic interactions. Therefore, it is important to understand how agricultural practices affect Fusarium at the community level. Lower levels of Fusarium mycotoxin contamination of organically produced cereals compared with conventionally produced have been reported, but the causes of these differences are not well understood. The aim of our study was to investigate the effect of agricultural factors on Fusarium abundance and community composition in different cropping systems. Winter wheat kernels were collected from 18 organically and conventionally cultivated fields in Sweden, paired based on their geographical distance and the wheat cultivar grown. We characterised the Fusarium community in harvested wheat kernels using 454 sequencing of translation elongation factor 1-α amplicons. In addition, we quantified Fusarium spp. using real-time PCR to reveal differences in biomass between fields. We identified 12 Fusarium operational taxonomic units (OTUs) with a median of 4.5 OTUs per field. Fusarium graminearum was the most abundant species, while F. avenaceum had the highest occurrence. The abundance of Fusarium spp. ranged two orders of magnitude between fields. Two pairs of Fusarium species co-occurred between fields: F. poae with F. tricinctum and F. culmorum with F. sporotrichoides. We could not detect any difference in Fusarium communities between the organic and conventional systems. However, agricultural intensity, measured as the number of pesticide applications and the amount of nitrogen fertiliser applied, had an

Statistical analysis of the influence of wheat black point kernels on selected indicators of wheat flour quality

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Petrov Verica D.

2011-01-01

Full Text Available The influence of wheat black point kernels on selected indicators of wheat flour quality - farinograph and extensograph indicators, amylolytic activity, wet gluten and flour ash content, were examined in this study. The examinations were conducted on samples of wheat harvested in the years 2007 and 2008 from the area of Central Banat in four treatments-control (without black point flour and with 2, 4 and 10% of black point flour which was added as a replacement for a part of the control sample. Statistically significant differences between treatments were observed on the dough stability, falling number and extensibility. The samples with 10% of black point flour had the lowest dough stability and the highest amylolytic activity and extensibility. There was a trend of the increasing 15 min drop and water absorption with the increased share of black point flour. Extensograph area, resistance and ratio resistance to extensibility decreased with the addition of black point flour, but not properly. Mahalanobis distance indicates that the addition of 10% black point flour had the greatest influence on the observed quality indicators, thus proving that black point contributes to the technological quality of wheat, i.e .flour.

Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

Science.gov (United States)

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...

Genetic analysis of kernel texture (grain hardness) in a hard red spring wheat (Triticum aestivum L.) bi-parental population

Science.gov (United States)

Grain hardness is a very important trait in determining wheat market class and also influences milling and baking traits. At the grain Hardness (Ha) locus on chromosome 5DS, there are two primary mutations responsible for conveying a harder kernel texture among U.S. hard red spring wheats: (1) the P...

Biocontrol of Fusarium graminearum Growth and Deoxynivalenol Production in Wheat Kernels with Bacterial Antagonists

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Cuijuan Shi

2014-01-01

Full Text Available Fusarium graminearum is the main causal pathogen affecting small-grain cereals, and it produces deoxynivalenol, a kind of mycotoxin, which displays a wide range of toxic effects in human and animals. Bacterial strains isolated from peanut shells were investigated for their activities against F. graminearum by dual-culture plate and tip-culture assays. Among them, twenty strains exhibited potent inhibition to the growth of F. graminearum, and the inhibition rates ranged from 41.41% to 54.55% in dual-culture plate assay and 92.70% to 100% in tip-culture assay. Furthermore, eighteen strains reduced the production of deoxynivalenol by 16.69% to 90.30% in the wheat kernels assay. Finally, the strains with the strongest inhibitory activity were identified by morphological, physiological, biochemical methods and also 16S rDNA and gyrA gene analysis as Bacillus amyloliquefaciens. The current study highlights the potential application of antagonistic microorganisms and their metabolites in the prevention of fungal growth and mycotoxin production in wheat kernels. As a biological strategy, it might avoid safety problems and nutrition loss which always caused by physical and chemical strategies.

Kernel Function Tuning for Single-Layer Neural Networks

Czech Academy of Sciences Publication Activity Database

Vidnerová, Petra; Neruda, Roman

-, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/

Evaluation of date kernel oils and their effects on wheat flour characteristics

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Elsakr, A. S.

1991-06-01

Full Text Available Date kernels constitute about 13% of the whole date fruit, and cotain moderate amounts of oils with relatively high caloric values. Agwa soft and Aprimi dry date kernel oils were used in this work. Results showed that Aprimi date kernel oils have high levels of both caproic acid and stearic acid of 23.04 and 18.40% respectively, while Agwa kernel oils have high levels of caprylic acid and capric acid of 22.31 and 12.20%. Moreover Agwa oils achieved higher amounts of unsaponifiable matters, sterols and tocopherols. The addition of soft and dry date kernel oils did not improve the wheat flour strength but raised its resistance to extensibility.

Las pepitas de dátiles constituyen alrededor del 13% del fruto entero, y contienen cantidades moderadas de aceite con valores calóricos relativamente altos. En este trabajo se han utilizado aceites de pepitas de dátiles Agwa blandas y Aprimi secas. Los resultados mostraron que los aceites de pepitas de dátiles Aprimi tienen altos niveles de ácidos caproico y esteárico, 23’04 y 18'40% respectivamente, mientras que los aceites de pepitas Agwa tienen niveles altos de ácidos caprílico y cáprico, 22'31 y 12'20%. Por otra parte los aceites Agwa alcanzaron valores elevados de materia insaponificable, esteroles y tocoferoles. La adición de aceites de pepitas de dátiles secas y blandas no mejoró el poder de la harina de trigo pero incrementó su resistencia a la extensibilidad.

Soft durum wheat - a paradigm shift

Science.gov (United States)

Two traits define most aspects of wheat quality and utilization: kernel texture (hardness) and gluten. The former is far simpler genetically and is controlled by two genes, Puroindoline a and Puroindoline b. Durum wheat lacks puroindolines and has very hard kernels. As such, durum wheat when milled ...

TaGS5-3A, a grain size gene selected during wheat improvement for larger kernel and yield.

Science.gov (United States)

Ma, Lin; Li, Tian; Hao, Chenyang; Wang, Yuquan; Chen, Xinhong; Zhang, Xueyong

2016-05-01

Grain size is a dominant component of grain weight in cereals. Earlier studies have shown that OsGS5 plays a major role in regulating both grain size and weight in rice via promotion of cell division. In this study, we isolated TaGS5 homoeologues in wheat and mapped them on chromosomes 3A, 3B and 3D. Temporal and spatial expression analysis showed that TaGS5 homoeologues were preferentially expressed in young spikes and developing grains. Two alleles of TaGS5-3A, TaGS5-3A-T and TaGS5-3A-G were identified in wheat accessions, and a functional marker was developed to discriminate them. Association analysis revealed that TaGS5-3A-T was significantly correlated with larger grain size and higher thousand kernel weight. Biochemical assays showed that TaGS5-3A-T possesses a higher enzymatic activity than TaGS5-3A-G. Transgenic rice lines overexpressing TaGS5-3A-T also exhibited larger grain size and higher thousand kernel weight than TaGS5-3A-G lines, and the transcript levels of cell cycle-related genes in TaGS5-3A-T lines were higher than those in TaGS5-3A-G lines. Furthermore, systematic evolution analysis in diploid, tetraploid and hexaploid wheat showed that TaGS5-3A underwent strong artificial selection during wheat polyploidization events and the frequency changes of two alleles demonstrated that TaGS5-3A-T was favoured in global modern wheat cultivars. These results suggest that TaGS5-3A is a positive regulator of grain size and its favoured allele TaGS5-3A-T exhibits a larger potential application in wheat high-yield breeding. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Wheat Quality Council, Hard Spring Wheat Technical Committee, 2017 Crop

Science.gov (United States)

Nine experimental lines of hard spring wheat were grown at up to six locations in 2017 and evaluated for kernel, milling, and bread baking quality against the check variety Glenn. Wheat samples were submitted through the Wheat Quality Council and processed and milled at the USDA-ARS Hard Red Spring...

Effects of grown origin, genotype, harvest year, and their interactions of wheat kernels on near infrared spectral fingerprints for geographical traceability.

Science.gov (United States)

Zhao, Haiyan; Guo, Boli; Wei, Yimin; Zhang, Bo

2014-01-01

The effects of origin, genotype, harvest year, and their interactions on wheat near infrared (NIR) spectra were studied to find the reasons for differences in NIR fingerprints of wheat from different geographical origins and the stability of NIR fingerprints among different years. Ten varieties were grown in three regions of China for 2 years. 180 kernel samples were analysed by NIR. The spectra after pre-treatment were analysed by principal component analysis, multi-way analysis of variance, and discriminant partial least-squares. The results showed that origin, genotype, year, and their interactions all had significant effects on wheat NIR fingerprints. The second overtones of N-H and C-H stretching vibrations and a combination of stretch and deformation of C-H group in wheat were mainly influenced by the geographical origin. The wavelength ranges 975-990 nm, 1200 nm, and 1355-1380 nm contained plenty of origin information to build robust discriminant models of wheat geographical origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

Wheat for Kids! [and] Teacher's Guide.

Science.gov (United States)

Idaho Wheat Commission, Boise.

"Wheat for Kids" contains information at the elementary school level about: the structure of the wheat kernel; varieties of wheat and their uses; growing wheat; making wheat dough; the U.S. Department of Agriculture Food Guide Pyramid and nutrition; Idaho's part of the international wheat market; recipes; and word games based on the…

Multiple kernel learning using single stage function approximation for binary classification problems

Science.gov (United States)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

Application of calibrations to hyperspectral images of food grains: example for wheat falling number

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Nicola Caporaso

2017-04-01

Full Text Available The presence of a few kernels with sprouting problems in a batch of wheat can result in enzymatic activity sufficient to compromise flour functionality and bread quality. This is commonly assessed using the Hagberg Falling Number (HFN method, which is a batch analysis. Hyperspectral imaging (HSI can provide analysis at the single grain level with potential for improved performance. The present paper deals with the development and application of calibrations obtained using an HSI system working in the near infrared (NIR region (~900–2500 nm and reference measurements of HFN. A partial least squares regression calibration has been built using 425 wheat samples with a HFN range of 62–318 s, including field and laboratory pre-germinated samples placed under wet conditions. Two different approaches were tested to apply calibrations: i application of the calibration to each pixel, followed by calculation of the average of the resulting values for each object (kernel; ii calculation of the average spectrum for each object, followed by application of the calibration to the mean spectrum. The calibration performance achieved for HFN (R2 = 0.6; RMSEC ~ 50 s; RMSEP ~ 63 s compares favourably with other studies using NIR spectroscopy. Linear spectral pre-treatments lead to similar results when applying the two methods, while non-linear treatments such as standard normal variate showed obvious differences between these approaches. A classification model based on linear discriminant analysis (LDA was also applied to segregate wheat kernels into low (250 s HFN groups. LDA correctly classified 86.4% of the samples, with a classification accuracy of 97.9% when using an HFN threshold of 150 s. These results are promising in terms of wheat quality assessment using a rapid and non-destructive technique which is able to analyse wheat properties on a single-kernel basis, and to classify samples as acceptable or unacceptable for flour production.

Association of yield-related traits in founder genotypes and derivatives of common wheat (Triticum aestivum L.

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Jie Guo

2018-02-01

Full Text Available Abstract Background Yield improvement is an ever-important objective of wheat breeding. Studying and understanding the phenotypes and genotypes of yield-related traits has potential for genetic improvement of crops. Results The genotypes of 215 wheat cultivars including 11 founder parents and 106 derivatives were analyzed by the 9 K wheat SNP iSelect assay. A total of 4138 polymorphic single nucleotide polymorphism (SNP loci were detected on 21 chromosomes, of which 3792 were mapped to single chromosome locations. All genotypes were phenotyped for six yield-related traits including plant height (PH, spike length (SL, spikelet number per spike (SNPS, kernel number per spike (KNPS, kernel weight per spike (KWPS, and thousand kernel weight (TKW in six irrigated environments. Genome-wide association analysis detected 117 significant associations of 76 SNPs on 15 chromosomes with phenotypic explanation rates (R 2 ranging from 2.03 to 12.76%. In comparing allelic variation between founder parents and their derivatives (106 and other cultivars (98 using the 76 associated SNPs, we found that the region 116.0–133.2 cM on chromosome 5A in founder parents and derivatives carried alleles positively influencing kernel weight per spike (KWPS, rarely found in other cultivars. Conclusion The identified favorable alleles could mark important chromosome regions in derivatives that were inherited from founder parents. Our results unravel the genetic of yield in founder genotypes, and provide tools for marker-assisted selection for yield improvement.

Wheat in the Mediterranean revisited--tetraploid wheat landraces assessed with elite bread wheat Single Nucleotide Polymorphism markers.

Science.gov (United States)

Oliveira, Hugo R; Hagenblad, Jenny; Leino, Matti W; Leigh, Fiona J; Lister, Diane L; Penã-Chocarro, Leonor; Jones, Martin K

2014-05-08

Single Nucleotide Polymorphism (SNP) panels recently developed for the assessment of genetic diversity in wheat are primarily based on elite varieties, mostly those of bread wheat. The usefulness of such SNP panels for studying wheat evolution and domestication has not yet been fully explored and ascertainment bias issues can potentially affect their applicability when studying landraces and tetraploid ancestors of bread wheat. We here evaluate whether population structure and evolutionary history can be assessed in tetraploid landrace wheats using SNP markers previously developed for the analysis of elite cultivars of hexaploid wheat. We genotyped more than 100 tetraploid wheat landraces and wild emmer wheat accessions, some of which had previously been screened with SSR markers, for an existing SNP panel and obtained publically available genotypes for the same SNPs for hexaploid wheat varieties and landraces. Results showed that quantification of genetic diversity can be affected by ascertainment bias but that the effects of ascertainment bias can at least partly be alleviated by merging SNPs to haplotypes. Analyses of population structure and genetic differentiation show strong subdivision between the tetraploid wheat subspecies, except for durum and rivet that are not separable. A more detailed population structure of durum landraces could be obtained than with SSR markers. The results also suggest an emmer, rather than durum, ancestry of bread wheat and with gene flow from wild emmer. SNP markers developed for elite cultivars show great potential for inferring population structure and can address evolutionary questions in landrace wheat. Issues of marker genome specificity and mapping need, however, to be addressed. Ascertainment bias does not seem to interfere with the ability of a SNP marker system developed for elite bread wheat accessions to detect population structure in other types of wheat.

Discrete element method as an approach to model the wheat milling process

Science.gov (United States)

It is a well-known phenomenon that break-release, particle size, and size distribution of wheat milling are functions of machine operational parameters and grain properties. Due to the non-uniformity of characteristics and properties of wheat kernels, the kernel physical and mechanical properties af...

Magnetic resonance imaging of single rice kernels during cooking

NARCIS (Netherlands)

Mohoric, A.; Vergeldt, F.J.; Gerkema, E.; Jager, de P.A.; Duynhoven, van J.P.M.; Dalen, van G.; As, van H.

2004-01-01

The RARE imaging method was used to monitor the cooking of single rice kernels in real time and with high spatial resolution in three dimensions. The imaging sequence is optimized for rapid acquisition of signals with short relaxation times using centered out RARE. Short scan time and high spatial

Single corn kernel wide-line NMR oil analysis for breeding purpose

Energy Technology Data Exchange (ETDEWEB)

Wilmers, M C.C.; Rettori, C; Vargas, H; Barberis, G E [Universidade Estadual de Campinas (Brazil). Inst. de Fisica; da Silva, W J [Universidade Estadual de Campinas (Brazil). Inst. de Biologia

1978-12-01

The Wide-Line NMR technique was used to determine the oil content in single corn seeds. Using distinct radio frequency (RF) power, a systematic work was done in kernels with about 10% of moisture, and also in artificially dried seeds with approximated 5% of moisture. For nondried seeds NMR spectra showed clearly the presence of three resonances with different RF saturation factor. For dried seeds, the oil concentration determined by NMR was highly correlated (r = 0,997) with that determined by a gravimetric method. The highest discrepancy between the two methods was found to be about 1,3%. When relative measurements are required as in the case of single kernel for recurrent selection program, precision in the individual selected kernel will be about 2,5%. Applying this technique, a first cycle of recurrent selection using S/sub 1/ lines for low and high oil content was performed in an open pollinated variety. Gain from selection was 12.0 and 14.1% in the populations for high and low oil contents, respectively.

Near infrared hyperspectral imaging of blends of conventional and waxy hard wheats

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Stephen R. Delwiche

2018-02-01

Full Text Available Recent development of hard winter waxy (amylose-free wheat adapted to the North American climate has prompted the quest to find a rapid method that will determine mixture levels of conventional wheat in lots of identity preserved waxy wheat. Previous work documented the use of conventional near infrared (NIR reflectance spectroscopy to determine the mixture level of conventional wheat in waxy wheat, with an examined range, through binary sample mixture preparation, of 0–100% (weight conventional / weight total. The current study examines the ability of NIR hyperspectral imaging of intact kernels to determine mixture levels. Twenty-nine mixtures (0, 1, 2, 3, 4, 5, 10, 15, …, 95, 96, 97, 98, 99, 100% were formed from known genotypes of waxy and conventional wheat. Two-class partial least squares discriminant analysis (PLSDA and statistical pattern recognition classifier models were developed for identifying each kernel in the images as conventional or waxy. Along with these approaches, conventional PLS1 regression modelling was performed on means of kernel spectra within each mixture test sample. Results indicated close agreement between all three approaches, with standard errors of prediction for the better preprocess transformations (PLSDA models or better classifiers (pattern recognition models of approximately 9 percentage units. Although such error rates were slightly greater than ones previously published using non-imaging NIR analysis of bulk whole kernel wheat and wheat meal, the HSI technique offers an advantage of its potential use in sorting operations.

Wheat kernel dimensions: how do they contribute to kernel weight at ...

Indian Academy of Sciences (India)

2011-12-02

Dec 2, 2011 ... yield components, is greatly influenced by kernel dimensions. (KD), such as ..... six linkage gaps, and it covered 3010.70 cM of the whole genome with an ...... Ersoz E. et al. 2009 The Genetic architecture of maize flowering.

The botanical integrity of wheat products influences the gastric distention and satiety in healthy subjects

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Almér Lars-Olof

2008-04-01

Full Text Available Abstract Background Maintenance of the botanical integrity of cereal kernels and the addition of acetic acid (as vinegar in the product or meal has been shown to lower the postprandial blood glucose and insulin response and to increase satiety. However, the mechanism behind the benefits of acetic acid on blood glucose and satiety is not clear. We hypothesized that the gastric emptying rate could be involved. Thus, the aim of this study was to evaluate the possible influence of maintained botanical integrity of cereals and the presence of acetic acid (vinegar on gastric emptying rate (GER, postprandial blood glucose and satiety. Methods Fifteen healthy subjects were included in a blinded crossover trial, and thirteen of the subjects completed the study. Equicarbohydrate amounts of the following wheat-based meals were studied: white wheat bread, whole-kernel wheat bread or wholemeal wheat bread served with white wine vinegar. The results were compared with a reference meal consisting of white wheat bread without vinegar. The GER was measured with standardized real-time ultrasonography using normal fasting blood glucose Results The whole-kernel wheat bread with vinegar resulted in significantly higher ( Conclusion The present study shows higher satiety after a whole-kernel wheat bread meal with vinegar. This may be explained by increased antral distension after ingestion of intact cereal kernels but, in this study, not by a lower gastric emptying rate or higher postprandial blood glucose response. Trial registration NTR1116

Single pass kernel k-means clustering method

Indian Academy of Sciences (India)

paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

Self-Organized Crystallization Patterns from Evaporating Droplets of Common Wheat Grain Leakages as a Potential Tool for Quality Analysis

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Maria Olga Kokornaczyk

2011-01-01

Full Text Available We studied the evaporation-induced pattern formation in droplets of common wheat kernel leakages prepared out of ancient and modern wheat cultivars as a possible tool for wheat quality analysis. The experiments showed that the substances which passed into the water during the soaking of the kernels created crystalline structures with different degrees of complexity while the droplets were evaporating. The forms ranged from spots and simple structures with single ramifications, through dendrites, up to highly organized hexagonal shapes and fractal-like structures. The patterns were observed and photographed using dark field microscopy in small magnifications. The evaluation of the patterns was performed both visually and by means of the fractal dimension analysis. From the results, it can be inferred that the wheat cultivars differed in their pattern-forming capacities. Two of the analyzed wheat cultivars showed poor pattern formation, whereas another two created well-formed and complex patterns. Additionally, the wheat cultivars were analyzed for their vigor by means of the germination test and measurement of the electrical conductivity of the grain leakages. The results showed that the more vigorous cultivars also created more complex patterns, whereas the weaker cultivars created predominantly poor forms. This observation suggests a correlation between the wheat seed quality and droplet evaporation patterns.

Modeling of the endosperm crush response profile of hard red spring wheat using a single kernel characterization system

Science.gov (United States)

When a wheat endosperm is crushed the force profile shows viscoelastic response and the modulus of elasticity is an important parameter that might have substantial influence on wheat milling. An experiment was performed to model endosperm crush response profile (ECRP) and to determine the modulus o...

Density separation as a strategy to reduce the enzyme load of preharvest sprouted wheat and enhance its bread making quality.

Science.gov (United States)

Olaerts, Heleen; De Bondt, Yamina; Courtin, Christophe M

2018-02-15

As preharvest sprouting of wheat impairs its use in food applications, postharvest solutions for this problem are required. Due to the high kernel to kernel variability in enzyme activity in a batch of sprouted wheat, the potential of eliminating severely sprouted kernels based on density differences in NaCl solutions was evaluated. Compared to higher density kernels, lower density kernels displayed higher α-amylase, endoxylanase, and peptidase activities as well as signs of (incipient) protein, β-glucan and arabinoxylan breakdown. By discarding lower density kernels of mildly and severely sprouted wheat batches (11% and 16%, respectively), density separation increased flour FN of the batch from 280 to 345s and from 135 to 170s and increased RVA viscosity. This in turn improved dough handling, bread crumb texture and crust color. These data indicate that density separation is a powerful technique to increase the quality of a batch of sprouted wheat. Copyright © 2017 Elsevier Ltd. All rights reserved.

Higher Fusarium Toxin Accumulation in Grain of Winter Triticale Lines Inoculated with Fusarium culmorum as Compared with Wheat.

Science.gov (United States)

Góral, Tomasz; Wiśniewska, Halina; Ochodzki, Piotr; Walentyn-Góral, Dorota

2016-10-18

Resistance to Fusarium head blight in 32 winter triticale and 34 winter wheat accessions was evaluated. Triticale and wheat were sown in field experiments in two locations. At the time of flowering, heads were inoculated with three Fusarium culmorum isolates. Fusarium head blight index was scored and after the harvest percentage of Fusarium damaged kernels was assessed. Grain was analysed for type B trichothecenes (deoxynivalenol and derivatives, nivalenol) and zearalenone (ZEN) content. The average Fusarium head blight indexes were 28.0% for wheat and 19.2% for triticale accessions. The percentage of Fusarium damaged kernels was also higher for wheat and came to 55.6%, while for triticale this figure was 40.2%. The average content of deoxynivalenol (DON) for wheat amounted to 11.65 mg/kg and was lower than the result for triticale which was 14.12 mg/kg. The average contents of nivalenol were similar in both cereals: 4.13 mg/kg and 5.19 mg/kg for wheat and triticale respectively. Considerable amounts of DON derivatives in the cereals were also detected. The ZEN content in the grain was 0.60 mg/kg for wheat and 0.66 mg/kg for triticale. Relationships between Fusarium head blight index, Fusarium damaged kernels and mycotoxin contents were statistically significant for wheat and mostly insignificant for triticale. Triticale proved to have less infected heads and kernels than wheat. However, the content of type B trichothecenes was higher in triticale grain than in wheat grain.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

Science.gov (United States)

Li, Faji; Wen, Weie; He, Zhonghu; Liu, Jindong; Jin, Hui; Cao, Shuanghe; Geng, Hongwei; Yan, Jun; Zhang, Pingzhi; Wan, Yingxiu; Xia, Xianchun

2018-06-01

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

Higher Fusarium Toxin Accumulation in Grain of Winter Triticale Lines Inoculated with Fusarium culmorum as Compared with Wheat †

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Góral, Tomasz; Wiśniewska, Halina; Ochodzki, Piotr; Walentyn-Góral, Dorota

2016-01-01

Resistance to Fusarium head blight in 32 winter triticale and 34 winter wheat accessions was evaluated. Triticale and wheat were sown in field experiments in two locations. At the time of flowering, heads were inoculated with three Fusarium culmorum isolates. Fusarium head blight index was scored and after the harvest percentage of Fusarium damaged kernels was assessed. Grain was analysed for type B trichothecenes (deoxynivalenol and derivatives, nivalenol) and zearalenone (ZEN) content. The average Fusarium head blight indexes were 28.0% for wheat and 19.2% for triticale accessions. The percentage of Fusarium damaged kernels was also higher for wheat and came to 55.6%, while for triticale this figure was 40.2%. The average content of deoxynivalenol (DON) for wheat amounted to 11.65 mg/kg and was lower than the result for triticale which was 14.12 mg/kg. The average contents of nivalenol were similar in both cereals: 4.13 mg/kg and 5.19 mg/kg for wheat and triticale respectively. Considerable amounts of DON derivatives in the cereals were also detected. The ZEN content in the grain was 0.60 mg/kg for wheat and 0.66 mg/kg for triticale. Relationships between Fusarium head blight index, Fusarium damaged kernels and mycotoxin contents were statistically significant for wheat and mostly insignificant for triticale. Triticale proved to have less infected heads and kernels than wheat. However, the content of type B trichothecenes was higher in triticale grain than in wheat grain. PMID:27763547

Modeling end-use quality in U. S. soft wheat germplasm

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End-use quality in soft wheat (Triticum aestivum L.) can be assessed by a wide array of measurements, generally categorized into grain, milling, and baking characteristics. Samples were obtained from four regional nurseries. Selected parameters included: test weight, kernel hardness, kernel size, ke...

Physical characteristics of some wheat genotypes cultivated in Lake District of Turkey

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Hülya GÜL

2012-12-01

Full Text Available This study was carried out to determine the physical characteristics of wheat genotypes cultivated in lakes district of Turkey. The genotypes were collected from the center of Isparta and Burdur province, districts and selected five different villages in this district at harvest in 2011. Totaly 19 genotypes named as; Hard Wheat, Red Kazmalı Wheat, Lavanta, Red Wheat, Burgaz, Osmaniye and Yunak (Landraces, Kızıltan-91, İzmir 85, Bezostoya, Ankara 98, Sönmez 2001, Çeşit-1252, Hatay 86, Mirzabey, Kunduru-1149, Gerek-79, Gediz-75 and Cumhuriyet-75 (Wheat registered cultivars were collected from these districts. Physical characteristics of the wheat samples brought to laboratory were analyzed as completely randomized design with three replications. Foreign matters of wheats were determined according to TS 2974 standards. 4 genotypes were found at second degree, 5 genotypes were at third degree and remaining 10 genotypes were found out of these rating. Highest thousand kernel weight and hectoliter weight were determined on Mirzabey and Sönmez 2001 respectively in bread wheat varieties while highest thousand kernel weight and hectoliter weight were determeined on Kunduru 1149 and Burgaz respectively in durum wheat varieties.

Effects of Sowing Date and Limited Irrigation on Yield and Yield Components of Five Rainfed Wheat Varieties in Maragheh Region

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A. R. Tavakkoli

2013-03-01

Full Text Available In order to investigate the effects of sowing date (SD and single irrigation (SI amounts on yield and yield components of rainfed wheat varieties, a field experiment was conducted as split-split plots arranged in a randomized complete blocks design with three replications during 2002-2004 at main station of Dryland Agricultural Research Institute in Maragheh, Iran. Treatments included three sowing dates (early, normal and late, three levels of single irrigation (rainfed, 50 mm and 100 mm only at planting time and five wheat varieties (three numbered lines, Azar2 and double-cross Shahi. Results revealed that interactions of SD, SI and wheat varieties were significant for grain yield, number of kernels per spike and water productivity (P≤0.01. Single irrigation at normal planting time increased grain yield, straw, biomass, harvest index, and water productivity. Grain yield and water productivity were increased by 131% and 84.8%, respectively. Single irrigation at late planting time was not significant on agronomic traits and produced low water productivity. Regarding the reaction of wheat to planting date and single irrigation, results showed that normal single irrigation can improve yield, yield components and water productivity index. The effectiveness of single irrigation under dryland conditions can be observed in all wheat cultivars. Although this effectiveness on yield and yield components is observable, but it is necessary to select the time of irrigation properly.

Colonisation of winter wheat grain by Fusarium spp. and mycotoxin content as dependent on a wheat variety, crop rotation, a crop management system and weather conditions.

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Czaban, Janusz; Wróblewska, Barbara; Sułek, Alicja; Mikos, Marzena; Boguszewska, Edyta; Podolska, Grażyna; Nieróbca, Anna

2015-01-01

Field experiments were conducted during three consecutive growing seasons (2007/08, 2008/09 and 2009/10) with four winter wheat (Triticum aestivum L.) cultivars - 'Bogatka', 'Kris', 'Satyna' and 'Tonacja' - grown on fields with a three-field crop rotation (winter triticale, spring barley, winter wheat) and in a four-field crop rotation experiment (spring wheat, spring cereals, winter rapeseed, winter wheat). After the harvest, kernels were surface disinfected with 2% NaOCl and then analysed for the internal infection by different species of Fusarium. Fusaria were isolated on Czapek-Dox iprodione dichloran agar medium and identified on the basis of macro- and micro-morphology on potato dextrose agar and synthetic nutrient agar media. The total wheat grain infection by Fusarium depended mainly on relative humidity (RH) and a rainfall during the flowering stage. Intensive rainfall and high RH in 2009 and 2010 in the period meant the proportions of infected kernels by the fungi were much higher than those in 2008 (lack of precipitation during anthesis). Weather conditions during the post-anthesis period changed the species composition of Fusarium communities internally colonising winter wheat grain. The cultivars significantly varied in the proportion of infected kernels by Fusarium spp. The growing season and type of crop rotation had a distinct effect on species composition of Fusarium communities colonising the grain inside. A trend of a higher percentage of the colonised kernels by the fungi in the grain from the systems using more fertilisers and pesticides as well as the buried straw could be perceived. The most frequent species in the grain were F. avenaceum, F. tricinctum and F. poae in 2008, and F. avenaceum, F. graminearum, F. tricinctum and F. poae in 2009 and 2010. The contents of deoxynivalenol and zearalenon in the grain were correlated with the percentage of kernels colonised by F. graminearum and were the highest in 2009 in the grain from the four

Impact of Triticum mosaic virus infection on hard winter wheat milling and bread baking quality.

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Miller, Rebecca A; Martin, T Joe; Seifers, Dallas L

2012-03-15

Triticum mosaic virus (TriMV) is a newly discovered wheat virus. Information regarding the effect of wheat viruses on milling and baking quality is limited. The objective of this study was to determine the impact of TriMV infection on the kernel characteristics, milling yield and bread baking quality of wheat. Commercial hard winter varieties evaluated included RonL, Danby and Jagalene. The TriMV resistance of RonL is low, while that of Danby and Jagalene is unknown. KS96HW10-3, a germplasm with high TriMV resistance, was included as a control. Plots of each variety were inoculated with TriMV at the two- to three-leaf stage. Trials were conducted at two locations in two crop years. TriMV infection had no effect on the kernel characteristics, flour yield or baking properties of KS96HW10-3. The effect of TriMV on the kernel characteristics of RonL, Danby and Jagalene was not consistent between crop years and presumably an environmental effect. The flour milling and bread baking properties of these three varieties were not significantly affected by TriMV infection. TriMV infection of wheat plants did not affect harvested wheat kernel characteristics, flour milling properties or white pan bread baking quality. Copyright © 2011 Society of Chemical Industry.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

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Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Emotion Recognition from Single-Trial EEG Based on Kernel Fisher’s Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

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Yi-Hung Liu

2014-07-01

Full Text Available Electroencephalogram-based emotion recognition (EEG-ER has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI. However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher’s discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher’s emotion pattern (KFEP, and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68% and arousal (84.79% among all testing methods.

Visual, instrumental, mycological and mycotoxicological characterization of wheat inoculated with and protected against Alternaria spp.

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Janić-Hajnal Elizabet P.

2016-01-01

Full Text Available The aim of this work was to characterize visual properties, instrumentally measured colour properties, field fungi presence and Alternaria toxins levels in wheat samples grown under conditions aimed at inhibition and stimulation of wheat infection with fungi from the Alternaria genus. Experiment was carried out on the wheat treated by fungicide and wheat inoculated by Alternaria spp., while non treated wheat was used as a control. Statistically significant difference was observed between all three treatments using visual scale. Protected wheat samples were significantly different from other samples in terms of all measured colour parameters while inoculated and control wheat samples were significantly different in terms of lightness and dominant wavelength. Identification of field fungi in the all examined wheat samples showed that the dominant mycotoxigenic fungus was Alternaria spp., followed by Fusarium spp. The content of Alternaria toxins in samples of wheat hulls and dehulled kernels point out at higher concentrations of Alternaria toxins in hulls than in dehulled kernels. [Projekat Ministarstvo nauke Republike Srbije, br. III 46001 i br. III 46005

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

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Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

90Sr and 137Cs contamination of wheat produced in Japan. Survey and analysis during the years 1959 through 1995 including the Chernobyl accident

International Nuclear Information System (INIS)

Komamura, Misako; Tsumura, Akito; Kihou, Nobuharu; Kodaira, Kiyoshi

2002-01-01

This paper attempts to discuss the influences of global-scale radioactive fallout on wheat produced in Japan. For this purpose, a set of wheat samples was collected annually from sixteen National and Prefectural Experimental Farms during the years from 1959 to 1995. According to the graph presenting year-to-year variations in the nationwide averages of 90 Sr and 137 Cs contents (mBq/kg) in wheat kernels, the sharp peak was first marked in 1963 with 12300 for 90 Sr and 43600 for 137 Cs. In 1966, however, the nuclide contents dropped drastically to 2360 for 90 Sr and 2870 for 137 Cs respectively. In the years following, both nuclides continued to decrease slowly although there were minor fluctuations. It is noticeable that low-level 137 Cs contamination was caused in Japan's wheat in 1981, the year after the nuclear testing in China. It is also noticeable that 137 Cs contents in wheat kernels increased to 5960 in 1986 when the Chernobyl nuclear power plant accident happened, although it dropped back to its normal level of 40 in the year after. The following are also discussed in this paper: Year to year variations in the ratio of 90 Sr to 137 Cs contents in wheat kernels and wheat flour. Regional differences in 90 Sr and 137 Cs contents in wheat kernels. Comparison of 90 Sr and 137 Cs contents in wheat kernels and unpolished rice. Direct and indirect pathways of 90 Sr and 137 Cs that contaminate wheat. Influence of the Chernobyl power plant accident. Suggestions about the ways of estimating the level of 137 Cs contamination in case of nuclear accidents, if any. (author)

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

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Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

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Jaime Cuevas

2017-01-01

Full Text Available The phenomenon of genotype × environment (G × E interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects ( u that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP and Gaussian (Gaussian kernel, GK. The other model has the same genetic component as the first model ( u plus an extra component, f, that captures random effects between environments that were not captured by the random effects u . We used five CIMMYT data sets (one maize and four wheat that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u   and   f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u .

Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

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Jeffrey B. Endelman

2011-11-01

Full Text Available Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR, which is equivalent to best linear unbiased prediction (BLUP when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat ( L. grain yield but equivalent for several maize ( L. traits.

Comparison of tungsten carbide and stainless steel ball bearings for grinding single maize kernels in a reciprocating grinder

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Reciprocating grinders can grind single maize kernels by shaking the kernel in a vial with a ball bearing. This process results in a grind quality that is not satisfactory for many experiments. Tungesten carbide ball bearings are nearly twice as dense as steel, so we compared their grinding performa...

Fumonisins production potential of Fusarium verticillioides isolated from Serbian maize and wheat kernels

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Krstović Saša Z.

2017-01-01

Full Text Available The production of fumonisins by potentially toxigenic Fusarium verticillioides isolates originating from Serbian maize and wheat kernels was tested in vitro. A total of six F. verticillioides isolates were incubated on yeast extract sucrose medium (YESA for 4 weeks at 25 °C in the dark. Their toxin production potential was tested by applying a modified HPLC method for determination of fumonisins in cereals, since the TLC method gave no results. Analyses were performed on a HPLC-FLD system after sample extraction from YESA and extract cleanup on a SPE column. Although the isolates were tested for fumonisin B1, B2 and B3, only fumonisin B1 was detected. The results showed that all tested isolates had toxigenic potential for fumonisin B1 production. The average fumonisin B1 production of the isolates ranged from 7 to 289 μg/kg, thus indicating a highly variable toxigenic potential among the isolates. Isolate 1282 expressed the highest toxigenic potential for fumonisin B1 production (289 μg/kg, while isolate 2533/A showed a questionable potential for fumonisin production (7 μg/kg. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 31023

Systemic Growth of F. graminearum in Wheat Plants and Related Accumulation of Deoxynivalenol

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Antonio Moretti

2014-04-01

Full Text Available Fusarium head blight (FHB is an important disease of wheat worldwide caused mainly by Fusarium graminearum (syn. Gibberella zeae. This fungus can be highly aggressive and can produce several mycotoxins such as deoxynivalenol (DON, a well known harmful metabolite for humans, animals, and plants. The fungus can survive overwinter on wheat residues and on the soil, and can usually attack the wheat plant at their point of flowering, being able to infect the heads and to contaminate the kernels at the maturity. Contaminated kernels can be sometimes used as seeds for the cultivation of the following year. Poor knowledge on the ability of the strains of F. graminearum occurring on wheat seeds to be transmitted to the plant and to contribute to the final DON contamination of kernels is available. Therefore, this study had the goals of evaluating: (a the capability of F. graminearum causing FHB of wheat to be transmitted from the seeds or soil to the kernels at maturity and the progress of the fungus within the plant at different growth stages; (b the levels of DON contamination in both plant tissues and kernels. The study has been carried out for two years in a climatic chamber. The F. gramineraum strain selected for the inoculation was followed within the plant by using Vegetative Compatibility technique, and quantified by Real-Time PCR. Chemical analyses of DON were carried out by using immunoaffinity cleanup and HPLC/UV/DAD. The study showed that F. graminearum originated from seeds or soil can grow systemically in the plant tissues, with the exception of kernels and heads. There seems to be a barrier that inhibits the colonization of the heads by the fungus. High levels of DON and F. graminearum were found in crowns, stems, and straw, whereas low levels of DON and no detectable levels of F. graminearum were found in both heads and kernels. Finally, in all parts of the plant (heads, crowns, and stems at milk and vitreous ripening stages, and straw at

Haplotypes of the TaGS5-A1 gene are associated with thousand-kernel weight in Chinese bread wheat

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Wang Sha Sha

2016-06-01

Full Text Available In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG, which occurred in the Sp1 domain of the promoter sequence. Combined with previous single nucleotide polymorphism (SNP in the TaGS5-A1 exon sequence, four genotypes were formed at the TaGS5-A1 locus and were designated as TaGS5-A1a-a, TaGS5-A1a-b, TaGS5-A1b-a, and TaGS5-A1b-b, respectively. Analysis of the association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with the TaGS5-A1a-b allele possessed significantly higher thousand-kernel weight (TKW and lower plant height than cultivars with the TaGS5-A1a-a allele, and cultivars with the TaGS5-A1b-b allele showed higher TKW than cultivars with the TaGS5-A1b-a allele. The differences of these traits between the TaGS5-A1a-a and TaGS5-A1a-b alleles were larger than those of the TaGS5-A1b-a and TaGS5-A1b-b alleles, suggesting that the -1925G insertion plays the more important role in TaGS5-A1a genotypes than in TaGS5-A1b genotypes. qRT-PCR indicated that TaGS5-A1b-b possessed the significantly highest expression level among four TaGS5-A1 haplotypes in mature seeds and further showed a significantly higher expression level than TaGS5-A1b-a at five different developmental stages of the seeds, suggesting that high expression of TaGS5-A1 was positively associated with high TKW in bread wheat. This study could provide a relatively superior genotype in view of TKW in wheat breeding programs and could also provide important information for dissection of the regulatory mechanism of the yield-related traits.

Genetic evolution and utilization of wheat germplasm resources in Huanghuai winter wheat region of China

International Nuclear Information System (INIS)

Xiyong, C.; Haixia, X.U.; Feng, C.

2011-01-01

To determine the genetic variation of wheat germplasm resources and improve their use in wheat breeding, 215 wheat cultivars and advanced lines from the Huanghuai Wheat Region of China were used to identify 14 agronomic traits and 7 quality traits, as well as the evolution and utilization of high molecular weight glutenin subunits (HMW-GS) and low molecular weight-glutenin subunits (LMW-GS). From land race cultivars to current cultivars there had been significant increases in grain numbers spike/sip -1/, grain weight spike/sup -1/, 1000-kernel weight, grain weight plant/sup -1/, spikelet number spike/sup -1/, sterile spikelet numbers spike/sup -1/, flag leaf width, and flag leaf area. There had been significant decreases in spike number plant/sup -1/, plant height, the first inter node length, flag leaf length, kernel protein content and wet gluten content. Based on Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) results, a novel HMW-GS combination 20/8 was identified in 1B chromosome of Chinese landrace cultivar Heputou. Subunits 22, 20/8, 2.2+12, and GluB3a were only found in cultivars before the 1960s, and subunits 6+8, 13+16, 3+12, and 4+12 were only found in the cultivars after the 1980s. The average diversity index of 21 traits and allele variance of HMW-GS showed a decreasing-increasing-decreasing tendency. HMW-GS and LMW-GS combination-type cultivars showed an increasing-decreasing tendency. Before the 1980s, most parental strains were from foreign cultivars and landrace cultivars, while after the 1980s, most parental strains were from released cultivars and germplasm created by distant hybridization. This study provided useful information for improvement of wheat breeding in Huanghuai winter wheat region. (author)

Influence of wheat type and pretreatment on fungal growth in solid-state fermentation

NARCIS (Netherlands)

Hoogschagen, M.; Zhu, Y.; As, H. van; Tramper, J.; Rinzema, A.

2001-01-01

The respiration kinetics of Aspergillus oryzae on different varieties of whole wheat kernels were studied. Six wheat varieties were pretreated in two different ways. Five of the six substrates fermented similarly and independently of the pretreatment method. However, pretreatment affected

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

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Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

Directory of Open Access Journals (Sweden)

Yotam Luz

Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

Interaction Effect Of Irradiation And Fertilization On Grain Yield, Kernel Weight And Severity Of Wheat To Septoria Tritici Blotch

International Nuclear Information System (INIS)

Arabi, M. A.; Jawhar, M.

2004-01-01

Field research was undertaken, for two growing seasons, to investigate the effects of soil fertilization with potassium (K 2 SO 4 , 36% K) and nitrogen (urea, 46% N), seed irradiation with gamma rays (0, 5, 10 and 15 Gy) and their combinations on the grain yield, 1000-kernel weight and severity of Mycosphaerella graminicola on wheat. Two Syrian wheat cultivars; Bohuth 6 (Triticum aestivum L.) and Bohuth 5 (T. turgidum var durum Desf.) were used in this study. Plants were inoculated with a mixture of 15 virulent isolates of the pathogen at the growth stage (GS) 33-34. Results indicated that the average response to fertilizer application and irradiation treatments was dependent on the susceptibility level of cultivars compared with the control. The level of infection of the combined NK and 15 Gy treatment was reduced by 9 and 46 % in 1998 and by 6 and 42 % in 1999 for Bohuth 5 and Bohuth 6, respectively. This was associated with increased grain yield by 68 and 59% in 1998 and 59 and 33% in 1999, respectively. Highest yield losses from M. graminicola occurred in the treatment of nil fertilization and irradiation. Grain weight was increased by various treatments applied, but such an increase was highest in the combined NK and 15 Gy treatment. This combined treatment appeared to be more effective on calcareous soils, which are typical of Mediterranean environments. (Authors)

Genetic variability, path-coefficient and correlation studies in twenty elite bread-wheat (triticum aestivum L.) lines

International Nuclear Information System (INIS)

Mujahid, M.Y.; Asif, M.; Ahmad, I.; Kisana, N.A.; Ahmad, Z.; Asim, M.

2005-01-01

Twenty bread-wheat elite lines of diverse origin, developed by various research institutes in the country, were tested and evaluated at National Agricultural Research Centre (NARC) under optimum irrigated conditions. Significant variation was observed for all the traits studied viz: days to heading, days to maturity, kernel weight, test weight and grain yield. Genotypic and phenotypic correlations were computed and the direct and indirect contributions of each trait towards grain-yield were determined. Grain-yield showed significant association with test weight and kernel weight. Direct positive effects of kernel weight and test weight towards grain-yield suggest the effectiveness of these traits to select and identify the desirable wheat- genotypes for a target environment. (author)

Prolamin proteins alteration in durum wheat by species of the genus Eurygaster and Aelia (Insecta, Hemiptera)

International Nuclear Information System (INIS)

Salis, L.; Goula, M.; Valero, J.; Gordun, E.

2010-01-01

Wheat bugs are widely distributed in various areas of Europe, Asia and North Africa. Species belonging to the genus Eurygaster and Aelia pierce wheat kernels affecting protein quality. The effects of these insects feeding activity have been studied mainly in bread wheat (Triticum aestivum L.). This study provides information on the degradation of prolamin proteins (glutenins and gliadins) of bug-damaged durum wheat (Triticum turgidum L. var durum) in six cultivars grown in Sardinia (Italy). Samples of whole flour mixture of 70% sound wheat and 30% damaged wheat were hydrated and incubated at two temperatures (45 and 4 degree centigrade), for different periods of time (0, 1 and 3 h). Glutenin and gliadin content was analysed using free zone capillary electrophoresis. The presence of bug-damaged kernels had influence on the quality of durum wheat proteins. Glutenins were rapidly degraded independently to incubation temperature. Gliadin degradation, however, took place with dependence on temperature and incubation time. Therefore glutenin degradation was possibly not due solely to the activity of proteolytic enzymes but also to some other as yet unknown factor linked to wheat bugs feeding activity. (Author) 35 refs.

Prolamin proteins alteration in durum wheat by species of the genus Eurygaster and Aelia (Insecta, Hemiptera)

Energy Technology Data Exchange (ETDEWEB)

Salis, L.; Goula, M.; Valero, J.; Gordun, E.

2010-07-01

Wheat bugs are widely distributed in various areas of Europe, Asia and North Africa. Species belonging to the genus Eurygaster and Aelia pierce wheat kernels affecting protein quality. The effects of these insects feeding activity have been studied mainly in bread wheat (Triticum aestivum L.). This study provides information on the degradation of prolamin proteins (glutenins and gliadins) of bug-damaged durum wheat (Triticum turgidum L. var durum) in six cultivars grown in Sardinia (Italy). Samples of whole flour mixture of 70% sound wheat and 30% damaged wheat were hydrated and incubated at two temperatures (45 and 4 degree centigrade), for different periods of time (0, 1 and 3 h). Glutenin and gliadin content was analysed using free zone capillary electrophoresis. The presence of bug-damaged kernels had influence on the quality of durum wheat proteins. Glutenins were rapidly degraded independently to incubation temperature. Gliadin degradation, however, took place with dependence on temperature and incubation time. Therefore glutenin degradation was possibly not due solely to the activity of proteolytic enzymes but also to some other as yet unknown factor linked to wheat bugs feeding activity. (Author) 35 refs.

Transcript-specific, single-nucleotide polymorphism discovery and linkage analysis in hexaploid bread wheat (Triticum aestivum L.).

Science.gov (United States)

Allen, Alexandra M; Barker, Gary L A; Berry, Simon T; Coghill, Jane A; Gwilliam, Rhian; Kirby, Susan; Robinson, Phil; Brenchley, Rachel C; D'Amore, Rosalinda; McKenzie, Neil; Waite, Darren; Hall, Anthony; Bevan, Michael; Hall, Neil; Edwards, Keith J

2011-12-01

Food security is a global concern and substantial yield increases in cereal crops are required to feed the growing world population. Wheat is one of the three most important crops for human and livestock feed. However, the complexity of the genome coupled with a decline in genetic diversity within modern elite cultivars has hindered the application of marker-assisted selection (MAS) in breeding programmes. A crucial step in the successful application of MAS in breeding programmes is the development of cheap and easy to use molecular markers, such as single-nucleotide polymorphisms. To mine selected elite wheat germplasm for intervarietal single-nucleotide polymorphisms, we have used expressed sequence tags derived from public sequencing programmes and next-generation sequencing of normalized wheat complementary DNA libraries, in combination with a novel sequence alignment and assembly approach. Here, we describe the development and validation of a panel of 1114 single-nucleotide polymorphisms in hexaploid bread wheat using competitive allele-specific polymerase chain reaction genotyping technology. We report the genotyping results of these markers on 23 wheat varieties, selected to represent a broad cross-section of wheat germplasm including a number of elite UK varieties. Finally, we show that, using relatively simple technology, it is possible to rapidly generate a linkage map containing several hundred single-nucleotide polymorphism markers in the doubled haploid mapping population of Avalon × Cadenza. © 2011 The Authors. Plant Biotechnology Journal © 2011 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd.

Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers.

Science.gov (United States)

Mogensen, J M; Sørensen, S M; Sulyok, M; van der Westhuizen, L; Shephard, G S; Frisvad, J C; Thrane, U; Krska, R; Nielsen, K F

2011-12-01

Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n=15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins. The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin content by 71%. Of the 400 kernels, 80 were screened for 186 microbial metabolites by liquid chromatography-tandem mass spectrometry, detecting 17 other fungal metabolites, including fusaric acid, equisetin, fusaproliferin, beauvericin, cyclosporins, agroclavine, chanoclavine, rugulosin and emodin. Fusaric acid in samples without fumonisins indicated the possibility of using non-toxinogenic Fusaria as biocontrol agents to reduce fumonisin exposure, as done for Aspergillus flavus. This is the first report of mycotoxin profiling in single naturally infected maize kernels. © 2011 Taylor & Francis

Evaluation of the Single-precision Floatingpoint Vector Add Kernel Using the Intel FPGA SDK for OpenCL

Energy Technology Data Exchange (ETDEWEB)

Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-04-20

Open Computing Language (OpenCL) is a high-level language that enables software programmers to explore Field Programmable Gate Arrays (FPGAs) for application acceleration. The Intel FPGA software development kit (SDK) for OpenCL allows a user to specify applications at a high level and explore the performance of low-level hardware acceleration. In this report, we present the FPGA performance and power consumption results of the single-precision floating-point vector add OpenCL kernel using the Intel FPGA SDK for OpenCL on the Nallatech 385A FPGA board. The board features an Arria 10 FPGA. We evaluate the FPGA implementations using the compute unit duplication and kernel vectorization optimization techniques. On the Nallatech 385A FPGA board, the maximum compute kernel bandwidth we achieve is 25.8 GB/s, approximately 76% of the peak memory bandwidth. The power consumption of the FPGA device when running the kernels ranges from 29W to 42W.

The use of near infrared transmittance kernel sorting technology to salvage high quality grain from grain downgraded due to Fusarium damage

Directory of Open Access Journals (Sweden)

Michael E. Kautzman

2015-03-01

Full Text Available The mycotoxins associated with specific Fusarium fungal infections of grains are a threat to global food and feed security. These fungal infestations are referred to as Fusarium Head Blight (FHB and lead to Fusarium Damaged Kernels (FDK. Incidence of FDK >0.25% will lower the grade, with a tolerance of 5% FDK for export feed grain. During infestation, the fungi can produce a variety of mycotoxins, the most common being deoxynivalenol (DON. Fusarium Damaged Kernels have been associated with reduced crude protein (CP, lowering nutritional, functional and grade value. New technology has been developed using Near Infrared Transmittance (NIT spectra that estimate CP of individual kernels of wheat, barley and durum. Our objective is to evaluate the technology's capability to reduce FDK and DON of downgraded wheat and ability to salvage high quality safe kernels. In five FDK downgraded sources of wheat, the lowest 20% CP kernels had significantly increased FDK and DON with the high CP fractions having decreased FDK and DON, thousand kernel weights (TKW and bushel weight (Bu. Strong positive correlations were observed between FDK and DON (r = 0.90; FDK and grade (r = 0.62 and DON and grade (r = 0.62. Negative correlations were observed between FDK and DON with CP (r = −0.27 and −0.32; TKW (r = −0.45 and −0.54 and Bu (r = −0.79 and −0.74. Results show improved quality and value of Fusarium downgraded grain using this technology.

Hydration kinetics of some durum and bread wheat varieties grown in south-eastern region of turkey

International Nuclear Information System (INIS)

Yildirm, A.

2017-01-01

Hydration kinetics of wheat varieties grown in South-Eastern Region of Turkey, covering a temperature range from 25 to 50 degree C was examined. Peleg's model together with Arrhenius relationship were successfully used to evaluate water uptake of some Durum (Local names; Zenit and BurgosBurgos) and Bread (Local names; Dariyel and Karatopak) wheat varieties during soaking at a temperature range of 25-50 degree C. Model was found to be suitable for describing the soaking behaviour of wheat kernels with a coefficient of determination (R2) and Root mean square error (RMSE) greater than 0.9805, and less than 0.051, respectively. The Peleg rate and capacity constants, K1 and K2, were affected by temperature and wheat varieties. Activation energy values of Zenit, BurgosBurgos, Dariyel and Karatopak wheats were found as 39.94, 38.03, 36.25 and 29.54 kJ mol-1, respectively. Zenit wheat was the least hydrated while Karatopak was the most hydrated one due to kernel size and protein content. General equations to describe the water uptake of wheat varieties as a function of soaking time, temperature and initial moisture content were developed. These derived equations can be used for wheat operations such as tempering, mixing, knedding etc. (author)

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng

2016-07-06

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

Directory of Open Access Journals (Sweden)

Guozheng Liu

Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

Science.gov (United States)

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

TaGW2, a Good Reflection of Wheat Polyploidization and Evolution.

Science.gov (United States)

Qin, Lin; Zhao, Junjie; Li, Tian; Hou, Jian; Zhang, Xueyong; Hao, Chenyang

2017-01-01

Hexaploid wheat consists of three subgenomes, namely, A, B, and D. These well-characterized ancestral genomes also exist at the diploid and tetraploid levels, thereby rendering wheat as a good model species for studying polyploidization. Here, we performed intra- and inter-species comparative analyses of wheat and its relatives to dissect polymorphism and differentiation of the TaGW2 genes. Our results showed that genetic diversity of TaGW2 decreased with progression from the diploids to tetraploids and hexaploids. The strongest selection occurred in the promoter regions of TaGW2-6A and TaGW2-6B . Phylogenetic trees clearly indicated that Triticum urartu and Ae. speltoides were the donors of the A and B genomes in tetraploid and hexaploid wheats. Haplotypes detected among hexaploid genotypes traced back to the tetraploid level. Fst and π values revealed that the strongest selection on TaGW2 occurred at the tetraploid level rather than in hexaploid wheat. This infers that grain size enlargement, especially increased kernel width, mainly occurred in tetraploid genotypes. In addition, relative expression levels of TaGW2s significantly declined from the diploid level to tetraploids and hexaploids, further indicating that these genes negatively regulate kernel size. Our results also revealed that the polyploidization events possibly caused much stronger differentiation than domestication and breeding.

Laboratory-scale dry/wet-milling process for the extraction of starch and gluten from wheat

NARCIS (Netherlands)

Steeneken, P.A.M.; Helmens, H.J.

2009-01-01

A laboratory-scale process is presented for the manufacture of starch and gluten from wheat. Main feature of this process is that whole wheat kernels are crushed dry between smooth rolls prior to wet disintegration in excess water in such way that gluten formation is prevented and fibres can be

The carotenoid biosynthetic and catabolic genes in wheat and their association with yellow pigments.

Science.gov (United States)

Colasuonno, Pasqualina; Lozito, Maria Luisa; Marcotuli, Ilaria; Nigro, Domenica; Giancaspro, Angelica; Mangini, Giacomo; De Vita, Pasquale; Mastrangelo, Anna Maria; Pecchioni, Nicola; Houston, Kelly; Simeone, Rosanna; Gadaleta, Agata; Blanco, Antonio

2017-01-31

In plants carotenoids play an important role in the photosynthetic process and photo-oxidative protection, and are the substrate for the synthesis of abscisic acid and strigolactones. In addition to their protective role as antioxidants and precursors of vitamin A, in wheat carotenoids are important as they influence the colour (whiteness vs. yellowness) of the grain. Understanding the genetic basis of grain yellow pigments, and identifying associated markers provide the basis for improving wheat quality by molecular breeding. Twenty-four candidate genes involved in the biosynthesis and catabolism of carotenoid compounds have been identified in wheat by comparative genomics. Single nucleotide polymorphisms (SNPs) found in the coding sequences of 19 candidate genes allowed their chromosomal location and accurate map position on two reference consensus maps to be determined. The genome-wide association study based on genotyping a tetraploid wheat collection with 81,587 gene-associated SNPs validated quantitative trait loci (QTLs) previously detected in biparental populations and discovered new QTLs for grain colour-related traits. Ten carotenoid genes mapped in chromosome regions underlying pigment content QTLs indicating possible functional relationships between candidate genes and the trait. The availability of linked, candidate gene-based markers can facilitate breeding wheat cultivars with desirable levels of carotenoids. Identifying QTLs linked to carotenoid pigmentation can contribute to understanding genes underlying carotenoid accumulation in the wheat kernels. Together these outputs can be combined to exploit the genetic variability of colour-related traits for the nutritional and commercial improvement of wheat products.

Bread Wheat Quality: Some Physical, Chemical and Rheological Characteristics of Syrian and English Bread Wheat Samples

Directory of Open Access Journals (Sweden)

Abboud Al-Saleh

2012-11-01

Full Text Available The relationships between breadmaking quality, kernel properties (physical and chemical, and dough rheology were investigated using flours from six genotypes of Syrian wheat lines, comprising both commercially grown cultivars and advanced breeding lines. Genotypes were grown in 2008/2009 season in irrigated plots in the Eastern part of Syria. Grain samples were evaluated for vitreousness, test weight, 1000-kernel weight and then milled and tested for protein content, ash, and water content. Dough rheology of the samples was studied by the determination of the mixing time, stability, weakness, resistance and the extensibility of the dough. Loaf baking quality was evaluated by the measurement of the specific weight, resilience and firmness in addition to the sensory analysis. A comparative study between the six Syrian wheat genotypes and two English flour samples was conducted. Significant differences were observed among Syrian genotypes in vitreousness (69.3%–95.0%, 1000-kernel weight (35.2–46.9 g and the test weight (82.2–88.0 kg/hL. All samples exhibited high falling numbers (346 to 417 s for the Syrian samples and 285 and 305 s for the English flours. A significant positive correlation was exhibited between the protein content of the flour and its absorption of water (r = 0.84 **, as well as with the vitreousness of the kernel (r = 0.54 *. Protein content was also correlated with dough stability (r = 0.86 **, extensibility (r = 0.8 **, and negatively correlated with dough weakness (r = −0.69 **. Bread firmness and dough weakness were positively correlated (r = 0.66 **. Sensory analysis indicated Doumah-2 was the best appreciated whilst Doumah 40765 and 46055 were the least appreciated which may suggest their suitability for biscuit preparation rather than bread making.

Bread Wheat Quality: Some Physical, Chemical and Rheological Characteristics of Syrian and English Bread Wheat Samples.

Science.gov (United States)

Al-Saleh, Abboud; Brennan, Charles S

2012-11-22

The relationships between breadmaking quality, kernel properties (physical and chemical), and dough rheology were investigated using flours from six genotypes of Syrian wheat lines, comprising both commercially grown cultivars and advanced breeding lines. Genotypes were grown in 2008/2009 season in irrigated plots in the Eastern part of Syria. Grain samples were evaluated for vitreousness, test weight, 1000-kernel weight and then milled and tested for protein content, ash, and water content. Dough rheology of the samples was studied by the determination of the mixing time, stability, weakness, resistance and the extensibility of the dough. Loaf baking quality was evaluated by the measurement of the specific weight, resilience and firmness in addition to the sensory analysis. A comparative study between the six Syrian wheat genotypes and two English flour samples was conducted. Significant differences were observed among Syrian genotypes in vitreousness (69.3%-95.0%), 1000-kernel weight (35.2-46.9 g) and the test weight (82.2-88.0 kg/hL). All samples exhibited high falling numbers (346 to 417 s for the Syrian samples and 285 and 305 s for the English flours). A significant positive correlation was exhibited between the protein content of the flour and its absorption of water (r = 0.84 **), as well as with the vitreousness of the kernel (r = 0.54 *). Protein content was also correlated with dough stability (r = 0.86 **), extensibility (r = 0.8 **), and negatively correlated with dough weakness (r = -0.69 **). Bread firmness and dough weakness were positively correlated (r = 0.66 **). Sensory analysis indicated Doumah-2 was the best appreciated whilst Doumah 40765 and 46055 were the least appreciated which may suggest their suitability for biscuit preparation rather than bread making.

Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

OpenAIRE

Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

2016-01-01

To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...

Single pass kernel k-means clustering method

Indian Academy of Sciences (India)

In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

Kernel PLS Estimation of Single-trial Event-related Potentials

Science.gov (United States)

Rosipal, Roman; Trejo, Leonard J.

2004-01-01

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

An obstructive sleep apnea detection approach using kernel density classification based on single-lead electrocardiogram.

Science.gov (United States)

Chen, Lili; Zhang, Xi; Wang, Hui

2015-05-01

Obstructive sleep apnea (OSA) is a common sleep disorder that often remains undiagnosed, leading to an increased risk of developing cardiovascular diseases. Polysomnogram (PSG) is currently used as a golden standard for screening OSA. However, because it is time consuming, expensive and causes discomfort, alternative techniques based on a reduced set of physiological signals are proposed to solve this problem. This study proposes a convenient non-parametric kernel density-based approach for detection of OSA using single-lead electrocardiogram (ECG) recordings. Selected physiologically interpretable features are extracted from segmented RR intervals, which are obtained from ECG signals. These features are fed into the kernel density classifier to detect apnea event and bandwidths for density of each class (normal or apnea) are automatically chosen through an iterative bandwidth selection algorithm. To validate the proposed approach, RR intervals are extracted from ECG signals of 35 subjects obtained from a sleep apnea database ( http://physionet.org/cgi-bin/atm/ATM ). The results indicate that the kernel density classifier, with two features for apnea event detection, achieves a mean accuracy of 82.07 %, with mean sensitivity of 83.23 % and mean specificity of 80.24 %. Compared with other existing methods, the proposed kernel density approach achieves a comparably good performance but by using fewer features without significantly losing discriminant power, which indicates that it could be widely used for home-based screening or diagnosis of OSA.

Characterization and glutenin diversity in tetraploid wheat varieties ...

African Journals Online (AJOL)

STORAGESEVER

2008-11-19

Nov 19, 2008 ... Important methods applied for the breeding of bread-quality wheat (Triticum durum L.) consist of small- scale bread-quality tests for the determination of the grain protein content, SDS-sedimentation volume, thousand weight kernel and ... marked as a x and y – type subunits, based on their electrophoretic ...

Point kernels and superposition methods for scatter dose calculations in brachytherapy

International Nuclear Information System (INIS)

Carlsson, A.K.

2000-01-01

Point kernels have been generated and applied for calculation of scatter dose distributions around monoenergetic point sources for photon energies ranging from 28 to 662 keV. Three different approaches for dose calculations have been compared: a single-kernel superposition method, a single-kernel superposition method where the point kernels are approximated as isotropic and a novel 'successive-scattering' superposition method for improved modelling of the dose from multiply scattered photons. An extended version of the EGS4 Monte Carlo code was used for generating the kernels and for benchmarking the absorbed dose distributions calculated with the superposition methods. It is shown that dose calculation by superposition at and below 100 keV can be simplified by using isotropic point kernels. Compared to the assumption of full in-scattering made by algorithms currently in clinical use, the single-kernel superposition method improves dose calculations in a half-phantom consisting of air and water. Further improvements are obtained using the successive-scattering superposition method, which reduces the overestimates of dose close to the phantom surface usually associated with kernel superposition methods at brachytherapy photon energies. It is also shown that scatter dose point kernels can be parametrized to biexponential functions, making them suitable for use with an effective implementation of the collapsed cone superposition algorithm. (author)

Study on Spectrum Estimation in Biophoton Emission Signal Analysis of Wheat Varieties

Directory of Open Access Journals (Sweden)

Yitao Liang

2014-01-01

Full Text Available The photon emission signal in visible range (380 nm–630 nm was measured from various wheat kernels by means of a low noise photomultiplier system. To study the features of the photon emission signal, the spectrum estimation method of the photon emission signal is described for the first time. The biophoton emission signal, belonging to four varieties of wheat, is analyzed in time domain and frequency domain. It shows that the intensity of the biophoton emission signal for four varieties of wheat kernels is relatively weak and has dramatic changes over time. Mean and mean square value are obviously different in four varieties; the range was, respectively, 3.7837 and 74.8819. The difference of variance is not significant. The range is 1.1764. The results of power spectrum estimation deduced that the biophoton emission signal is a low frequency signal, and its power spectrum is mostly distributed in the frequency less than 0.1 Hz. Then three parameters, which are spectral edge frequency, spectral gravity frequency, and power spectral entropy, are adopted to explain the features of the kernels’ spontaneous biophoton emission signal. It shows that the parameters of the spontaneous biophoton emission signal for different varieties of wheat are similar.

Fusarium proliferatum and fumonisin B1 co-occur with Fusarium species causing Fusarium Head Blight in durum wheat in Italy

OpenAIRE

Amato, Barbara; Pfohl, Katharina; Tonti, Stefano; Nipoti, Paola; Dastjerdi, Raana; Pisi, Annamaria; Karlovsky, Petr; Prodi, Antonio

2015-01-01

Fusarium Head Blight caused by phytopathogenic Fusarium spp. with Fusarium graminearum as main causal agent is a major disease of durum wheat (Triticum durum Desf.). Mycotoxins in wheat are dominated by trichothecenes B. Fumonisins have only occasionally been reported from wheat; their occurrence was attributed to Fusarium proliferatum and Fusarium verticillioides. We investigated kernels of durum wheat grown in Italy in 2008 - 2010 for colonization with Fusarium spp. and for the content o...

Agronomic traits and deoxynivalenol contamination of two tetraploid wheat species (Triticum turgidum spp. durum, Triticum turgidum spp. turanicum grown strictly under low input conditions

Directory of Open Access Journals (Sweden)

Giovanni Dinelli

2014-09-01

Full Text Available An evaluation of the agronomic performance of two tetraploid wheat varieties (Triticum turgidum spp. durum, Claudio; Triticum turgidum spp. turanicum, Kamut® grown strictly under low input conditions was carried out over three consecutive cropping years. The study reported grain yield values ranging from 1.8 to 2.6 t ha-1. Productivity showed to be primarily affected by environmental conditions, while no differences were observed between the two genotypes. The study of the yield components highlighted that the durum wheat variety had a higher plant density than Kamut®, but this discrepancy was offset by a greater number of kernels per spike and the kernel weight of khorasan wheat. The investigated wheat genotypes were also analysed to assess the mycotoxin (DON levels of wholegrain semolina and the efficiency of cleaning treatments to reduce contamination. Results showed that both wheat varieties had a good hygienic and sanitary quality with a DON content ranging from 0.35 to 1.31 mg kg-1, which was lower than the maximum acceptable level set by the European regulation at 1.75 mg kg-1. In addition, our research work investigated the effects of premilling cleaning procedures, such as water washing and brushing, on mycotoxin levels, which yielded interesting results in terms of decontamination efficiency. These methods were particularly efficient with Kamut® semolina (46-93% DON reduction, suggesting that mycotoxins accumulate in this variety at more superficial levels than in the durum wheat variety. On the whole, our study provided additional knowledge on the traits to be further improved to respond to low input requirements and to enhance the potential adaptability of wheat genotypes to organic agriculture. Our results emphasized the need to develop wheat varieties that can provide adequate performance without high levels of nitrogen inputs by selecting specific traits, such as kernel weight, spike length and kernel/spike. This may help

Screening for resistance to Fusarium head blight in spring wheat cultivars

OpenAIRE

Scholten, Dr. Olga E.; Steenhuis-Broers, Greet; Osman, Aart; Bremer, Esther

2006-01-01

Fusarium fungi cause Fusarium head blight in wheat. This disease is a problem that occurs both in organic and conventional farming systems. As Fusarium fungi produce mycotoxins in wheat kernels they are a threat to human and animal health. Breeding for disease resistance is the only way to prevent or reduce the occurrence of the disease. The aim of the current research project is to identify different mechanisms of resistance in cultivars and breeding lines to be used in further breeding pro...

Exogenous Cytokinins Increase Grain Yield of Winter Wheat Cultivars by Improving Stay-Green Characteristics under Heat Stress.

Directory of Open Access Journals (Sweden)

Dongqing Yang

Full Text Available Stay-green, a key trait of wheat, can not only increase the yield of wheat but also its resistance to heat stress during active photosynthesis. Cytokinins are the most potent general coordinator between the stay-green trait and senescence. The objectives of the present study were to identify and assess the effects of cytokinins on the photosynthetic organ and heat resistance in wheat. Two winter wheat cultivars, Wennong 6 (a stay-green cultivar and Jimai 20 (a control cultivar, were subjected to heat stress treatment from 1 to 5 days after anthesis (DAA. The two cultivars were sprayed daily with 10 mg L-1 of 6-benzylaminopurine (6-BA between 1 and 3 DAA under ambient and elevated temperature conditions. We found that the heat stress significantly decreased the number of kernels per spike and the grain yield (P < 0.05. Heat stress also decreased the zeatin riboside (ZR content, but increased the gibberellin (GA3, indole-3-acetic acid (IAA, and abscisic acid (ABA contents at 3 to 15 DAA. Application of 6-BA significantly (P < 0.05 increased the grain-filling rate, endosperm cell division rate, endosperm cell number, and 1,000-grain weight under heated condition. 6-BA application increased ZR and IAA contents at 3 to 28 DAA, but decreased GA3 and ABA contents. The contents of ZR, ABA, and IAA in kernels were positively and significantly correlated with the grain-filling rate (P < 0.05, whereas GA3 was counter-productive at 3 to 15 DAA. These results suggest that the decrease in grain yield under heat stress was due to a lower ZR content and a higher GA3 content compared to that at elevated temperature during the early development of the kernels, which resulted in less kernel number and lower grain-filling rate. The results also provide essential information for further utilization of the cytokinin substances in the cultivation of heat-resistant wheat.

Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

Science.gov (United States)

Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

2013-02-01

This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

Anatomy and Cytogenetic Identification of a Wheat-Psathyrostachys huashanica Keng Line with Early Maturation.

Directory of Open Access Journals (Sweden)

Liangming Wang

Full Text Available In previous studies, our research team successfully transferred the Ns genome from Psathyrostachys huashanica Keng into Triticum aestivum (common wheat cv. 7182 using embryo culture. In the present study, one of these lines, i.e., hybrid progeny 25-10-3, which matured about 10-14 days earlier than its wheat parent, was assessed using sequenced characterized amplified region (SCAR analysis, EST-SSR and EST-STS molecular markers, and genomic in situ hybridization (GISH. We found that this was a stable wheat-P. huashanica disomic addition line (2n = 44 = 22 II and the results demonstrated that it was a 6Ns disomic chromosome addition line, but it exhibited many different features compared with previously characterized lines, i.e., a longer awn, early maturation, and no twin spikelets. It was considered to be an early-maturing variety based on the early stage of inflorescence initiation in field experiments and binocular microscope observations over three consecutive years. This characteristic was distinct, especially from the single ridge stage and double ridge stage until the glume stage. In addition, it had a higher photosynthesis rate and economic values than common wheat cv. 7182, i.e., more spikelets per spike, more florets per spikelet, more kernels per spike, and a higher thousand-grain weight. These results suggest that this material may comprise a genetic pool of beneficial genes or chromosome segments, which are suitable for introgression to improve the quality of common wheat.

Characterization of Brazilian wheat cultivars for specific technological applications

Directory of Open Access Journals (Sweden)

Patrícia Matos Scheuer

2011-09-01

Full Text Available Functional and technological properties of wheat depend on its chemical composition, which together with structural and microscopic characteristics, define flour quality. The aim of the present study was to characterize four Brazilian wheat cultivars (BRS Louro, BRS Timbauva, BRS Guamirim and BRS Pardela and their respective flours in order to indicate specific technological applications. Kernels were analyzed for test weight, thousand kernel weight, hardness, moisture, and water activity. Flours were analyzed for water activity, color, centesimal composition, total dietary fiber, amylose content and identification of high molecular weight glutenins. The rheological properties of the flours were estimated by farinography, extensography, falling number, rapid visco amylography, and glutomatic and glutork equipment. Baking tests and scanning electron microscopy were also performed. The data were subjected to analysis of variance and principal component analysis. BRS Timbauva and BRS Guamirim presented results that did not allow for specific technological application. On the other hand, BRS Louro presented suitable characteristics for the elaboration of products with low dough strength such as cakes, pies and biscuits, while BRS Pardela seemed suitable for bread and pasta products.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Impact of bran components on the quality of whole wheat bread

Science.gov (United States)

Whole grains contain components, such as dietary fiber, starch, fat, antioxidant nutrients, minerals, vitamin, lignans, and phenolic compounds, which are beneficial to human health. Most of the beneficial components are found in the germ and bran as part of a wheat kernel, which are reduced in the ...

Heterosis for yield and its components in bread wheat crosses among powdery mildew resistant and susceptible genotypes

International Nuclear Information System (INIS)

Ilker, E.; Tonk, F.A.; Tosun, M.

2010-01-01

The objective of this research was to investigate heterotic effects between five powdery mildew resistant wheat lines derived from CIMMYT and three susceptible commercial wheat varieties growing in Turkey and to determine mode of gene actions of the parents for yield characters in F1 generation. All 15 F1 crosses and their parents were planted in randomized complete block design in three replications. Measurements were done for plant height, pike length, spike let and kernel number per spike, grain weight per spike and 1000-kernel weight. Promising findings of the crosses 72 x Golia, 70 x Golia, 70 x Basribey, 48 x Basribey, 48 x Atilla-12 and 72 x Atilla12 were obtained to breed new varieties or pure lines having shorter plant height and taller spike length, more number of spike let and kernel per spike, besides higher grain yield than their mid or better parents to improve powdery mildew resistant varieties. (author)

Unsupervised multiple kernel learning for heterogeneous data integration.

Science.gov (United States)

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

Difference in postprandial GLP-1 response despite similar glucose kinetics after consumption of wheat breads with different particle size in healthy men.

Science.gov (United States)

Eelderink, Coby; Noort, Martijn W J; Sozer, Nesli; Koehorst, Martijn; Holst, Jens J; Deacon, Carolyn F; Rehfeld, Jens F; Poutanen, Kaisa; Vonk, Roel J; Oudhuis, Lizette; Priebe, Marion G

2017-04-01

Underlying mechanisms of the beneficial health effects of low glycemic index starchy foods are not fully elucidated yet. We varied the wheat particle size to obtain fiber-rich breads with a high and low glycemic response and investigated the differences in postprandial glucose kinetics and metabolic response after their consumption. Ten healthy male volunteers participated in a randomized, crossover study, consuming 13 C-enriched breads with different structures; a control bread (CB) made from wheat flour combined with wheat bran, and a kernel bread (KB) where 85 % of flour was substituted with broken wheat kernels. The structure of the breads was characterized extensively. The use of stable isotopes enabled calculation of glucose kinetics: rate of appearance of exogenous glucose, endogenous glucose production, and glucose clearance rate. Additionally, postprandial plasma concentrations of glucose, insulin, glucagon, incretins, cholecystokinin, and bile acids were analyzed. Despite the attempt to obtain a bread with a low glycemic response by replacing flour by broken kernels, the glycemic response and glucose kinetics were quite similar after consumption of CB and KB. Interestingly, the glucagon-like peptide-1 (GLP-1) response was much lower after KB compared to CB (iAUC, P bread did not result in a difference in glucose response and kinetics, but in a pronounced difference in GLP-1 response. Thus, changing the processing conditions of wheat for baking bread can influence the metabolic response beyond glycemia and may therefore influence health.

NIR detects, destroys insect pests

International Nuclear Information System (INIS)

McGraw, L.C.

1998-01-01

What’s good for Georgia peanuts may also be good for Kansas wheat. An electric eye that scans all food-grade peanuts for visual defects could one day do the same for wheat kernels. For peanuts, it’s a proven method for monitoring quality. In wheat, scanning with near-infrared (NIR) energy can reveal hidden insect infestations that lower wheat quality. ARS entomologists James E. Throne and James E. Baker and ARS agricultural engineer Floyd E. Dowell are the first to combine NIR with an automated grain-handling system to rapidly detect insects hidden in single wheat kernels

Analog forecasting with dynamics-adapted kernels

Science.gov (United States)

Zhao, Zhizhen; Giannakis, Dimitrios

2016-09-01

Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

Effect of seeding rate on grain quality of winter wheat

Directory of Open Access Journals (Sweden)

Veselinka Zecevic

2014-03-01

Full Text Available Planting density is important factor which influence yield and quality of wheat (Triticum aestivum L. For this reason, in scientific investigations is constantly investigated optimization of plant number per unit area. The objective of this study was to determine the influence of seeding rate in grain quality of winter wheat cultivars. The experiment was conducted with four winter wheat genotypes ('Ana Morava', 'Vizija', 'L-3027', and 'Perla' at the Small Grains Research Centre of Kragujevac, Serbia, in 3 yr at two seeding rates (SR1 = 500 and SR2 = 650 germinating seeds m-2. The 1000-kernel weight, Zeleny sedimentation, and wet gluten content in divergent wheat genotypes were investigated depending on the seeding rate and ecological factors. Significant differences in quality components were established between investigated seeding rates. The highest values of all investigated quality traits were established in SR2 variant when applied 650 seeds m-2. Genotypes reacted differently to seeding rate. 'Perla' in average had the highest mean sedimentation value (42.2 mL and wet gluten content (33.76% in SR2 variant and this cultivar responded the best to seeding rate. Significant differences for sedimentation value and wet gluten content were found among cultivars, years, seeding rate, and for all their interactions. Also, ANOVA for 1000-kernel weight showed highly significant differences among investigated varieties, seeding rate and growing seasons, but all their interactions were not significant. In all investigated genotypes, better quality was established in SR2 variant when applied 650 seeds m-2.

Dose point kernels for beta-emitting radioisotopes

International Nuclear Information System (INIS)

Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.

1986-01-01

Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables

A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints. This pa......Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints......). Second, a heterogeneous multi-core architecture is investigated, focusing on its performance in relation to hard real-time constraints and predictable behavior. Third, the hardware implementation of HARTEX is designated to support the heterogeneous multi-core architecture. This hardware kernel has...... several advantages over a similar kernel implemented in software: higher-speed processing capability, parallel computation, and separation between the kernel itself and the applications being run. A microbenchmark has been used to compare the hardware kernel with the software kernel, and compare...

Reduced multiple empirical kernel learning machine.

Science.gov (United States)

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

An SVM model with hybrid kernels for hydrological time series

Science.gov (United States)

Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

2017-12-01

Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

Multineuron spike train analysis with R-convolution linear combination kernel.

Science.gov (United States)

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple kernel SVR based on the MRE for remote sensing water depth fusion detection

Science.gov (United States)

Wang, Jinjin; Ma, Yi; Zhang, Jingyu

2018-03-01

Remote sensing has an important means of water depth detection in coastal shallow waters and reefs. Support vector regression (SVR) is a machine learning method which is widely used in data regression. In this paper, SVR is used to remote sensing multispectral bathymetry. Aiming at the problem that the single-kernel SVR method has a large error in shallow water depth inversion, the mean relative error (MRE) of different water depth is retrieved as a decision fusion factor with single kernel SVR method, a multi kernel SVR fusion method based on the MRE is put forward. And taking the North Island of the Xisha Islands in China as an experimentation area, the comparison experiments with the single kernel SVR method and the traditional multi-bands bathymetric method are carried out. The results show that: 1) In range of 0 to 25 meters, the mean absolute error(MAE)of the multi kernel SVR fusion method is 1.5m,the MRE is 13.2%; 2) Compared to the 4 single kernel SVR method, the MRE of the fusion method reduced 1.2% (1.9%) 3.4% (1.8%), and compared to traditional multi-bands method, the MRE reduced 1.9%; 3) In 0-5m depth section, compared to the single kernel method and the multi-bands method, the MRE of fusion method reduced 13.5% to 44.4%, and the distribution of points is more concentrated relative to y=x.

Locally linear approximation for Kernel methods : the Railway Kernel

OpenAIRE

Muñoz, Alberto; González, Javier

2008-01-01

In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...

Effects of kernel weight and source-limitation on wheat grain yield ...

African Journals Online (AJOL)

DRmohammadi

2012-02-09

Feb 9, 2012 ... Many regions need wheat cultivars that are capable of high yields when the weather is beneficial but produce stable yields when conditions are adverse. These geno- types should have high yield potential in both favorable and high temperature environments (Yang et al., 2002a;. Ahmed et al., 2011a, b).

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

Charara, Ali

2017-06-06

We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar\\'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

Charara, Ali; Keyes, David E.; Ltaief, Hatem

2017-01-01

We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

Glycine betaine and salicylic acid induced modification in productivity of two different cultivars of wheat grown under water stress

Directory of Open Access Journals (Sweden)

Heshmat S. Aldesuquy

2012-05-01

Full Text Available A pot experiment was conducted to evaluate the beneficial effect of foliar application of glycine betaine (10mM, grain presoaking in salicylic acid (0.05 M and their interaction on drought tolerance of two wheat (Triticum aestivum L. cultivars (sensitive, Sakha 94 and resistant, Sakha 93. Water stress decreased wheat yield components (spike length, number of spikelets / main spike, 100 kernel weight, grain number / spike, grain yield / spike, grain yield / plant, straw yield / plant, crop yield / plant, harvest, mobilization and crop indices and the biochemical aspects of grains(grain biomass, carbohydrates, total protein, total phosphorus, ions content and amino acids in both wheat cultivars. The applied chemicals appeared to alleviate the negative effects of water stress on wheat productivity (particularly the sensitive one and the biochemical aspects of yielded grains. The effect was more pronounced with GB+SA treatment. This improvement would result from the repairing effect of the provided chemicals on growth and metabolism of wheat plants grown under water deficit condition. In response to the applied water stress and the used chemicals, the grain yield of the sensitive and resistant wheat cultivars was strongly correlated with all the estimated yield components (shoot length, spike length, plant height, main spike weight, number of spikelets per main spike, 100 kernel weight, grain number per spike, grain weight per plant, straw weight per plant, crop yield per plant, harvest, mobilization and crop indices.

An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

Directory of Open Access Journals (Sweden)

Senyue Zhang

2016-01-01

Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.

The Response of Durum Wheat to the Preceding Crop in a Mediterranean Environment

Directory of Open Access Journals (Sweden)

Laura Ercoli

2014-01-01

Full Text Available Crop sequence is an important management practice that may affect durum wheat (Triticum durum Desf. production. Field research was conducted in 2007-2008 and 2008-2009 seasons in a rain-fed cold Mediterranean environment to examine the impact of the preceding crops alfalfa (Medicago sativa L., maize (Zea mays L., sunflower (Helianthus annuus L., and bread wheat (Triticum aestivum L. on yield and N uptake of four durum wheat varieties. The response of grain yield of durum wheat to the preceding crop was high in 2007-2008 and was absent in the 2008-2009 season, because of the heavy rainfall that negatively impacted establishment, vegetative growth, and grain yield of durum wheat due to waterlogging. In the first season, durum wheat grain yield was highest following alfalfa, and was 33% lower following wheat. The yield increase of durum wheat following alfalfa was mainly due to an increased number of spikes per unit area and number of kernels per spike, while the yield decrease following wheat was mainly due to a reduction of spike number per unit area. Variety growth habit and performance did not affect the response to preceding crop and varieties ranked in the order Levante > Saragolla = Svevo > Normanno.

Effects of Cd2+ on chlorophyll content in flag and grain yield of wheats

International Nuclear Information System (INIS)

Zhu Zhiyong; Li Youjun; Liu Yingjie; Duan Youqiang; Li Qiang; Hao Yufen; Guo Jia

2011-01-01

A field experiment was conducted with wheat cultivars Luohan 6 and Yumai 18 to investigate the effects of Cd 2+ stress on chlorophyll contents in flag leaves, flag leave area, thousand kernel weight, kernel filling velocity and yield of wheat. Results indicated that, under low Cd 2+ stress (10 mg/kg), the average contents of chlorophyll a + b of Luohan 6 reduced by 1.6%, however, its average area of flag leave and yield increased by 3.8% and 1.6%, respectively. At the same time, the average content of chlorophyll a + b, area of flag leave yield of Yumai 18 reduced 8.0%, 9.6% and 5.4%. Under high Cd 2+ stress (100 mg/kg), the average contents of chlorophyll a + b, areas of flag leaves and yields of Luohan 6 and Yumai 18 reduced by 29.2% and 30.5%, 6.3% and 17.4%, 16.7% and 36.7%, respectively. The results demonstrated that Cd 2+ restrained synthesis and accumulation of chlorophyll and its components. This study even showed that within a range of Cd 2+ concentration could promote the growth of flag leaves, and it also had an equal positive effect on yield of wheat if the Cd 2+ concentration in grains were not out of limit. The growth of flag leave and yield of wheat would be limited when Cd 2+ concentration exceed that range. Overall, Yumai 18 bore more poison from Cd 2+ than Luohan 6. (authors)

Variability of Pathogenicity of Fusarium spp. Originating from Maize and Wheat Grains

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Sonja Tančić

2009-01-01

Full Text Available Differences in the pathogenicity of 93 isolates of seven species belonging to the genus Fusarium (F. graminearum, F. verticillioides, F. proliferatum, F. subglutinans, F. sporotrichioides, F. semitectum and F. equiseti, originating from maize kernels (61 and wheat grains (32, were examined based on the germination percentage of inoculated seeds. The studied species demonstrated inter- and intraspecies variability regarding the effects on maize seed germination. On the average, the greatest germination reduction was found in seeds inoculated with the spore suspensions of F. sporotrichioides and F. graminearum. A similar reduction was detected in seeds inoculated with F. proliferatum and F. subglutinans. The effect of F. subglutinans on seed germination reduction was higher compared to the two latter species, while the effects of F. semitectum and F. equiseti were smallest. The majority of isolates were of moderate pathogenicity, while the lowest number of isolates was either very pathogenic (7 or apathogenic (10. Pathogenicity of the isolates originating from wheat grains was generally lower than the pathogenicity of isolates originating from maize kernels, with the exception of F. sporotrichioides.

New spring wheat varieties ‘Panianka’ and ‘Diana’

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О. А. Демидов

2016-12-01

Full Text Available Purpose. To create new competitive spring wheat varieties. Methods. Field study, laboratory test. Results. Based on the competitive variety trial, bread spring wheat line ‘Lutescens 07-26’ has been selected due to high values of such traits as resistance to fungal diseases, grain qua­lity(protein content accounted for 15.0%, 1000 kernel weight (44.6 g productivity (3.92 t/ha and lodging resistance (9 points. In 2011, it was submitted to the State variety testing as ‘Panianka’ variety. Durum spring wheat line ‘Leukurum 08-11’ was characterized by a number of positive traits: quite a high productivity (3.05 t/ha, short stem (79 cm, resistance to fungal diseases and lodging(9 points, and in 2011 it was submitted to the State variety testing as ‘Diana’ variety. According to the results of the State variety testing in 2012–2014, spring wheat varieties ‘Panianka’ and ‘Diana’ in 2015 were put on the State Register of plant varieties suitable for dissemination in Ukraine. Conclusions. For farms in Forest-Steppe and Polissia zones of Ukraine, bread and durum spring wheat varieties were bred by V. M.Remeslo Myronivka Institute of Wheat of NAAS of Ukraine that demonstrated rather high potential of productivity and adaptability to stress conditions. This goes to prove that cultivation of domestic spring wheat varieties will promote formation of high and quality grain yields.

Single-copy genes define a conserved order between rice and wheat for understanding differences caused by duplication, deletion, and transposition of genes.

Science.gov (United States)

Singh, Nagendra K; Dalal, Vivek; Batra, Kamlesh; Singh, Binay K; Chitra, G; Singh, Archana; Ghazi, Irfan A; Yadav, Mahavir; Pandit, Awadhesh; Dixit, Rekha; Singh, Pradeep K; Singh, Harvinder; Koundal, Kirpa R; Gaikwad, Kishor; Mohapatra, Trilochan; Sharma, Tilak R

2007-01-01

The high-quality rice genome sequence is serving as a reference for comparative genome analysis in crop plants, especially cereals. However, early comparisons with bread wheat showed complex patterns of conserved synteny (gene content) and colinearity (gene order). Here, we show the presence of ancient duplicated segments in the progenitor of wheat, which were first identified in the rice genome. We also show that single-copy (SC) rice genes, those representing unique matches with wheat expressed sequence tag (EST) unigene contigs in the whole rice genome, show more than twice the proportion of genes mapping to syntenic wheat chromosome as compared to the multicopy (MC) or duplicated rice genes. While 58.7% of the 1,244 mapped SC rice genes were located in single syntenic wheat chromosome groups, the remaining 41.3% were distributed randomly to the other six non-syntenic wheat groups. This could only be explained by a background dispersal of genes in the genome through transposition or other unknown mechanism. The breakdown of rice-wheat synteny due to such transpositions was much greater near the wheat centromeres. Furthermore, the SC rice genes revealed a conserved primordial gene order that gives clues to the origin of rice and wheat chromosomes from a common ancestor through polyploidy, aneuploidy, centromeric fusions, and translocations. Apart from the bin-mapped wheat EST contigs, we also compared 56,298 predicted rice genes with 39,813 wheat EST contigs assembled from 409,765 EST sequences and identified 7,241 SC rice gene homologs of wheat. Based on the conserved colinearity of 1,063 mapped SC rice genes across the bins of individual wheat chromosomes, we predicted the wheat bin location of 6,178 unmapped SC rice gene homologs and validated the location of 213 of these in the telomeric bins of 21 wheat chromosomes with 35.4% initial success. This opens up the possibility of directed mapping of a large number of conserved SC rice gene homologs in wheat

Combined Kernel-Based BDT-SMO Classification of Hyperspectral Fused Images

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Fenghua Huang

2014-01-01

Full Text Available To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1 different radial basis kernel functions (RBFs are employed for spectral and textural features, and a new combined radial basis kernel function (CRBF is proposed by combining them in a weighted manner; (2 the binary decision tree-based multiclass SMO (BDT-SMO is used in the classification of hyperspectral fused images; (3 experiments are carried out, where the single radial basis function- (SRBF- based BDT-SMO classifier and the CRBF-based BDT-SMO classifier are used, respectively, to classify the land usages of hyperspectral fused images, and genetic algorithms (GA are used to optimize the kernel parameters of the classifiers. The results show that, compared with SRBF, CRBF-based BDT-SMO classifiers display greater classification accuracy and efficiency.

Thermal neutron scattering kernels for sapphire and silicon single crystals

International Nuclear Information System (INIS)

Cantargi, F.; Granada, J.R.; Mayer, R.E.

2015-01-01

Highlights: • Thermal cross section libraries for sapphire and silicon single crystals were generated. • Debye model was used to represent the vibrational frequency spectra to feed the NJOY code. • Sapphire total cross section was measured at Centro Atómico Bariloche. • Cross section libraries were validated with experimental data available. - Abstract: Sapphire and silicon are materials usually employed as filters in facilities with thermal neutron beams. Due to the lack of the corresponding thermal cross section libraries for those materials, necessary in calculations performed in order to optimize beams for specific applications, here we present the generation of new thermal neutron scattering kernels for those materials. The Debye model was used in both cases to represent the vibrational frequency spectra required to feed the NJOY nuclear data processing system in order to produce the corresponding libraries in ENDF and ACE format. These libraries were validated with available experimental data, some from the literature and others obtained at the pulsed neutron source at Centro Atómico Bariloche

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

Science.gov (United States)

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Genetic gains in wheat in Turkey: Winter wheat for dryland conditions

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Mesut Keser

2017-12-01

Full Text Available Wheat breeders in Turkey have been developing new varieties since the 1920s, but few studies have evaluated the rates of genetic improvement. This study determined wheat genetic gains by evaluating 22 winter/facultative varieties released for rainfed conditions between 1931 and 2006. The study was conducted at three locations in Turkey during 2008–2012, with a total of 21 test sites. The experimental design was a randomized complete block with four replicates in 2008 and 2009 and three replicates in 2010–2012. Regression analysis was conducted to determine genetic progress over time. Mean yield across all 21 locations was 3.34 t ha−1, but varied from 1.11 t ha−1 to 6.02 t ha−1 and was highly affected by moisture stress. Annual genetic gain was 0.50% compared to Ak-702, or 0.30% compared to the first modern landmark varieties. The genetic gains in drought-affected sites were 0.75% compared to Ak-702 and 0.66% compared to the landmark varieties. Modern varieties had both improved yield potential and tolerance to moisture stress. Rht genes and rye translocations were largely absent in the varieties studied. The number of spikes per unit area decreased by 10% over the study period, but grains spike−1 and 1000-kernel weight increased by 10%. There were no significant increases in harvest index, grain size, or spike fertility, and no significant decrease in quality over time. Future use of Rht genes and rye translocations in breeding programs may increase yield under rainfed conditions. Keywords: Genetic gain, Rainfed wheat production, Winter wheat, Yield

A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...

Multiple kernel boosting framework based on information measure for classification

International Nuclear Information System (INIS)

Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

2016-01-01

The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.

Sina and Sinb genes in triticale do not determine grain hardness contrary to their orthologs Pina and Pinb in wheat.

Science.gov (United States)

Gasparis, Sebastian; Orczyk, Waclaw; Nadolska-Orczyk, Anna

2013-11-26

Secaloindoline a (Sina) and secaloindoline b (Sinb) genes of hexaploid triticale (x Triticosecale Wittmack) are orthologs of puroindoline a (Pina) and puroindoline b (Pinb) in hexaploid wheat (Triticum aestivum L.). It has already been proven that RNA interference (RNAi)-based silencing of Pina and Pinb genes significantly decreased the puroindoline a and puroindoline b proteins in wheat and essentially increased grain hardness (J Exp Bot 62:4025-4036, 2011). The function of Sina and Sinb in triticale was tested by means of RNAi silencing and compared to wheat. Novel Sina and Sinb alleles in wild-type plants of cv. Wanad were identified and their expression profiles characterized. Alignment with wheat Pina-D1a and Pinb-D1a alleles showed 95% and 93.3% homology with Sina and Sinb coding sequences. Twenty transgenic lines transformed with two hpRNA silencing cassettes directed to silence Sina or Sinb were obtained by the Agrobacterium-mediated method. A significant decrease of expression of both Sin genes in segregating progeny of tested T1 lines was observed independent of the silencing cassette used. The silencing was transmitted to the T4 kernel generation. The relative transcript level was reduced by up to 99% in T3 progeny with the mean for the sublines being around 90%. Silencing of the Sin genes resulted in a substantial decrease of secaloindoline a and secaloindoline b content. The identity of SIN peptides was confirmed by mass spectrometry. The hardness index, measured by the SKCS (Single Kernel Characterization System) method, ranged from 22 to 56 in silent lines and from 37 to 49 in the control, and the mean values were insignificantly lower in the silent ones, proving increased softness. Additionally, the mean total seed protein content of silenced lines was about 6% lower compared with control lines. Correlation coefficients between hardness and transcript level were weakly positive. We documented that RNAi-based silencing of Sin genes resulted in

Wheat related allergy – A retrospective single-centre study of 156 patient

DEFF Research Database (Denmark)

Junker Christensen, Morten

2014-01-01

Background Allergy to wheat can manifest in different forms: sensitization to ingested wheat via the gastrointestinal tract can cause traditional food allergy or in combination with exercise, Wheat-Dependent Exercise-Induced Anaphylaxis (WDEIA). Sensitization to inhaled wheat flour may lead to oc...

Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

KAUST Repository

Charara, Ali; Keyes, David E.; Ltaief, Hatem

2017-01-01

Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

KAUST Repository

Charara, Ali

2017-03-06

Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt Seed Viability with Multivariate Data Analysis

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Guangjun Qiu

2018-03-01

Full Text Available The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR spectroscopy with a wavelength range of 1000–2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis.

Science.gov (United States)

Qiu, Guangjun; Lü, Enli; Lu, Huazhong; Xu, Sai; Zeng, Fanguo; Shui, Qin

2018-03-28

The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR) spectroscopy with a wavelength range of 1000-2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA) were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

Data-variant kernel analysis

CERN Document Server

Motai, Yuichi

2015-01-01

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include

Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

Science.gov (United States)

Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

2014-01-01

This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

Urease inhibitor (NBPT and efficiency of single or split application of urea in wheat crop

Directory of Open Access Journals (Sweden)

Marcelo Curitiba Espindula

2014-04-01

Full Text Available NBPT (N-(n-butyl thiophosphoric triamide, a urease inhibitor, has been reported as one of the most promising compounds to maximize urea nitrogen use in agricultural systems. The objective of this study was to evaluate the performance of irrigated wheat fertilized with urea or urea + NBPT as single or split application. The experiment was conducted from June to October 2006 in Viçosa, MG, Brazil. The experimental design followed a 2×2 factorial scheme, in which urea or urea + NBPT were combined with two modes of application: full dose at sowing (60kg ha-1 or split (20kg ha-1 at sowing + 40kg ha-1 as topdressing at tillering, in randomized blocks with ten replications. The split application of nitrogen fertilization does not improve the yield wheat under used conditions. The use of urease inhibitor improves the grain yield of wheat crop when urea is applied in topdressing at tillering, but its use does not promote difference when urea is applied in the furrow at planting.

Quasi-Dual-Packed-Kerneled Au49 (2,4-DMBT)27 Nanoclusters and the Influence of Kernel Packing on the Electrochemical Gap.

Science.gov (United States)

Liao, Lingwen; Zhuang, Shengli; Wang, Pu; Xu, Yanan; Yan, Nan; Dong, Hongwei; Wang, Chengming; Zhao, Yan; Xia, Nan; Li, Jin; Deng, Haiteng; Pei, Yong; Tian, Shi-Kai; Wu, Zhikun

2017-10-02

Although face-centered cubic (fcc), body-centered cubic (bcc), hexagonal close-packed (hcp), and other structured gold nanoclusters have been reported, it was unclear whether gold nanoclusters with mix-packed (fcc and non-fcc) kernels exist, and the correlation between kernel packing and the properties of gold nanoclusters is unknown. A Au 49 (2,4-DMBT) 27 nanocluster with a shell electron count of 22 has now been been synthesized and structurally resolved by single-crystal X-ray crystallography, which revealed that Au 49 (2,4-DMBT) 27 contains a unique Au 34 kernel consisting of one quasi-fcc-structured Au 21 and one non-fcc-structured Au 13 unit (where 2,4-DMBTH=2,4-dimethylbenzenethiol). Further experiments revealed that the kernel packing greatly influences the electrochemical gap (EG) and the fcc structure has a larger EG than the investigated non-fcc structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

Science.gov (United States)

Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

2016-02-01

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

KAUST Repository

Rosen, Paul

2013-01-01

We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

KAUST Repository

Rosen, Paul

2013-06-01

We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Resistance to Wheat Curl Mite in Arthropod-Resistant Rye-Wheat Translocation Lines

Directory of Open Access Journals (Sweden)

Lina Maria Aguirre-Rojas

2017-11-01

Full Text Available The wheat curl mite, Aceria toschiella (Keifer, and a complex of viruses vectored by A. toschiella substantially reduce wheat yields in every wheat-producing continent in the world. The development of A. toschiella-resistant wheat cultivars is a proven economically and ecologically viable method of controlling this pest. This study assessed A. toschiella resistance in wheat genotypes containing the H13, H21, H25, H26, H18 and Hdic genes for resistance to the Hessian fly, Mayetiola destructor (Say and in 94M370 wheat, which contains the Dn7 gene for resistance to the Russian wheat aphid, Diuraphis noxia (Kurdjumov. A. toschiella populations produced on plants containing Dn7 and H21 were significantly lower than those on plants of the susceptible control and no different than those on the resistant control. Dn7 resistance to D. noxia and H21 resistance to M. destructor resulted from translocations of chromatin from rye into wheat (H21—2BS/2RL, Dn7—1BL/1RS. These results provide new wheat pest management information, indicating that Dn7 and H21 constitute resources that can be used to reduce yield losses caused by A. toschiella, M. destructor, D. noxia, and wheat streak mosaic virus infection by transferring multi-pest resistance to single sources of germplasm.

Option Valuation with Volatility Components, Fat Tails, and Non-Monotonic Pricing Kernels

DEFF Research Database (Denmark)

Babaoglu, Kadir; Christoffersen, Peter; Heston, Steven L.

We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A U-shaped pricing kernel is economically most im...

Approximate kernel competitive learning.

Science.gov (United States)

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

Directory of Open Access Journals (Sweden)

Peter S. Kristensen

2018-02-01

Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

Classification With Truncated Distance Kernel.

Science.gov (United States)

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

The Relationship between Black Point and Fungi Species and Effects of Black Point on Seed Germination Properties in Bread Wheat

OpenAIRE

TOKLU, Faruk; AKGÜL, Davut Soner; BİÇİCİ, Mehmet; KARAKÖY, Tolga

2014-01-01

This study was undertaken to investigate the relationship between some fungi species and black point incidence and the effect of black point on seed weight, germination percentage, seedling emergence, seedling establishment, number of embryonic roots, and coleoptile length under field conditions in bread wheat. In this research, black-pointed and black point-free kernel samples of 5 bread wheat cultivars, namely Ceyhan-99, Doğankent-1, Yüreğir-89, Seyhan-95, and Adana-99 - commonly grown unde...

Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM

Directory of Open Access Journals (Sweden)

Chenchao Zhao

2018-01-01

Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.

Effects of Milling and Cooking Processes on the Deoxynivalenol Content in Wheat

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Masayo Kushiro

2008-11-01

Full Text Available Deoxynivalenol (DON, vomitoxin is a natural-occuring mycotoxin mainly produced by Fusarium graminearum, a food-borne fungi widely distributed in crops and it is one of the most important mycotoxins in wheat and wheat-based foods and feeds. DON affects animal and human health causing diarrhea, vomiting, gastro-intestinal inflammation, and immunomodulation. Since the rate of the occurrence of DON in wheat is high, effective procedures to remove or eliminate DON from food products is essential to minimize exposures in those who consume large amounts of wheat. Cleaning prior to milling reduced to some extent the concentration of DON in final products. Since DON is distributed throughout the kernels, with higher content in the outer skin, milling is also effective in reducing the DON levels of wheat-based foods if bran and shorts are removed before thermal cooking. DON is water-soluble and cooking with larger amounts of water lowers DON content in products such as spaghetti and noodles. During baking or heating, DON is partially degraded to DON-related chemicals, whose toxicological effects are not studied well. This paper reviews the researches on the effects of milling and cooking on the DON level and discusses the perspectives of further studies.

End-use quality of CIMMYT-derived soft kernel durum wheat germplasm. II. Dough strength and pan bread quality

Science.gov (United States)

Durum wheat (Triticum turgidum ssp. durum) is considered unsuitable for the majority of commercial bread production because its weak gluten strength combined with flour particle size and flour starch damage after milling are not commensurate with hexaploid wheat flours. Recently a new durum cultivar...

Proteome analysis of the almond kernel (Prunus dulcis).

Science.gov (United States)

Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

2016-08-01

Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Subsampling Realised Kernels

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

2011-01-01

In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our...... that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled...

An endogenous reference gene of common and durum wheat for detection of genetically modified wheat.

Science.gov (United States)

Imai, Shinjiro; Tanaka, Keiko; Nishitsuji, Yasuyuki; Kikuchi, Yosuke; Matsuoka, Yasuyuki; Arami, Shin-Ichiro; Sato, Megumi; Haraguchi, Hiroyuki; Kurimoto, Youichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2012-01-01

To develop a method for detecting GM wheat that may be marketed in the near future, we evaluated the proline-rich protein (PRP) gene as an endogenous reference gene of common wheat (Triticum aestivum L.) and durum wheat (Triticum durum L.). Real-time PCR analysis showed that only DNA of wheat was amplified and no amplification product was observed for phylogenetically related cereals, indicating that the PRP detection system is specific to wheat. The intensities of the amplification products and Ct values among all wheat samples used in this study were very similar, with no nonspecific or additional amplification, indicating that the PRP detection system has high sequence stability. The limit of detection was estimated at 5 haploid genome copies. The PRP region was demonstrated to be present as a single or double copy in the common wheat haploid genome. Furthermore, the PRP detection system showed a highly linear relationship between Ct values and the amount of plasmid DNA, indicating that an appropriate calibration curve could be constructed for quantitative detection of GM wheat. All these results indicate that the PRP gene is a suitable endogenous reference gene for PCR-based detection of GM wheat.

Breeding value of primary synthetic wheat genotypes for grain yield

Science.gov (United States)

To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes (SYN) were crossed to 20 spring bread wheat (BW) cultivars at the International Wheat and Maize Improvement Center. Modified single...

Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers

DEFF Research Database (Denmark)

Mogensen, Jesper Mølgaard; Sørensen, S.M.; Sulyok, M.

2011-01-01

Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were...... analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n = 15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins....... The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin...

Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates

International Nuclear Information System (INIS)

Hanft, J.M.; Jones, R.J.

1986-01-01

This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose

Alterations and abnormal mitosis of wheat chromosomes induced by wheat-rye monosomic addition lines.

Directory of Open Access Journals (Sweden)

Shulan Fu

Full Text Available BACKGROUND: Wheat-rye addition lines are an old topic. However, the alterations and abnormal mitotic behaviours of wheat chromosomes caused by wheat-rye monosomic addition lines are seldom reported. METHODOLOGY/PRINCIPAL FINDINGS: Octoploid triticale was derived from common wheat T. aestivum L. 'Mianyang11'×rye S. cereale L. 'Kustro' and some progeny were obtained by the controlled backcrossing of triticale with 'Mianyang11' followed by self-fertilization. Genomic in situ hybridization (GISH using rye genomic DNA and fluorescence in situ hybridization (FISH using repetitive sequences pAs1 and pSc119.2 as probes were used to analyze the mitotic chromosomes of these progeny. Strong pSc119.2 FISH signals could be observed at the telomeric regions of 3DS arms in 'Mianyang11'. However, the pSc119.2 FISH signals were disappeared from the selfed progeny of 4R monosomic addition line and the changed 3D chromosomes could be transmitted to next generation stably. In one of the selfed progeny of 7R monosomic addition line, one 2D chromosome was broken and three 4A chromosomes were observed. In the selfed progeny of 6R monosomic addition line, structural variation and abnormal mitotic behaviour of 3D chromosome were detected. Additionally, 1A and 4B chromosomes were eliminated from some of the progeny of 6R monosomic addition line. CONCLUSIONS/SIGNIFICANCE: These results indicated that single rye chromosome added to wheat might cause alterations and abnormal mitotic behaviours of wheat chromosomes and it is possible that the stress caused by single alien chromosome might be one of the factors that induced karyotype alteration of wheat.

The lignin pyrolysis composition and pyrolysis products of palm kernel shell, wheat straw, and pine sawdust

International Nuclear Information System (INIS)

Chang, Guozhang; Huang, Yanqin; Xie, Jianjun; Yang, Huikai; Liu, Huacai; Yin, Xiuli; Wu, Chuangzhi

2016-01-01

Highlights: • The primarily pyrolysis composition of PKS lignin was p-hydroxyphenyl unit. • Higher phenol yield and lower gas energy yield were obtained from PKS pyrolysis. • PKS produced more bio-oil and biochar than WS and PS from pyrolysis at 650–850 °C. • PKS-char had poorer gasification reactivity due to higher ordering carbon degree. - Abstract: The lignin monomer composition of palm kernel shell (PKS) was characterized using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), and the characteristics and distributions of products obtained from PKS pyrolysis were investigated using Py-GC/MS, GC, and a specially designed pyrolysis apparatus. The gasification reactivity of PKS biochar was also characterized using thermogravimetry (TG) and Raman spectroscopy. All the results were compared with those obtained from wheat straw (WS) and pine sawdust (PS). The results showed that PKS lignin is primarily composed of p-hydroxyphenyl structural units, while WS and PS lignins are mainly made up of guaiacyl units. Both the mass and energy yields of non-condensable gases from PKS pyrolysis were lower than those obtained from WS and PS pyrolysis at 650–850 °C, owing to the lower volatile content (75.21%) and lack of methoxy groups in PKS. Compared with WS and PS, higher bio-oil productivity was observed during PKS pyrolysis. Phenols were the main component of PKS bio-oil from pyrolysis at 500 °C, and the phenol content of PKS bio-oil (13.49%) was higher than in WS bio-oil (1.62%) and PS bio-oil (0.55%). A higher yield of biochar (on an ash-free basis) was also obtained from PKS pyrolysis. Because of its greater relative degree of ordered carbon, PKS biochar exhibited lower in situ reactivity during CO_2 or H_2O gasification than WS and PS biochars. A longer residence time and addition of steam were found to be beneficial during PKS biochar gasification.

Evidence of isolate-specificity in non-hypersensitive resistance in spring wheat (Triticum aestivum) to wheat leaf rust

NARCIS (Netherlands)

Qamar, Maqsood; Niks, R.E.

2007-01-01

Isolate-specific aspect of non-hypersensitive resistance in wheat to wheat leaf rust was studied at seedling stage in the green house. Isolate-specific response of non-hypersensitive resistance was assessed from latency period (LP) and infection frequency (IF) of two single-pustule isolates of

Optimized Kernel Entropy Components.

Science.gov (United States)

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

SCAP-82, Single Scattering, Albedo Scattering, Point-Kernel Analysis in Complex Geometry

International Nuclear Information System (INIS)

Disney, R.K.; Vogtman, S.E.

1987-01-01

1 - Description of problem or function: SCAP solves for radiation transport in complex geometries using the single or albedo scatter point kernel method. The program is designed to calculate the neutron or gamma ray radiation level at detector points located within or outside a complex radiation scatter source geometry or a user specified discrete scattering volume. Geometry is describable by zones bounded by intersecting quadratic surfaces within an arbitrary maximum number of boundary surfaces per zone. Anisotropic point sources are describable as pointwise energy dependent distributions of polar angles on a meridian; isotropic point sources may also be specified. The attenuation function for gamma rays is an exponential function on the primary source leg and the scatter leg with a build- up factor approximation to account for multiple scatter on the scat- ter leg. The neutron attenuation function is an exponential function using neutron removal cross sections on the primary source leg and scatter leg. Line or volumetric sources can be represented as a distribution of isotropic point sources, with un-collided line-of-sight attenuation and buildup calculated between each source point and the detector point. 2 - Method of solution: A point kernel method using an anisotropic or isotropic point source representation is used, line-of-sight material attenuation and inverse square spatial attenuation between the source point and scatter points and the scatter points and detector point is employed. A direct summation of individual point source results is obtained. 3 - Restrictions on the complexity of the problem: - The SCAP program is written in complete flexible dimensioning so that no restrictions are imposed on the number of energy groups or geometric zones. The geometric zone description is restricted to zones defined by boundary surfaces defined by the general quadratic equation or one of its degenerate forms. The only restriction in the program is that the total

Soft Sensing of Key State Variables in Fermentation Process Based on Relevance Vector Machine with Hybrid Kernel Function

Directory of Open Access Journals (Sweden)

Xianglin ZHU

2014-06-01

Full Text Available To resolve the online detection difficulty of some important state variables in fermentation process with traditional instruments, a soft sensing modeling method based on relevance vector machine (RVM with a hybrid kernel function is presented. Based on the characteristic analysis of two commonly-used kernel functions, that is, local Gaussian kernel function and global polynomial kernel function, a hybrid kernel function combing merits of Gaussian kernel function and polynomial kernel function is constructed. To design optimal parameters of this kernel function, the particle swarm optimization (PSO algorithm is applied. The proposed modeling method is used to predict the value of cell concentration in the Lysine fermentation process. Simulation results show that the presented hybrid-kernel RVM model has a better accuracy and performance than the single kernel RVM model.

Association Mapping and Nucleotide Sequence Variation in Five Drought Tolerance Candidate Genes in Spring Wheat

Directory of Open Access Journals (Sweden)

Erena A. Edae

2013-07-01

Full Text Available Functional markers are needed for key genes involved in drought tolerance to improve selection for crop yield under moisture stress conditions. The objectives of this study were to (i characterize five drought tolerance candidate genes, namely dehydration responsive element binding 1A (, enhanced response to abscisic acid ( and , and fructan 1-exohydrolase ( and , in wheat ( L. for nucleotide and haplotype diversity, Tajima’s D value, and linkage disequilibrium (LD and (ii associate within-gene single nucleotide polymorphisms (SNPs with phenotypic traits in a spring wheat association mapping panel ( = 126. Field trials were grown under contrasting moisture regimes in Greeley, CO, and Melkassa, Ethiopia, in 2010 and 2011. Genome-specific amplification and DNA sequence analysis of the genes identified SNPs and revealed differences in nucleotide and haplotype diversity, Tajima’s D, and patterns of LD. showed associations (false discovery rate adjusted probability value = 0.1 with normalized difference vegetation index, heading date, biomass, and spikelet number. Both and were associated with harvest index, flag leaf width, and leaf senescence. was associated with grain yield, and was associated with thousand kernel weight and test weight. If validated in relevant genetic backgrounds, the identified marker–trait associations may be applied to functional marker-assisted selection.

The effect of feeding wheat with purple pericarp on the growth of carp

Directory of Open Access Journals (Sweden)

Jan Mareš

2015-08-01

Full Text Available This study assessed and compared the influence of feeding wheat with purple pericarp (variety Konini and standard coloured wheat (red variety Bohemia on the growth characteristics of fingerling carp (Cyprinus carpio L. of the "Amurský lysec" line. The total content of anthocyanins converted to cyanidin 3-glucoside in the control Bohemia wheat was 24.95 mg.kg-1 and in the Konini purple wheat 41.70 mg.kg-1. Two experimental variants for feed were evaluated: dipped wheat grain and crushed wheat grain. The feed dose for wheat was 1.5% of the fish stock weight and for natural food (frozen Chironomid larvae was 0.2% of fish stock weight to all variants. Growth parameters (body length, body weight, Fulton's condition factor and feed conversion ratio of the fish were evaluated after one month of administration. The feed consumption and physico-chemical parameters (temperature, oxygen saturation, pH, N-NH4 +, N-NO2-, N-NO3- and Cl- of the environment were observed. During the feeding test, no major differences in food consumption among variations feeding on either wheat and on Chironomid larvae were noted. Satisfying results for mas and length gain were achieved in V2 wheat with purple pericarp (Konini variety - dipped grain, where the average total body length was 156.56 mm and the average unit mass was 60.81 g. In this variant, higher values of the parameters were achieved compared to the control group (100.6%, resp. 104.2%. A positive impact of wheat with purple pericarp on the evaluated parameter of fish condition factor was demonstrated. This trend was confirmed in all variants. No effect was demonstrated for mechanical disruption of kernels on the level of utilization of nutrients. In further experiments on growth characteristics we would like to determine antioxidant parameters in the blood and liver of fry.

Difference in postprandial GLP-1 response despite similar glucose kinetics after consumption of wheat breads with different particle size in healthy men

DEFF Research Database (Denmark)

Eelderink, Coby; Noort, Martijn W J; Sozer, Nesli

2017-01-01

PURPOSE: Underlying mechanisms of the beneficial health effects of low glycemic index starchy foods are not fully elucidated yet. We varied the wheat particle size to obtain fiber-rich breads with a high and low glycemic response and investigated the differences in postprandial glucose kinetics...... and metabolic response after their consumption. METHODS: Ten healthy male volunteers participated in a randomized, crossover study, consuming (13)C-enriched breads with different structures; a control bread (CB) made from wheat flour combined with wheat bran, and a kernel bread (KB) where 85 % of flour...... in a difference in glucose response and kinetics, but in a pronounced difference in GLP-1 response. Thus, changing the processing conditions of wheat for baking bread can influence the metabolic response beyond glycemia and may therefore influence health....

Alterations and Abnormal Mitosis of Wheat Chromosomes Induced by Wheat-Rye Monosomic Addition Lines

Science.gov (United States)

Fu, Shulan; Yang, Manyu; Fei, Yunyan; Tan, Feiquan; Ren, Zhenglong; Yan, Benju; Zhang, Huaiyu; Tang, Zongxiang

2013-01-01

Background Wheat-rye addition lines are an old topic. However, the alterations and abnormal mitotic behaviours of wheat chromosomes caused by wheat-rye monosomic addition lines are seldom reported. Methodology/Principal Findings Octoploid triticale was derived from common wheat T. aestivum L. ‘Mianyang11’×rye S. cereale L. ‘Kustro’ and some progeny were obtained by the controlled backcrossing of triticale with ‘Mianyang11’ followed by self-fertilization. Genomic in situ hybridization (GISH) using rye genomic DNA and fluorescence in situ hybridization (FISH) using repetitive sequences pAs1 and pSc119.2 as probes were used to analyze the mitotic chromosomes of these progeny. Strong pSc119.2 FISH signals could be observed at the telomeric regions of 3DS arms in ‘Mianyang11’. However, the pSc119.2 FISH signals were disappeared from the selfed progeny of 4R monosomic addition line and the changed 3D chromosomes could be transmitted to next generation stably. In one of the selfed progeny of 7R monosomic addition line, one 2D chromosome was broken and three 4A chromosomes were observed. In the selfed progeny of 6R monosomic addition line, structural variation and abnormal mitotic behaviour of 3D chromosome were detected. Additionally, 1A and 4B chromosomes were eliminated from some of the progeny of 6R monosomic addition line. Conclusions/Significance These results indicated that single rye chromosome added to wheat might cause alterations and abnormal mitotic behaviours of wheat chromosomes and it is possible that the stress caused by single alien chromosome might be one of the factors that induced karyotype alteration of wheat. PMID:23936213

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice.

Science.gov (United States)

Liu, Jie; Huang, Juan; Guo, Huan; Lan, Liu; Wang, Hongze; Xu, Yuancheng; Yang, Xiaohong; Li, Wenqiang; Tong, Hao; Xiao, Yingjie; Pan, Qingchun; Qiao, Feng; Raihan, Mohammad Sharif; Liu, Haijun; Zhang, Xuehai; Yang, Ning; Wang, Xiaqing; Deng, Min; Jin, Minliang; Zhao, Lijun; Luo, Xin; Zhou, Yang; Li, Xiang; Zhan, Wei; Liu, Nannan; Wang, Hong; Chen, Gengshen; Li, Qing; Yan, Jianbing

2017-10-01

Maize ( Zea mays ) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice ( Oryza sativa ) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1 , a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis ( Arabidopsis thaliana ) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1 ). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis. © 2017 American Society of Plant Biologists. All Rights Reserved.

A novel adaptive kernel method with kernel centers determined by a support vector regression approach

NARCIS (Netherlands)

Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

2012-01-01

The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an

Development of new iraqi wheat varieties induced by gamma rays

International Nuclear Information System (INIS)

Ibrahim, I.F.; Al-Janabi, K.K.; Al-Maaroof, E.M.; Al-Aubaidi, M.O.; Mahmoud, A.H.; Al-Janabi, A.A.

1991-01-01

The aim of the present investigation is to study agronomic traits of three wheat mutants induced by gamma rays and compared with their origin 'Saber Beg' during M 8 - M 11 generations. These mutants showed a moderate resistance to leaf rust and lodging, while the origin was susceptible. Also, these mutants surpassed their origin in seed weight of 100 spikes, weight of 1000 kernels and protein yield per unit area. Chemical and physical analyses of mutant flours indicated that it could be used for bread making successfully.2 fig.,4 tab

Assessment of chapatti quality of wheat varieties based on physicochemical, rheological and sensory traits.

Science.gov (United States)

Kundu, Manju; Khatkar, Bhupendar Singh; Gulia, Neelam

2017-07-01

Fifty wheat varieties were assessed for chapatti quality using grain characteristics, dough rheological properties and pasting characteristics. Results revealed that 88% of wheat varieties studied were medium-hard to hard based on kernel texture. Water absorption and damaged starch were found to be important parameters for chapatti quality as both parameters had significant positive effect on the pliability and puffing height of chapatti. Protein content and gluten strength parameters like SDS sedimentation volume, dough stability and gluten index were found to have a negative impact on chapatti quality. Based on chapatti quality assessment the wheat varieties were classified into four distinct clusters viz. good, acceptable, fair and poor for chapatti making. It was elucidated that 46% of the varieties studied were good to acceptable for chapatti making, while 54% resulted in fair or poor chapatti quality thereby clearly indicating the need to establish and substantiate the development of product-specific varieties. Copyright © 2016. Published by Elsevier Ltd.

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

Science.gov (United States)

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

Directory of Open Access Journals (Sweden)

Chunmei Liu

2016-01-01

Full Text Available This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

Science.gov (United States)

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

7 CFR 981.7 - Edible kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Directory of Open Access Journals (Sweden)

Hailun Wang

2017-01-01

Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

Kernel versions of some orthogonal transformations

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...

Model Selection in Kernel Ridge Regression

DEFF Research Database (Denmark)

Exterkate, Peter

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels......, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. We interpret the latter two kernels in terms of their smoothing properties, and we relate the tuning parameters associated to all these kernels to smoothness measures of the prediction function and to the signal-to-noise ratio. Based...... on these interpretations, we provide guidelines for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study confirms the practical usefulness of these rules of thumb. Finally, the flexible and smooth functional forms provided by the Gaussian and Sinc kernels makes them widely...

Penetuan Bilangan Iodin pada Hydrogenated Palm Kernel Oil (HPKO) dan Refined Bleached Deodorized Palm Kernel Oil (RBDPKO)

OpenAIRE

Sitompul, Monica Angelina

2015-01-01

Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...

7 CFR 981.8 - Inedible kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

7 CFR 981.408 - Inedible kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia.

Science.gov (United States)

El-Nahhal, Yasser; Hamdona, Nisreen

2015-01-01

This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values of binary mixture tests of (Alachlor + Bromacil), (Alachlor + Diuron), and (Bromacil + Diuron) were 12.21, 5.84, 10.22 on melon, 0.982, 925.4, 38.1 on molokhia, and 0.673, 1.34, 0.644 on wheat. Tertiary mixture tests showed EC50 values (TU/kg soil) of (Alachlor + Bromacil + Diuron) was 633.9 on melon, 3.02 on molokhia and 32.174 on wheat. Diuron was more toxic than Alachlor and Bromacil to the tested crops based on individual tests. Molokhia was the most sensitive crop to herbicides. Binary mixtures showed a synergistic effect as compared to the tertiary mixtures.

Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

KAUST Repository

Leach, Lindsey J

2014-04-11

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution \\'nullisomic-tetrasomic\\' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

KAUST Repository

Leach, Lindsey J; Belfield, Eric J; Jiang, Caifu; Brown, Carly; Mithani, Aziz; Harberd, Nicholas P

2014-01-01

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution 'nullisomic-tetrasomic' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

Model selection in kernel ridge regression

DEFF Research Database (Denmark)

Exterkate, Peter

2013-01-01

Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...

LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

Science.gov (United States)

Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

2018-05-07

Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

Viscosity kernel of molecular fluids

DEFF Research Database (Denmark)

Puscasu, Ruslan; Todd, Billy; Daivis, Peter

2010-01-01

, temperature, and chain length dependencies of the reciprocal and real-space viscosity kernels are presented. We find that the density has a major effect on the shape of the kernel. The temperature range and chain lengths considered here have by contrast less impact on the overall normalized shape. Functional...... forms that fit the wave-vector-dependent kernel data over a large density and wave-vector range have also been tested. Finally, a structural normalization of the kernels in physical space is considered. Overall, the real-space viscosity kernel has a width of roughly 3–6 atomic diameters, which means...

Heat damage and in vitro starch digestibility of puffed wheat kernels.

Science.gov (United States)

Cattaneo, Stefano; Hidalgo, Alyssa; Masotti, Fabio; Stuknytė, Milda; Brandolini, Andrea; De Noni, Ivano

2015-12-01

The effect of processing conditions on heat damage, starch digestibility, release of advanced glycation end products (AGEs) and antioxidant capacity of puffed cereals was studied. The determination of several markers arising from Maillard reaction proved pyrraline (PYR) and hydroxymethylfurfural (HMF) as the most reliable indices of heat load applied during puffing. The considerable heat load was evidenced by the high levels of both PYR (57.6-153.4 mg kg(-1) dry matter) and HMF (13-51.2 mg kg(-1) dry matter). For cost and simplicity, HMF looked like the most appropriate index in puffed cereals. Puffing influenced starch in vitro digestibility, being most of the starch (81-93%) hydrolyzed to maltotriose, maltose and glucose whereas only limited amounts of AGEs were released. The relevant antioxidant capacity revealed by digested puffed kernels can be ascribed to both the new formed Maillard reaction products and the conditions adopted during in vitro digestion. Copyright © 2015 Elsevier Ltd. All rights reserved.

Kernel learning algorithms for face recognition

CERN Document Server

Li, Jun-Bao; Pan, Jeng-Shyang

2013-01-01

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

Genetic rearrangements of six wheat-agropyron cristatum 6P addition lines revealed by molecular markers.

Directory of Open Access Journals (Sweden)

Haiming Han

Full Text Available Agropyron cristatum (L. Gaertn. (2n = 4x = 28, PPPP not only is cultivated as pasture fodder but also could provide many desirable genes for wheat improvement. It is critical to obtain common wheat-A. cristatum alien disomic addition lines to locate the desired genes on the P genome chromosomes. Comparative analysis of the homoeologous relationships between the P genome chromosome and wheat genome chromosomes is a key step in transferring different desirable genes into common wheat and producing the desired alien translocation line while compensating for the loss of wheat chromatin. In this study, six common wheat-A. cristatum disomic addition lines were produced and analyzed by phenotypic examination, genomic in situ hybridization (GISH, SSR markers from the ABD genomes and STS markers from the P genome. Comparative maps, six in total, were generated and demonstrated that all six addition lines belonged to homoeologous group 6. However, chromosome 6P had undergone obvious rearrangements in different addition lines compared with the wheat chromosome, indicating that to obtain a genetic compensating alien translocation line, one should recombine alien chromosomal regions with homoeologous wheat chromosomes. Indeed, these addition lines were classified into four types based on the comparative mapping: 6PI, 6PII, 6PIII, and 6PIV. The different types of chromosome 6P possessed different desirable genes. For example, the 6PI type, containing three addition lines, carried genes conferring high numbers of kernels per spike and resistance to powdery mildew, important traits for wheat improvement. These results may prove valuable for promoting the development of conventional chromosome engineering techniques toward molecular chromosome engineering.

Genetic Variation and Biological Control of Fusarium graminearum Isolated from Wheat in Assiut-Egypt

Directory of Open Access Journals (Sweden)

Amer F. Mahmoud

2016-04-01

Full Text Available Fusarium graminearum Schwabe causes Fusarium head blight (FHB, a devastating disease that leads to extensive yield and quality loss of wheat and other cereal crops. Twelve isolates of F. graminearum were collected from naturally infected spikes of wheat from Assiut Egypt. These isolates were compared using SRAP. The results indicated distinct genetic groups exist within F. graminearum, and demonstrated that these groups have different biological properties, especially with respect to their pathogenicity on wheat. There were biologically significant differences between the groups; with group (B isolates being more aggressive towards wheat than groups (A and (C. Furthermore, Trichoderma harzianum (Rifai and Bacillus subtilis (Ehrenberg which isolated from wheat kernels were screened for antagonistic activity against F. graminearum. They significantly reduced the growth of F. graminearum colonies in culture. In order to gain insight into biological control effect in situ, highly antagonistic isolates of T. harzianum and B. subtilis were selected, based on their in vitro effectiveness, for greenhouse test. It was revealed that T. harzianum and B. subtilis significantly reduced FHB severity. The obtained results indicated that T. harzianum and B. subtilis are very effective biocontrol agents that offer potential benefit in FHB and should be harnessed for further biocontrol applications. The accurate analysis of genetic variation and studies of population structures have significant implications for understanding the genetic traits and disease control programs in wheat. This is the first known report of the distribution and genetic variation of F. graminearum on wheat spikes in Assiut Egypt.

Partial Deconvolution with Inaccurate Blur Kernel.

Science.gov (United States)

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

Analysis of Quality-Related Parameters in Mature Kernels of Polygalacturonase Inhibiting Protein (PGIP) Transgenic Bread Wheat Infected with Fusarium graminearum.

Science.gov (United States)

Masci, Stefania; Laino, Paolo; Janni, Michela; Botticella, Ermelinda; Di Carli, Mariasole; Benvenuto, Eugenio; Danieli, Pier Paolo; Lilley, Kathryn S; Lafiandra, Domenico; D'Ovidio, Renato

2015-04-22

Fusarium head blight, caused by the fungus Fusarium graminearum, has a detrimental effect on both productivity and qualitative properties of wheat. To evaluate its impact on wheat flour, we compared its effect on quality-related parameters between a transgenic bread wheat line expressing a bean polygalacturonase inhibiting protein (PGIP) and its control line. We have compared metabolic proteins, the amounts of gluten proteins and their relative ratios, starch content, yield, extent of pathogen contamination, and deoxynivalenol (DON) accumulation. These comparisons showed that Fusarium significantly decreases the amount of starch in infected control plants, but not in infected PGIP plants. The flour of PGIP plants contained also a lower amount of pathogen biomass and DON accumulation. Conversely, both gluten and metabolic proteins were not significantly influenced either by the transgene or by fungal infection. These results indicate that the transgenic PGIP expression reduces the level of infection, without changing significantly the wheat seed proteome and other quality-related parameters.

Kernel methods for deep learning

OpenAIRE

Cho, Youngmin

2012-01-01

We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

Efeitos da precipitação pluvial, da umidade relativa do ar e de excesso e déficit hídrico do solo no peso do hectolitro, no peso de mil grãos e no rendimento de grãos de trigo Effects of rainfall, relative humidity and water excess and deficit on test weight, thousand kernel weight, and grain yield of wheat

Directory of Open Access Journals (Sweden)

Eliana Maria Guarienti

2005-09-01

Full Text Available Cerca de 90% da produção de trigo no Brasil está localizada nos estados do Paraná, do Rio Grande do Sul e de Santa Catarina. Nesses estados, a variabilidade climática é muito expressiva, tornando a produção tritícola uma atividade de risco e fazendo com que o decréscimo da produção e da produtividade de trigo seja objeto de questionamento de grande número de investigadores. Este trabalho teve por objetivo verificar a influência da precipitação pluvial, da umidade relativa do ar e de excesso e déficit hídrico do solo no peso do hectolitro, peso de mil grãos e rendimento de grãos. Foram usados dados de experimentos com a cultivar de trigo Embrapa 16, conduzidos durante os anos de 1990 a 1998, em sete locais do Rio Grande do Sul e em quatro locais de Santa Catarina. A análise estatística realizada foi correlação múltipla. Verificou-se que: a a precipitação pluvial e o excesso hídrico do solo afetaram negativamente o peso do hectolitro, peso de mil grãos e rendimento de grãos, e a umidade relativa do ar influenciou tanto positiva quanto negativamente essas variáveis; b o déficit hídrico do solo afetou positivamente o peso do hectolitro, peso de mil grãos e rendimento de grãos após a maturação fisiológica, isto é, nos dez primeiros dias anteriores à colheita, e negativamente nos demais períodos.About 90% of the wheat production in Brazil is located in Paraná, Rio Grande do Sul and Santa Catarina states. In these states there is a considerable climatic variability and consequently wheat production becomes a risky activity. Therefore, the decrease of wheat production and grain yield has been analyzed by a great number of investigators. This work aimed to verify the influence of rainfall, relative humidity, and water excess and deficit on test weight, thousand kernel weight, and grain yield of wheat. Data of Embrapa 16 wheat cultivar, obtained during the 1990-98 period, in seven Rio Grande do Sul state

Optimizing memory-bound SYMV kernel on GPU hardware accelerators

KAUST Repository

Abdelfattah, Ahmad

2013-01-01

Hardware accelerators are becoming ubiquitous high performance scientific computing. They are capable of delivering an unprecedented level of concurrent execution contexts. High-level programming language extensions (e.g., CUDA), profiling tools (e.g., PAPI-CUDA, CUDA Profiler) are paramount to improve productivity, while effectively exploiting the underlying hardware. We present an optimized numerical kernel for computing the symmetric matrix-vector product on nVidia Fermi GPUs. Due to its inherent memory-bound nature, this kernel is very critical in the tridiagonalization of a symmetric dense matrix, which is a preprocessing step to calculate the eigenpairs. Using a novel design to address the irregular memory accesses by hiding latency and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double precision arithmetics, respectively. © 2013 Springer-Verlag.

7 CFR 981.9 - Kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

Veto-Consensus Multiple Kernel Learning

NARCIS (Netherlands)

Zhou, Y.; Hu, N.; Spanos, C.J.

2016-01-01

We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The

7 CFR 51.2295 - Half kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

An Approximate Approach to Automatic Kernel Selection.

Science.gov (United States)

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Iterative software kernels

Energy Technology Data Exchange (ETDEWEB)

Duff, I.

1994-12-31

This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.

Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

Science.gov (United States)

Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

2018-05-01

With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

A kernel version of spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

. Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

Optimizing memory-bound SYMV kernel on GPU hardware accelerators

KAUST Repository

Abdelfattah, Ahmad; Dongarra, Jack; Keyes, David E.; Ltaief, Hatem

2013-01-01

and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double

Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

Science.gov (United States)

Karmeshu; Gupta, Varun; Kadambari, K V

2011-06-01

A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

7 CFR 51.1441 - Half-kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

Composite population kernels in ytterbium-buffer collisions studied by means of laser-saturated absorption

International Nuclear Information System (INIS)

Zhu, X.

1986-01-01

We present a systematic study of composite population kernels for 174 Yb collisions with He, Ar, and Xe buffer gases, using laser-saturation spectroscopy. 174 Yb is chosen as the active species because of the simple structure of its 1 S 0 - 3 P 1 resonance transition (lambda = 556 nm). Elastic collisions are modeled by means of a composite collision kernel, an expression of which is explicitly derived based on arguments of a hard-sphere potential and two-category collisions. The corresponding coupled population-rate equations are solved by iteration to obtain an expression for the saturated-absorption line shape. This expression is fit to the data to obtain information about the composite kernel, along with reasonable values for other parameters. The results confirm that a composite kernel is more general and realistic than a single-component kernel, and the generality in principle and the practical necessity of the former are discussed

Yellow berry, protein and agronomic characteristics in bread wheat under different conditions of nitrogen and irrigation in northwest mexico

International Nuclear Information System (INIS)

Felix, F.R.; Wong, B.R.; Chavez, P.I.T.; Alviles, A.; Salazar, S.M.; Martinez, M.E.R

2014-01-01

The aim of this research was to determine the effect of the amount of nitrogen fertilizer and number of irrigations on the YB disorder of wheat cultivar Tarachi, as well as its relationship with protein content, and the agronomic characteristics. The experiment was conducted in northwestern Mexico, during the fall-winter season, 2009-2010. Three levels of nitrogen (75, 150 or 250 kg ha-1) and three levels of irrigation (3, 4 or 5 irrigations) were studied. Increasing the nitrogen rate decreased the YB content, the thousand kernel weight and hectoliter weight; and increased the protein content and the number of grains per spike. The number of irrigations did not affect the number of grains per spike. However, increasing the number of irrigations increased the YB content, the thousand kernel weight and hectoliter weight; on the other hand, the protein content decreased. A negative correlation between protein content and percentage of YB was presented. It was concluded that the presence of the disorder YB in bread wheat, Tarachi, is due to a low nitrogen rate in the soil and an increase in number of irrigations. (author)

Method for calculating anisotropic neutron transport using scattering kernel without polynomial expansion

International Nuclear Information System (INIS)

Takahashi, Akito; Yamamoto, Junji; Ebisuya, Mituo; Sumita, Kenji

1979-01-01

A new method for calculating the anisotropic neutron transport is proposed for the angular spectral analysis of D-T fusion reactor neutronics. The method is based on the transport equation with new type of anisotropic scattering kernels formulated by a single function I sub(i) (μ', μ) instead of polynomial expansion, for instance, Legendre polynomials. In the calculation of angular flux spectra by using scattering kernels with the Legendre polynomial expansion, we often observe the oscillation with negative flux. But in principle this oscillation disappears by this new method. In this work, we discussed anisotropic scattering kernels of the elastic scattering and the inelastic scatterings which excite discrete energy levels. The other scatterings were included in isotropic scattering kernels. An approximation method, with use of the first collision source written by the I sub(i) (μ', μ) function, was introduced to attenuate the ''oscillations'' when we are obliged to use the scattering kernels with the Legendre polynomial expansion. Calculated results with this approximation showed remarkable improvement for the analysis of the angular flux spectra in a slab system of lithium metal with the D-T neutron source. (author)

Genetic variability and fumonisin production by Fusarium proliferatum isolated from durum wheat grains in Argentina.

Science.gov (United States)

Palacios, S A; Susca, A; Haidukowski, M; Stea, G; Cendoya, E; Ramírez, M L; Chulze, S N; Farnochi, M C; Moretti, A; Torres, A M

2015-05-18

Fusarium proliferatum is a member of the Fusarium fujikuroi species complex (FFSC) involved in the maize ear rot together with Fusarium verticillioides, which is a very closely related species. Recently, different studies have detected natural fumonisin contamination in wheat kernels and most of them have shown that the main species isolated was F. proliferatum. Fusarium strains obtained from freshly harvested durum wheat samples (2008 to 2011 harvest seasons) from Argentina were characterized through a phylogenetic analysis based on translation elongation factor-1 alpha (EF-1α) and calmodulin (CaM) genes, determination of mating type alleles, and evaluation of fumonisin production capability. The strains were identified as F. proliferatum (72%), F. verticillioides (24%) and other Fusarium species. The ratio of mating type alleles (MAT-1 and MAT-2) obtained for both main populations suggests possible occurrence of sexual reproduction in the wheat fields, although this seems more frequent in F. proliferatum. Phylogenetic analysis revealed greater nucleotide variability in F. proliferatum strains than in F. verticillioides, however this was not related to origin, host or harvest year. The fumonisin-producing ability was detected in 92% of the strains isolated from durum wheat grains. These results indicate that F. proliferatum and F. verticillioides, among the fumonisin producing species, frequently contaminate durum wheat grains in Argentina, presenting a high risk for human and animal health. Copyright © 2015 Elsevier B.V. All rights reserved.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

Science.gov (United States)

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

Differential representation of albumins and globulins during grain development in durum wheat and its possible functional consequences.

Science.gov (United States)

Arena, Simona; D'Ambrosio, Chiara; Vitale, Monica; Mazzeo, Fiorella; Mamone, Gianfranco; Di Stasio, Luigia; Maccaferri, Marco; Curci, Pasquale Luca; Sonnante, Gabriella; Zambrano, Nicola; Scaloni, Andrea

2017-06-06

-DIGE-based comparative analysis of the albumin/globulin fraction from durum wheat caryopses at six developmental stages was performed to describe the dynamic subproteomic changes associated with grain development. Quantitative variations of 217 differentially proteins demonstrated that highly affected are the functional categories of carbon metabolism, energy, protein destination/storage, disease/defense and cell growth/division, which displayed a general over-representation, consistently with concomitant occurrence of grain size increase and starch/protein reserve accumulation. Bioinformatics revealed a complex protein network centered mainly at enzymes involved in carbon and protein metabolism. Differentially represented proteins and corresponding functional categories highly resembled those previously identified as variable in developing bread wheat grain. This suggests that the main differences in kernel hardness between durum and bread wheat probably do not depend on proteomic changes in corresponding albumins/globulins, but on other specific factors affecting the interaction between the starch granules and the endosperm protein matrix in the kernel. Copyright © 2017 Elsevier B.V. All rights reserved.

Local Observed-Score Kernel Equating

Science.gov (United States)

Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

2014-01-01

Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

Characterisation and final disposal behaviour of theoria-based fuel kernels in aqueous phases

International Nuclear Information System (INIS)

Titov, M.

2005-08-01

Two high-temperature reactors (AVR and THTR) operated in Germany have produced about 1 million spent fuel elements. The nuclear fuel in these reactors consists mainly of thorium-uranium mixed oxides, but also pure uranium dioxide and carbide fuels were tested. One of the possible solutions of utilising spent HTR fuel is the direct disposal in deep geological formations. Under such circumstances, the properties of fuel kernels, and especially their leaching behaviour in aqueous phases, have to be investigated for safety assessments of the final repository. In the present work, unirradiated ThO 2 , (Th 0.906 ,U 0.094 )O 2 , (Th 0.834 ,U 0.166 )O 2 and UO 2 fuel kernels were investigated. The composition, crystal structure and surface of the kernels were investigated by traditional methods. Furthermore, a new method was developed for testing the mechanical properties of ceramic kernels. The method was successfully used for the examination of mechanical properties of oxide kernels and for monitoring their evolution during contact with aqueous phases. The leaching behaviour of thoria-based oxide kernels and powders was investigated in repository-relevant salt solutions, as well as in artificial leachates. The influence of different experimental parameters on the kernel leaching stability was investigated. It was shown that thoria-based fuel kernels possess high chemical stability and are indifferent to presence of oxidative and radiolytic species in solution. The dissolution rate of thoria-based materials is typically several orders of magnitude lower than of conventional UO 2 fuel kernels. The life time of a single intact (Th,U)O 2 kernel under aggressive conditions of salt repository was estimated as about hundred thousand years. The importance of grain boundary quality on the leaching stability was demonstrated. Numerical Monte Carlo simulations were performed in order to explain the results of leaching experiments. (orig.)

Credit scoring analysis using kernel discriminant

Science.gov (United States)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Kernel parameter dependence in spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L..

Directory of Open Access Journals (Sweden)

Jie Guo

Full Text Available Common wheat is one of the most important crops in China, which is the largest producer in the world. A set of 230 cultivars was used to identify yield-related loci by association mapping. This set was tested for seven yield-related traits, viz. plant height (PH, spike length (SL, spikelet number per spike (SNPS, kernel number per spike (KNPS, thousand-kernel weight (TKW, kernel weight per spike (KWPS, and sterile spikelet number (SSN per plant in four environments. A total of 106 simple sequence repeat (SSR markers distributed on all 21 chromosomes were used to screen the set. Twenty-one and 19 of them were associated with KNPS and TKW, respectively. Association mapping detected 73 significant associations across 50 SSRs, and the phenotypic variation explained (R2 by the associations ranged from 1.54 to 23.93%. The associated loci were distributed on all chromosomes except 4A, 7A, and 7D. Significant and potentially new alleles were present on 8 chromosomes, namely 1A, 1D, 2A, 2D, 3D, 4B, 5B, and 6B. Further analysis showed that genetic effects of associated loci were greatly influenced by association panels, and the R2 of crucial loci were lower in modern cultivars than in the mini core collection, probably caused by strong selection in wheat breeding. In order to confirm the results of association analysis, yield-related favorable alleles Xgwm135-1A138, Xgwm337-1D186, Xgwm102-2D144, and Xgwm132-6B128 were evaluated in a double haploid (DH population derived from Hanxuan10 xLumai14.These favorable alleles that were validated in various populations might be valuable in breeding for high-yield.

Evaluating the Production of Doubled Haploid Wheat Lines Using Various Methods of Wheat and Maize Crossing to Develop Heat-Tolerant Wheat Varieties

Directory of Open Access Journals (Sweden)

Tayebeh BAKHSHI

2017-02-01

Full Text Available Abstract. In this study, chromosome elimination method was used to develop doubled haploid wheat lines via crosses with maize. The plant materials used included 11, F1 wheat genotypes and maize genotype BC572. In these crosses, the maize plant was used as the male parent.Three methods of haploid production in wheat comprising conventional (A, detached-tiller culture (B and intermediate (C techniques were used and compared. The traits such as the number of seeds set, the number of embryos obtained and the number of haploid seedlings produced were studied. Comparisons showed that among various methods of storing wheat spikes, method (C was better than other techniques in terms of the percentage of seed production, embryo formation and haploid seedling production. Also, in all three methods, the percentage of seed production, the percentage of embryo formation and the percentage of haploid seedling production were respectively equal to 76.84, 25.22 and 51.89. Among the wheat genotypes in all three methods, genotype DH-133 with 87.28 percent seed set and genotype DH-132 with 32.71 percent embryo formation and 65.08 percent haploid seedling production were the best genotypes. A total of 92 doubled haploid lines were produced. In the field evaluations of 86 doubled haploid lines, traits such as growing season, plant height, lodging, kernel yield and 1000 kernel weight were examined. Finally, 3 lines were selected for adaptation and stability testing under heat stress conditions.Keywords: Wheat, Doubled haploid, Chromosome elimination, Detached-tiller culture Özet. Bu çalışmada, mısır ile çaprazlarla çift katlı haploid buğday hatlarının geliştirilmesi için kromozom eliminasyon yöntemi kullanılmıştır. Kullanılan bitki materyalleri 11, F1 buğday genotipleri ve BC572 mısır genotipini içermektedir. Bu çaprazlarda, mısır bitkisi erkek ebeveyn olarak kullanılmıştır. Geleneksel (A, ayrık-yeke kültürü (B ve ara (C

Effect of fungal colonization of wheat grains with Fusarium spp. on food choice, weight gain and mortality of meal beetle larvae (Tenebrio molitor.

Directory of Open Access Journals (Sweden)

Zhiqing Guo

Full Text Available Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin

Effect of Fungal Colonization of Wheat Grains with Fusarium spp. on Food Choice, Weight Gain and Mortality of Meal Beetle Larvae (Tenebrio molitor)

Science.gov (United States)

Guo, Zhiqing; Döll, Katharina; Dastjerdi, Raana; Karlovsky, Petr; Dehne, Heinz-Wilhelm; Altincicek, Boran

2014-01-01

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F

Effect of fungal colonization of wheat grains with Fusarium spp. on food choice, weight gain and mortality of meal beetle larvae (Tenebrio molitor).

Science.gov (United States)

Guo, Zhiqing; Döll, Katharina; Dastjerdi, Raana; Karlovsky, Petr; Dehne, Heinz-Wilhelm; Altincicek, Boran

2014-01-01

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F

Multiple Kernel Learning with Data Augmentation

Science.gov (United States)

2016-11-22

JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au...University, Australia Editors: Robert J. Durrant and Kee-Eung Kim Abstract The motivations of multiple kernel learning (MKL) approach are to increase... kernel expres- siveness capacity and to avoid the expensive grid search over a wide spectrum of kernels . A large amount of work has been proposed to

OS X and iOS Kernel Programming

CERN Document Server

Halvorsen, Ole Henry

2011-01-01

OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i

Model selection for Gaussian kernel PCA denoising

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Hansen, Lars Kai

2012-01-01

We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

Ultrafast convolution/superposition using tabulated and exponential kernels on GPU

Energy Technology Data Exchange (ETDEWEB)

Chen Quan; Chen Mingli; Lu Weiguo [TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 (United States)

2011-03-15

Purpose: Collapsed-cone convolution/superposition (CCCS) dose calculation is the workhorse for IMRT dose calculation. The authors present a novel algorithm for computing CCCS dose on the modern graphic processing unit (GPU). Methods: The GPU algorithm includes a novel TERMA calculation that has no write-conflicts and has linear computation complexity. The CCCS algorithm uses either tabulated or exponential cumulative-cumulative kernels (CCKs) as reported in literature. The authors have demonstrated that the use of exponential kernels can reduce the computation complexity by order of a dimension and achieve excellent accuracy. Special attentions are paid to the unique architecture of GPU, especially the memory accessing pattern, which increases performance by more than tenfold. Results: As a result, the tabulated kernel implementation in GPU is two to three times faster than other GPU implementations reported in literature. The implementation of CCCS showed significant speedup on GPU over single core CPU. On tabulated CCK, speedups as high as 70 are observed; on exponential CCK, speedups as high as 90 are observed. Conclusions: Overall, the GPU algorithm using exponential CCK is 1000-3000 times faster over a highly optimized single-threaded CPU implementation using tabulated CCK, while the dose differences are within 0.5% and 0.5 mm. This ultrafast CCCS algorithm will allow many time-sensitive applications to use accurate dose calculation.

Natural Variation in Grain Composition of Wheat and Related Cereals

OpenAIRE

Shewry, Peter R; Hawkesford, Malcolm J; Piironen, Vieno; Lampi, Anna-Maija; Gebruers, Kurt; Boros, Danuta; Andersson, Annica AM; Åman, Per; Rakszegi, Mariann; Bedo, Zoltan; Ward, Jane L

2013-01-01

The wheat grain comprises three groups of major components, starch, protein, and cell wall polysaccharides (dietary fiber), and a range of minor components that may confer benefits to human health. Detailed analyses of dietary fiber and other bioactive components were carried out under the EU FP6 HEALTHGRAIN program on 150 bread wheat lines grown on a single site, 50 lines of other wheat species and other cereals grown on the same site, and 23−26 bread wheat lines grown in six environments. P...

Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

Directory of Open Access Journals (Sweden)

Silvano O Assanga

Full Text Available Stable quantitative trait loci (QTL are important for deployment in marker assisted selection in wheat (Triticum aestivum L. and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading and yield related traits (test weight, thousand kernel weight, harvest index. The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1

Abiotic conditions leading to FUM gene expression and fumonisin accumulation by Fusarium proliferatum strains grown on a wheat-based substrate.

Science.gov (United States)

Cendoya, Eugenia; Pinson-Gadais, Laetitia; Farnochi, María C; Ramirez, María L; Chéreau, Sylvain; Marcheguay, Giselè; Ducos, Christine; Barreau, Christian; Richard-Forget, Florence

2017-07-17

Fusarium proliferatum produces fumonisins B not only on maize but also on diverse crops including wheat. Using a wheat-based medium, the effects of abiotic factors, temperature and water activity (a W ), on growth, fumonisin biosynthesis, and expression of FUM genes were compared for three F. proliferatum strains isolated from durum wheat in Argentina. Although all isolates showed similar profiles of growth, the fumonisin production profiles were slightly different. Regarding FUM gene transcriptional control, both FUM8 and FUM19 expression showed similar behavior in all tested conditions. For both genes, expression at 25°C correlated with fumonisin production, regardless of the a w conditions. However, at 15°C, these two genes were as highly expressed as at 25°C although the amounts of toxin were very weak, suggesting that the kinetics of fumonisin production was slowed at 15°C. This study provides useful baseline data on conditions representing a low or a high risk for contamination of wheat kernels with fumonisins. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimizing Multiple Kernel Learning for the Classification of UAV Data

Directory of Open Access Journals (Sweden)

Caroline M. Gevaert

2016-12-01

Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

Paramecium: An Extensible Object-Based Kernel

NARCIS (Netherlands)

van Doorn, L.; Homburg, P.; Tanenbaum, A.S.

1995-01-01

In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection

Theory of reproducing kernels and applications

CERN Document Server

Saitoh, Saburou

2016-01-01

This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...

Detection of Fusarium in single wheat kernels using spectral Imaging

NARCIS (Netherlands)

Polder, G.; Heijden, van der G.W.A.M.; Waalwijk, C.; Young, I.T.

2005-01-01

Fusarium head blight (FHB) is a harmful fungal disease that occurs in small grains. Non-destructive detection of this disease is traditionally done using spectroscopy or image processing. In this paper the combination of these two in the form of spectral imaging is evaluated. Transmission spectral

Kernels for structured data

CERN Document Server

Gärtner, Thomas

2009-01-01

This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by

QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management.

Directory of Open Access Journals (Sweden)

Jun Zou

Full Text Available Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1 markers on quantitative trait loci (QTL detection in a recombinant inbred lines (RILs population derived from a cross between two spring wheat (Triticum aestivum L. cultivars, 'Attila' and 'CDC Go', and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering, flowering time, maturity, plant height, test weight (grain volume weight, 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers, we identified a total of 14 QTLs associated with flowering time (1, maturity (2, plant height (1, grain yield (1, test weight (2, kernel weight (4, tillering (1 and grain protein content (2. Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61-66 cM, 4B (80-82 cM and 5A (296-297 cM harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r2 ≤ 0.75 with SNP markers that mapped within the QTL confidence interval. Six of the 14

SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement

International Nuclear Information System (INIS)

Chamberlain, S; French, S; Nazareth, D

2016-01-01

Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 10"6 to 3 × 10"7); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10"6 was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10"6 have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.

7 CFR 981.401 - Adjusted kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Adjusted kernel weight. 981.401 Section 981.401... Administrative Rules and Regulations § 981.401 Adjusted kernel weight. (a) Definition. Adjusted kernel weight... kernels in excess of five percent; less shells, if applicable; less processing loss of one percent for...

Effects of location and year on grain yield and its components in wheat genotypes developed from seed irradiation treatment

International Nuclear Information System (INIS)

Amer, I.M.; El-Rassas, H.N.; Abdel-Aleem, M.M.

1994-01-01

Eight mutant lines derived from gamma ray treatments and their parental cultivar sokha 69 of bread wheat were evaluated for grain yield per feddan, straw yield per feddan, harvest index, spike length, spike yield and weight of 1000-kernels at two locations (El-Fayoum and Inshas) in two seasons, 1991/92 and 1992/93. Significant effects of location on yield and yield components were found and the year significantly affects all the studied traits except grain yield per feddan. A significant location genotype interaction was detected for spike length, 1000-kernel weight and straw yield per feddan. In addition, year genotype interaction was significant in weight of 1000-kernels, straw yield per feddan and harvest index. The statistical analysis showed a significant difference among genotypes over all environments for spike length, 1000-kernel weight, straw yield per feddan and harvest index. However, these did not reflect significant effect on grain yield per feddan over all environments because it has a highly compensation ability. Meanwhile, mutant L 1 2 -1 exhibited significantly higher straw yield than sokha 69, when averaged over two seasons at El-Fayoum. Mutant L 1 9 -1 gave higher weight of 1000-kernels, spike length and harvest index than the other genotypes at low-yielding location (Inshas). It seems to be stable over a wide range of environments. 3 tabs

Testing Infrastructure for Operating System Kernel Development

DEFF Research Database (Denmark)

Walter, Maxwell; Karlsson, Sven

2014-01-01

Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....

Wheat (Triticum aestivum L.) transformation using immature embryos.

Science.gov (United States)

Ishida, Yuji; Tsunashima, Masako; Hiei, Yukoh; Komari, Toshihiko

2015-01-01

Wheat may now be transformed very efficiently by Agrobacterium tumefaciens. Under the protocol hereby described, immature embryos of healthy plants of wheat cultivar Fielder grown in a well-conditioned greenhouse were pretreated with centrifuging and cocultivated with A. tumefaciens. Transgenic wheat plants were obtained routinely from between 40 and 90 % of the immature embryos, thus infected in our tests. All regenerants were normal in morphology and fully fertile. About half of the transformed plants carried single copy of the transgene, which are inherited by the progeny in a Mendelian fashion.

Sensory, yield and quality differences between organically and conventionally grown winter wheat.

Science.gov (United States)

Arncken, Christine M; Mäder, Paul; Mayer, Jochen; Weibel, Franco P

2012-11-01

Consumers expect organic produce to have higher environmental, health and sensory related qualities than conventional produce. In order to test sensory differences between bio-dynamically, bio-organically and conventionally grown winter wheat (Triticum aestivum L., cv. Runal), we performed double-blinded triangle tests with two panels on dry wholemeal flour from the harvest years 2006, 2007 and 2009 and from two field replicates of the 'DOK' long-term farming system comparison field trial near Basel, Switzerland. Yield and quality parameters were also assessed. Significant farming system effects were found for yield (up to 42% reduction in the organic system), thousand kernel weight, hectolitre weight and crude protein content across the three years. In the triangle tests one out of 12 pair-wise farming system comparisons (PFSCs) on wholemeal flour made from the different wheat samples showed significant sensory differentiation (between bio-dynamically and conventionally grown wheat). When all data from the three harvest years and two panels were aggregated, a statistically significant effect (P = 0.045) of PFSCs on the number of correct answers became evident. Although testing of dry wholemeal flour was very challenging for panellists, we were able to show that sensory differences between farming systems can occur. Copyright © 2012 Society of Chemical Industry.

Pareto-path multitask multiple kernel learning.

Science.gov (United States)

Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

2015-01-01

A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

7 CFR 51.1403 - Kernel color classification.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

Effects of nitrogen and irrigation on gluten protein composition and their relationship to yellow berry disorder in wheat (triticum aestivum)

International Nuclear Information System (INIS)

Wong, B.R.; Felix, F.R.; Chavez, T

2014-01-01

In Mexico and the rest of the world, the presence of yellow berry (YB) in wheat grains (Triticum aestivum) has been related with poor quality, this defect is associated with low protein content in the grains. However, the quality of the wheat depends not only on the protein content, but also on the composition of the gluten proteins. The effect of the various agronomic factors on the composition of wheat gluten has been a subject of study worldwide. However, in Mexico, wheat quality still remains an issue, as there is a lack of knowledge regarding the optimal agronomic conditions to produce wheat with good-quality gluten. For this reason, the effects of nitrogen (N) rates and irrigations on the amount of gliadin subclasses, glutenin subunits (two main groups) and grain protein content as well as the relation of these proteins to the YB content in wheat grains were investigated. The experiment was conducted on arable farmland in the Valley of Empalme, Sonora, Mexico (27 degree 58' N, 110 degree 49' W; 10 m altitude), during the fall-winter period of 2009-2010. Tarachi, the hard wheat cultivar studied, was selected for its relative susceptibility to the presence of elevated YB content in mature wheat kernels. Three levels of N (75, 150 or 250 kg ha-1) and three levels of irrigation (1, 2 or 3 auxiliary irrigations) were studied. Using a N rate of 150 kg ha-1 with 3 auxiliary irrigations, wheat with good-quality gluten was obtained. The results suggest that the YB disorder is primarily related to the amount of protein in the wheat grain. (author)

Mutation induction of protein variability in wheat and rice

International Nuclear Information System (INIS)

Narahari, P.; Bhatia, C.R.; Gopalakrishna, T.; Mitra, R.K.

1976-01-01

No high protein mutants of wheat have been obtained without depression of grain yield after screening a few thousand lines. The best wheat mutant identified in our programme so far is an erectoid mutant that has consistently shown about 1.5-2% points increase in protein over Kalyan sona for the last four years. Grain yield of the mutant is about 89% of the parent. No significant variation in amino composition is noted in the mutant. Preliminary analysis of over 200 macro mutants in three varieties of rice has resulted in identification of mutants with high protein content (10-22%) compared with 8.0 to 8.5% in the high yielding controls. The amino-acid composition of some of the mutant kernels do not show great deviation from the controls. All the high protein percentage mutants are lower in grain yield. Despite very high F 1 sterility in a cross involving the high protein genotype GMPR-51 and high yielding IR-8, several fertile F 2 plants resembling IR-8 have been isolated which on preliminary analysis have shown still higher protein content than GMPR-51, suggesting a transgressive mode of inheritance of this trait. (author)

The definition of kernel Oz

OpenAIRE

Smolka, Gert

1994-01-01

Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...

Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

International Nuclear Information System (INIS)

Barnes, Charles; Richardson, Clay; Nagley, Scott; Hunn, John; Shaber, Eric

2010-01-01

Babcock and Wilcox (B and W) has been producing high quality uranium oxycarbide (UCO) kernels for Advanced Gas Reactor (AGR) fuel tests at the Idaho National Laboratory. In 2005, 350-(micro)m, 19.7% 235U-enriched UCO kernels were produced for the AGR-1 test fuel. Following coating of these kernels and forming the coated-particles into compacts, this fuel was irradiated in the Advanced Test Reactor (ATR) from December 2006 until November 2009. B and W produced 425-(micro)m, 14% enriched UCO kernels in 2008, and these kernels were used to produce fuel for the AGR-2 experiment that was inserted in ATR in 2010. B and W also produced 500-(micro)m, 9.6% enriched UO2 kernels for the AGR-2 experiments. Kernels of the same size and enrichment as AGR-1 were also produced for the AGR-3/4 experiment. In addition to fabricating enriched UCO and UO2 kernels, B and W has produced more than 100 kg of natural uranium UCO kernels which are being used in coating development tests. Successive lots of kernels have demonstrated consistent high quality and also allowed for fabrication process improvements. Improvements in kernel forming were made subsequent to AGR-1 kernel production. Following fabrication of AGR-2 kernels, incremental increases in sintering furnace charge size have been demonstrated. Recently small scale sintering tests using a small development furnace equipped with a residual gas analyzer (RGA) has increased understanding of how kernel sintering parameters affect sintered kernel properties. The steps taken to increase throughput and process knowledge have reduced kernel production costs. Studies have been performed of additional modifications toward the goal of increasing capacity of the current fabrication line to use for production of first core fuel for the Next Generation Nuclear Plant (NGNP) and providing a basis for the design of a full scale fuel fabrication facility.

The influence of α-amylase supplementation, γ-irradiation (60Co) as well as long time of storage of wheat grain on flour technological properties

International Nuclear Information System (INIS)

Warchalewski, J.R.

1989-01-01

The varieties of winter wheat, Aria and Beta, were studied. The Aria variety was stored for the period of four years. The part of wheat grain from Beta variety was irradiated with γ rays ( 60 Co). In extracts from wheat kernels and flour protein content, total α- and β-amylolytic activity as well as α-amylolytic activity were determined, α-amylases of native and fungal origin were added to the flour obtained from samples of stored wheat kernels (Aria), irradiated and non-irradiated (Beta). Consequently native α-amylase activity of flour increased by 25% and 50%, respectively. Extensive technological estimation of grain and flour with amylase supplements was carried out. The study included: sedimentation analysis, falling number test, milling experiment, farinogram and extensogram analyses, measurement of the degree of damaged starch and flour colour, as well as baking experiment. The obtained experimental loaves of bread were tested for their ability to remain fresh. It was found out that the stored grain flour was characterized by the highest α-amylolytic activity and the lowest falling number value, whereas the irradiated grain flour showed the highest degree of starch damage and water absorption. When α-amylase supplementation to doughs was not accompanied by either irradiation or storage of grain, it definitely changed their physical properties for the worse. The negative influence of native α-amylases appeared to be less significant than that of fungal α-amylases. The positive influence of α-amylase supplementations, especially of those increasing by 25% the native α-amylolytic activity of flour on volume, and freshness of loaves of bread was observed. (author)

Studies on productivity lodge resistance of radiation induced mutants of syrian local durum wheat

Energy Technology Data Exchange (ETDEWEB)

Elfares, A M; Ghazal, H M [Dep. of Radiation Agriculture, Syrian Atomic Energy Commision, Damascus, P.O. Box 6091, (Syrian Arab Republic)

1995-10-01

The aim of the research was to induce mutations characterized by lodging resistant and high yielding ability in two syrian local durum wheat land races. This research was carried out at two periods during 1983-1987 and from 1991-1993. At the first period, Kernels of Hourani and Senatore Cappelle were treated with 10, 15, 20, 25 and 30 K rad of gamma rays at the Laboratory of the commission of Syrian Atomic Energy to induce mutations. The treated Kernels were planted in 1983/1984 season. After that, selection were practicised on plants which characterized by good performance and lodging resistant. During the successive seasons, screening were made on mutant lines to keep out only lines which show adaptability to intensive cultivation. Second period includes testing of selected lines at two govern orates of syria (Raqqa and Aleppo) during three successive seasons; 1991/1992 and 1992/1993 under intensive cultivation conditions (fertilization, irrigation, stands, etc.).

Option Valuation with Volatility Components, Fat Tails, and Nonlinear Pricing Kernels

DEFF Research Database (Denmark)

Babaoglu, Kadir Gokhan; Christoffersen, Peter; Heston, Steven

We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A second volatility factor is economically most i...

Anisotropic hydrodynamics with a scalar collisional kernel

Science.gov (United States)

Almaalol, Dekrayat; Strickland, Michael

2018-04-01

Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

Object classification and detection with context kernel descriptors

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2014-01-01

Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

Rising Temperatures Reduce Global Wheat Production

Science.gov (United States)

Asseng, S.; Ewert, F.; Martre, P.; Rötter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.;

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Natural variation in grain composition of wheat and related cereals.

Science.gov (United States)

Shewry, Peter R; Hawkesford, Malcolm J; Piironen, Vieno; Lampi, Ann-Maija; Gebruers, Kurt; Boros, Danuta; Andersson, Annica A M; Åman, Per; Rakszegi, Mariann; Bedo, Zoltan; Ward, Jane L

2013-09-04

The wheat grain comprises three groups of major components, starch, protein, and cell wall polysaccharides (dietary fiber), and a range of minor components that may confer benefits to human health. Detailed analyses of dietary fiber and other bioactive components were carried out under the EU FP6 HEALTHGRAIN program on 150 bread wheat lines grown on a single site, 50 lines of other wheat species and other cereals grown on the same site, and 23-26 bread wheat lines grown in six environments. Principal component analysis allowed the 150 bread wheat lines to be classified on the basis of differences in their contents of bioactive components and wheat species (bread, durum, spelt, emmer, and einkorn wheats) to be clearly separated from related cereals (barley, rye, and oats). Such multivariate analyses could be used to define substantial equivalence when novel (including transgenic) cereals are considered.

Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

Science.gov (United States)

Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

Reproducing kernel method with Taylor expansion for linear Volterra integro-differential equations

Directory of Open Access Journals (Sweden)

Azizallah Alvandi

2017-06-01

Full Text Available This research aims of the present a new and single algorithm for linear integro-differential equations (LIDE. To apply the reproducing Hilbert kernel method, there is made an equivalent transformation by using Taylor series for solving LIDEs. Shown in series form is the analytical solution in the reproducing kernel space and the approximate solution $ u_{N} $ is constructed by truncating the series to $ N $ terms. It is easy to prove the convergence of $ u_{N} $ to the analytical solution. The numerical solutions from the proposed method indicate that this approach can be implemented easily which shows attractive features.

Wigner functions defined with Laplace transform kernels.

Science.gov (United States)

Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

2011-10-24

We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

Metabolic network prediction through pairwise rational kernels.

Science.gov (United States)

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

Science.gov (United States)

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

Directory of Open Access Journals (Sweden)

Massaine Bandeira e Sousa

2017-06-01

Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia

OpenAIRE

El-Nahhal, Yasser; Hamdona, Nisreen

2015-01-01

This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values ...

Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

OpenAIRE

Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

2017-01-01

Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...

The Linux kernel as flexible product-line architecture

NARCIS (Netherlands)

M. de Jonge (Merijn)

2002-01-01

textabstractThe Linux kernel source tree is huge ($>$ 125 MB) and inflexible (because it is difficult to add new kernel components). We propose to make this architecture more flexible by assembling kernel source trees dynamically from individual kernel components. Users then, can select what

A SNP-Based Molecular Barcode for Characterization of Common Wheat.

Directory of Open Access Journals (Sweden)

LiFeng Gao

Full Text Available Wheat is grown as a staple crop worldwide. It is important to develop an effective genotyping tool for this cereal grain both to identify germplasm diversity and to protect the rights of breeders. Single-nucleotide polymorphism (SNP genotyping provides a means for developing a practical, rapid, inexpensive and high-throughput assay. Here, we investigated SNPs as robust markers of genetic variation for typing wheat cultivars. We identified SNPs from an array of 9000 across a collection of 429 well-known wheat cultivars grown in China, of which 43 SNP markers with high minor allele frequency and variations discriminated the selected wheat varieties and their wild ancestors. This SNP-based barcode will allow for the rapid and precise identification of wheat germplasm resources and newly released varieties and will further assist in the wheat breeding program.

Exploiting graph kernels for high performance biomedical relation extraction.

Science.gov (United States)

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

Learning a peptide-protein binding affinity predictor with kernel ridge regression

Science.gov (United States)

2013-01-01

Background The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. Results We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it’s approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. Conclusion On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting

a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

Science.gov (United States)

Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

2014-10-01

In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

GRIM : Leveraging GPUs for Kernel integrity monitoring

NARCIS (Netherlands)

Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris

2016-01-01

Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious

7 CFR 51.2296 - Three-fourths half kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

Tolerance to Septoria nodorum in wheat: Evaluation of the infection and selection method and the mutagenesis programme

International Nuclear Information System (INIS)

Broennimann, A.; Fossati, A.

1977-01-01

In Switzerland, the selection for tolerance in wheat to Septoria nodorum Berk. has been carried out for quite a long time. The selection is based on artificial field infection and selection according to the grain appearance. The relative thousand kernel weight (infected as a percentage of the uninfected control) is used as a reference for tolerance. The advantage and the inconvenience of this method are discussed in the first part of the paper. The second part deals with the use of the mutation technique for increasing tolerance to Septoria nodorum in short forms of wheat. Two ways were suitable: the selection for tolerance in short forms or the shortening of tolerant forms. Since increased tolerance is normally combined with a decrease in yield if the disease is absent, these lines can be used only as parents for tolerance in a breeding programme. (author)

Comparative proteome analysis of metabolic proteins from seeds of durum wheat (cv. Svevo) subjected to heat stress

DEFF Research Database (Denmark)

Laino, Paolo; Shelton, Dale; Finnie, Christine

2010-01-01

of nonprolamin proteins were monitored to identify polypeptides affected by heat stress during grain fill. This study shows that heat stress alters significantly the durum wheat seed proteome, although the changes range is only between 1.2- and 2.2-fold. This analysis revealed 132 differentially expressed...... include proteins with metabolic activity or structural function. In order to investigate the consequences of heat stress on the accumulation of nonprolamin proteins in mature durum wheat kernels, the Italian cultivar Svevo was subjected to two thermal regimes (heat stress versus control). The 2-D patterns...... polypeptides, 47 of which were identified by MALDI-TOF and MALDI-TOF-TOF MS and included HSPs, proteins involved in the glycolysis and carbohydrate metabolism, as well as stress-related proteins. Many of the heat-induced polypeptides are considered to be allergenic for sensitive individuals....

Monitoring of wheat lactic acid bacteria from the field until the first step of dough fermentation.

Science.gov (United States)

Alfonzo, Antonio; Miceli, Claudia; Nasca, Anna; Franciosi, Elena; Ventimiglia, Giusi; Di Gerlando, Rosalia; Tuohy, Kieran; Francesca, Nicola; Moschetti, Giancarlo; Settanni, Luca

2017-04-01

The present work was carried out to retrieve the origin of lactic acid bacteria (LAB) in sourdough. To this purpose, wheat LAB were monitored from ear harvest until the first step of fermentation for sourdough development. The influence of the geographical area and variety on LAB species/strain composition was also determined. The ears of four Triticum durum varieties (Duilio, Iride, Saragolla and Simeto) were collected from several fields located within the Palermo province (Sicily, Italy) and microbiologically investigated. In order to trace the transfer of LAB during the consecutive steps of manipulation, ears were transformed aseptically and, after threshing, milling and fermentation, samples of kernels, semolinas and doughs, respectively, were analysed. LAB were not found to dominate the microbial communities of the raw materials. In general, kernels harboured lower levels of microorganisms than ears and ears than semolinas. Several samples showing no development of LAB colonies acidified the enrichment broth suggesting the presence of LAB below the detection limit. After fermentation, LAB loads increased consistently for all doughs, reaching levels of 7.0-7.5 Log CFU/g on M17. The values of pH (5.0) and TTA (5.6 mL NaOH/10 g of dough) indicated the occurrence of the acidification process for several doughs. LAB were phenotypically and genotypically differentiated by randomly amplified polymorphic DNA (RAPD)-PCR into eight groups including 51 strains belonging to the species Lactobacillus brevis, Lactobacillus coryniformis, Lactobacillus plantarum, Lactococcus lactis, Lactococcus garvieae, Enterococcus casseliflavus, Enterococcus faecium, Leuconostoc citreum, and Pediococcus pentosaceus. Lactobacilli constituted a minority the LAB community, while lactococci represented more than 50% of strains. Lower LAB complexity was found on kernels, while a richer biodiversity was observed in semolinas and fermented doughs. For broader microbiota characterisation in

The pangenome of hexaploid bread wheat.

Science.gov (United States)

Montenegro, Juan D; Golicz, Agnieszka A; Bayer, Philipp E; Hurgobin, Bhavna; Lee, HueyTyng; Chan, Chon-Kit Kenneth; Visendi, Paul; Lai, Kaitao; Doležel, Jaroslav; Batley, Jacqueline; Edwards, David

2017-06-01

There is an increasing understanding that variation in gene presence-absence plays an important role in the heritability of agronomic traits; however, there have been relatively few studies on variation in gene presence-absence in crop species. Hexaploid wheat is one of the most important food crops in the world and intensive breeding has reduced the genetic diversity of elite cultivars. Major efforts have produced draft genome assemblies for the cultivar Chinese Spring, but it is unknown how well this represents the genome diversity found in current modern elite cultivars. In this study we build an improved reference for Chinese Spring and explore gene diversity across 18 wheat cultivars. We predict a pangenome size of 140 500 ± 102 genes, a core genome of 81 070 ± 1631 genes and an average of 128 656 genes in each cultivar. Functional annotation of the variable gene set suggests that it is enriched for genes that may be associated with important agronomic traits. In addition to variation in gene presence, more than 36 million intervarietal single nucleotide polymorphisms were identified across the pangenome. This study of the wheat pangenome provides insight into genome diversity in elite wheat as a basis for genomics-based improvement of this important crop. A wheat pangenome, GBrowse, is available at http://appliedbioinformatics.com.au/cgi-bin/gb2/gbrowse/WheatPan/, and data are available to download from http://wheatgenome.info/wheat_genome_databases.php. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

Science.gov (United States)

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...

African Journals Online (AJOL)

This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain.

Science.gov (United States)

Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

2016-01-01

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4%) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha(-1) year(-1), except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

A kernel version of multivariate alteration detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

2013-01-01

Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....

Single Nucleotide Polymorphisms in B-Genome Specific UDP-Glucosyl Transferases Associated with Fusarium Head Blight Resistance and Reduced Deoxynivalenol Accumulation in Wheat Grain.

Science.gov (United States)

Sharma, Pallavi; Gangola, Manu P; Huang, Chen; Kutcher, H Randy; Ganeshan, Seedhabadee; Chibbar, Ravindra N

2018-01-01

An in vitro spike culture method was optimized to evaluate Fusarium head blight (FHB) resistance in wheat (Triticum aestivum) and used to screen a population of ethyl methane sulfonate treated spike culture-derived variants (SCDV). Of the 134 SCDV evaluated, the disease severity score of 47 of the variants was ≤30%. Single nucleotide polymorphisms (SNP) in the UDP-glucosyltransferase (UGT) genes, TaUGT-2B, TaUGT-3B, and TaUGT-EST, differed between AC Nanda (an FHB-susceptible wheat variety) and Sumai-3 (an FHB-resistant wheat cultivar). SNP at 450 and 1,558 bp from the translation initiation site in TaUGT-2B and TaUGT-3B, respectively were negatively correlated with FHB severity in the SCDV population, whereas the SNP in TaUGT-EST was not associated with FHB severity. Fusarium graminearum strain M7-07-1 induced early expression of TaUGT-2B and TaUGT-3B in FHB-resistant SCDV lines, which were associated with deoxynivalenol accumulation and reduced FHB disease progression. At 8 days after inoculation, deoxynivalenol concentration varied from 767 ppm in FHB-resistant variants to 2,576 ppm in FHB-susceptible variants. The FHB-resistant SCDV identified can be used as new sources of FHB resistance in wheat improvement programs.

Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat.

Science.gov (United States)

Placido, Dante F; Campbell, Malachy T; Folsom, Jing J; Cui, Xinping; Kruger, Greg R; Baenziger, P Stephen; Walia, Harkamal

2013-04-01

Root architecture traits are an important component for improving water stress adaptation. However, selection for aboveground traits under favorable environments in modern cultivars may have led to an inadvertent loss of genes and novel alleles beneficial for adapting to environments with limited water. In this study, we elucidate the physiological and molecular consequences of introgressing an alien chromosome segment (7DL) from a wild wheat relative species (Agropyron elongatum) into cultivated wheat (Triticum aestivum). The wheat translocation line had improved water stress adaptation and higher root and shoot biomass compared with the control genotypes, which showed significant drops in root and shoot biomass during stress. Enhanced access to water due to higher root biomass enabled the translocation line to maintain more favorable gas-exchange and carbon assimilation levels relative to the wild-type wheat genotypes during water stress. Transcriptome analysis identified candidate genes associated with root development. Two of these candidate genes mapped to the site of translocation on chromosome 7DL based on single-feature polymorphism analysis. A brassinosteroid signaling pathway was predicted to be involved in the novel root responses observed in the A. elongatum translocation line, based on the coexpression-based gene network generated by seeding the network with the candidate genes. We present an effective and highly integrated approach that combines root phenotyping, whole-plant physiology, and functional genomics to discover novel root traits and the underlying genes from a wild related species to improve drought adaptation in cultivated wheat.

Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

Science.gov (United States)

Kwak, Nojun

2016-05-20

Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

Molecular and cytogenetic characterization of the 5DS-5BS chromosome translocation conditioning soft kernel texture in durum wheat

Science.gov (United States)

Cultivar ‘Soft Svevo’, a new non-GMO soft durum cultivar with soft kernel texture, was developed through a 5DS(5BS) chromosomal translocation from event. cv. Chinese Spring, and subsequently used to create new soft durum germplasm. The development of Soft Svevo featured the Ph1b-mediated homoeologou...

Uranium kernel formation via internal gelation

International Nuclear Information System (INIS)

Hunt, R.D.; Collins, J.L.

2004-01-01

In the 1970s and 1980s, U.S. Department of Energy (DOE) conducted numerous studies on the fabrication of nuclear fuel particles using the internal gelation process. These amorphous kernels were prone to flaking or breaking when gases tried to escape from the kernels during calcination and sintering. These earlier kernels would not meet today's proposed specifications for reactor fuel. In the interim, the internal gelation process has been used to create hydrous metal oxide microspheres for the treatment of nuclear waste. With the renewed interest in advanced nuclear fuel by the DOE, the lessons learned from the nuclear waste studies were recently applied to the fabrication of uranium kernels, which will become tri-isotropic (TRISO) fuel particles. These process improvements included equipment modifications, small changes to the feed formulations, and a new temperature profile for the calcination and sintering. The modifications to the laboratory-scale equipment and its operation as well as small changes to the feed composition increased the product yield from 60% to 80%-99%. The new kernels were substantially less glassy, and no evidence of flaking was found. Finally, key process parameters were identified, and their effects on the uranium microspheres and kernels are discussed. (orig.)

Kernel learning at the first level of inference.

Science.gov (United States)

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Global Polynomial Kernel Hazard Estimation

DEFF Research Database (Denmark)

Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch

2015-01-01

This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

Quantum tomography, phase-space observables and generalized Markov kernels

International Nuclear Information System (INIS)

Pellonpaeae, Juha-Pekka

2009-01-01

We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase-space observable with a regular kernel state. Illustrative examples are given in the cases of a 'Schroedinger cat' kernel state and the Cahill-Glauber s-parametrized distributions. Also we consider an example of a kernel state when the generalized Markov kernel cannot be constructed.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Relationship between attenuation coefficients and dose-spread kernels

International Nuclear Information System (INIS)

Boyer, A.L.

1988-01-01

Dose-spread kernels can be used to calculate the dose distribution in a photon beam by convolving the kernel with the primary fluence distribution. The theoretical relationships between various types and components of dose-spread kernels relative to photon attenuation coefficients are explored. These relations can be valuable as checks on the conservation of energy by dose-spread kernels calculated by analytic or Monte Carlo methods

Canola-Wheat Rotation versus Continuous Wheat for the Southern Plains

OpenAIRE

Duke, Jason C.; Epplin, Francis M.; Vitale, Jeffrey D.; Peeper, Thomas F.

2009-01-01

Crop rotations are not common in the wheat belt of the Southern Plains. After years of continuous wheat, weeds have become increasingly difficult and expensive to manage. Yield data were elicited from farmers and used to determine if canola-wheat-wheat rotations are economically competitive with continuous wheat in the region.

Mixture Density Mercer Kernels: A Method to Learn Kernels

Data.gov (United States)

National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...

Integral equations with contrasting kernels

Directory of Open Access Journals (Sweden)

Theodore Burton

2008-01-01

Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.

Kernel methods in orthogonalization of multi- and hypervariate data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis...... via inner products in the Gram matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings...... are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MAF analysis handle nonlinearities by implicitly transforming data into high (even infinite...

Kernel based subspace projection of near infrared hyperspectral images of maize kernels

DEFF Research Database (Denmark)

Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

2009-01-01

In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...

Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

Science.gov (United States)

2016-01-05

SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model, is able to model the rate of occurrence of... kernel methods made use of: (i) the Bayesian property of improving predictive accuracy as data are dynamically obtained, and (ii) the kernel function

The Classification of Diabetes Mellitus Using Kernel k-means

Science.gov (United States)

Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

2018-01-01

Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

Evaluating the Application of Tissue-Specific Dose Kernels Instead of Water Dose Kernels in Internal Dosimetry : A Monte Carlo Study

NARCIS (Netherlands)

Moghadam, Maryam Khazaee; Asl, Alireza Kamali; Geramifar, Parham; Zaidi, Habib

2016-01-01

Purpose: The aim of this work is to evaluate the application of tissue-specific dose kernels instead of water dose kernels to improve the accuracy of patient-specific dosimetry by taking tissue heterogeneities into consideration. Materials and Methods: Tissue-specific dose point kernels (DPKs) and

Characterization of a Wheat Breeders' Array suitable for high-throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum).

Science.gov (United States)

Allen, Alexandra M; Winfield, Mark O; Burridge, Amanda J; Downie, Rowena C; Benbow, Harriet R; Barker, Gary L A; Wilkinson, Paul A; Coghill, Jane; Waterfall, Christy; Davassi, Alessandro; Scopes, Geoff; Pirani, Ali; Webster, Teresa; Brew, Fiona; Bloor, Claire; Griffiths, Simon; Bentley, Alison R; Alda, Mark; Jack, Peter; Phillips, Andrew L; Edwards, Keith J

2017-03-01

Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism-based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high-density Affymetrix Axiom ® genotyping array (the Wheat Breeders' Array), in a high-throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders' Array is also suitable for generating high-density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site 'CerealsDB'. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Parsimonious Wavelet Kernel Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Wang Qin

2015-11-01

Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

Difference between standard and quasi-conformal BFKL kernels

International Nuclear Information System (INIS)

Fadin, V.S.; Fiore, R.; Papa, A.

2012-01-01

As it was recently shown, the colour singlet BFKL kernel, taken in Möbius representation in the space of impact parameters, can be written in quasi-conformal shape, which is unbelievably simple compared with the conventional form of the BFKL kernel in momentum space. It was also proved that the total kernel is completely defined by its Möbius representation. In this paper we calculated the difference between standard and quasi-conformal BFKL kernels in momentum space and discovered that it is rather simple. Therefore we come to the conclusion that the simplicity of the quasi-conformal kernel is caused mainly by using the impact parameter space.

An enzyme complex increases in vitro dry matter digestibility of corn and wheat in pigs.

Science.gov (United States)

Park, Kyu Ree; Park, Chan Sol; Kim, Beob Gyun

2016-01-01

Two experiments were conducted to determine the effects of enzyme complex on in vitro dry matter (DM) digestibility for feed ingredients. The objective of experiment 1 was to screen feed ingredients that can be effective substrates for an enzyme complex, mainly consisted of β-pentosanase, β-glucanase and α-amylase, using in vitro digestibility methods. In experiment 1, the test ingredients were three grain sources (barley, corn and wheat) and six protein supplements (canola meal, copra expellers, cottonseed meal, distillers dried grains with solubles, palm kernel expellers and soybean meal). In vitro ileal and total tract digestibility (IVID and IVTTD, respectively) of DM for test ingredients were determined. In vitro digestibility methods consisted of two- or three-step procedure simulating in vivo digestion in the pig gastrointestinal tracts with or without enzyme complex. As the enzyme complex added, the IVID of DM for corn and wheat increased (p digestibility, corn grains were selected to determine the in vitro digestibility of the fractions (starch, germ, hull and gluten) that maximally respond to the enzyme complex in experiment 2. The IVID of DM for corn starch, germ and hull increased (p digestibility of corn and wheat, and the digestibility increments of corn are mainly attributed to the increased digestibility of corn starch.

Kernel Tuning and Nonuniform Influence on Optical and Electrochemical Gaps of Bimetal Nanoclusters.

Science.gov (United States)

He, Lizhong; Yuan, Jinyun; Xia, Nan; Liao, Lingwen; Liu, Xu; Gan, Zibao; Wang, Chengming; Yang, Jinlong; Wu, Zhikun

2018-03-14

Fine tuning nanoparticles with atomic precision is exciting and challenging and is critical for tuning the properties, understanding the structure-property correlation and determining the practical applications of nanoparticles. Some ultrasmall thiolated metal nanoparticles (metal nanoclusters) have been shown to be precisely doped, and even the protecting staple metal atom could be precisely reduced. However, the precise addition or reduction of the kernel atom while the other metal atoms in the nanocluster remain the same has not been successful until now, to the best of our knowledge. Here, by carefully selecting the protecting ligand with adequate steric hindrance, we synthesized a novel nanocluster in which the kernel can be regarded as that formed by the addition of two silver atoms to both ends of the Pt@Ag 12 icosohedral kernel of the Ag 24 Pt(SR) 18 (SR: thiolate) nanocluster, as revealed by single crystal X-ray crystallography. Interestingly, compared with the previously reported Ag 24 Pt(SR) 18 nanocluster, the as-obtained novel bimetal nanocluster exhibits a similar absorption but a different electrochemical gap. One possible explanation for this result is that the kernel tuning does not essentially change the electronic structure, but obviously influences the charge on the Pt@Ag 12 kernel, as demonstrated by natural population analysis, thus possibly resulting in the large electrochemical gap difference between the two nanoclusters. This work not only provides a novel strategy to tune metal nanoclusters but also reveals that the kernel change does not necessarily alter the optical and electrochemical gaps in a uniform manner, which has important implications for the structure-property correlation of nanoparticles.

Optimising nitrogen in order to improve the efficiency, eco-physiology, yield and quality on one cultivar of durum wheat

Directory of Open Access Journals (Sweden)

Luigi Tedone

2014-04-01

Full Text Available A 3-year field experiment was carried out in southern Italy to evaluate the effect of different combinations of nitrogen (N fertilizer rates (0, 55, 90, 135 kg ha–1, time of application (sowing, tillering, stem elongation and number of nitrogen applications on durum wheat (Triticum turgidum L., var. durum. A total of eight different combinations - in terms of quantity and time of application - were arranged in a randomized complete block design with four replications. Soil plant analysis development was analysed along with leaf area index, grain and straw yield, plant height, plant lodging, thousand-kernel weight, non-vitreous kernels, shrunken and discarded kernels, hectolitre weight, grain protein content, and sodium dodecylsulfate sedimentation. Nitrogen contents of soil, grain and straw were measured in order to assess nitrogen efficiency. The results showed the positive effect of increased nitrogen dosages of 90 and 135 kg ha–1. The optimization of nitrogen administration increased by splitting the nitrogen into three application times, as shown by the eco-physiological, productive and qualitative parameters, and the nitrogen efficiency parameters measured (N application efficiency and N recovery fraction.

Identification of leaf rust resistant gene Lr10 in Pakistani wheat ...

African Journals Online (AJOL)

Leaf (brown) rust is the major disease of wheat in Pakistan and other countries. The disease is more effectively controlled when several rust resistance genes are pyramided into a single line. Molecular survey was conducted to screen 25 Pakistan wheat germplasm for the presence of leaf rust resistance gene Lr10 using ...

A laser optical method for detecting corn kernel defects

Energy Technology Data Exchange (ETDEWEB)

Gunasekaran, S.; Paulsen, M. R.; Shove, G. C.

1984-01-01

An opto-electronic instrument was developed to examine individual corn kernels and detect various kernel defects according to reflectance differences. A low power helium-neon (He-Ne) laser (632.8 nm, red light) was used as the light source in the instrument. Reflectance from good and defective parts of corn kernel surfaces differed by approximately 40%. Broken, chipped, and starch-cracked kernels were detected with nearly 100% accuracy; while surface-split kernels were detected with about 80% accuracy. (author)

GWAS for plant growth stages and yield components in spring wheat (Triticum aestivum L.) harvested in three regions of Kazakhstan.

Science.gov (United States)

Turuspekov, Yerlan; Baibulatova, Aida; Yermekbayev, Kanat; Tokhetova, Laura; Chudinov, Vladimir; Sereda, Grigoriy; Ganal, Martin; Griffiths, Simon; Abugalieva, Saule

2017-11-14

Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS. Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits. Field

Kernel maximum autocorrelation factor and minimum noise fraction transformations

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...

Combined effects of elevated temperature and CO2 enhance threat from low temperature hazard to winter wheat growth in North China.

Science.gov (United States)

Tan, Kaiyan; Zhou, Guangsheng; Lv, Xiaomin; Guo, Jianping; Ren, Sanxue

2018-03-12

We examined the growth and yield of winter wheat (Triticum aestivum) in response to the predicted elevated CO 2 concentration and temperature to determine the mechanism of the combined impacts in North China Plain. An elevated treatment (CO 2 : 600 μmol mol -1 , temperature: +2.5~3.0 °C, ECTI) and a control treatment (ambient CO 2 and temperature, CK) were conducted in open-top chambers from October 2013 to June 2016. Post-winter growth stages of winter wheat largely advanced and shifted to a cooler period of nature season under combined impact of elevated CO 2 and temperature during the entire growing season. The mean temperature and accumulated photosynthetic active radiations (PAR) over the post-winter growing period in ECTI decreased by 0.8-1.5 °C and 10-13%, respectively compared with that in CK, negatively impacted winter wheat growth. As a result, winter wheat in ECTI suffered from low temperature hazards during critical period of floret development and anthesis and grain number per ear was reduced by 10-31% in the three years. Although 1000-kernel weight in ECTI increased by 8-9% mainly due to elevated CO 2 , increasing CO 2 concentration from 400 to 600 μmol mol -1 throughout the growth stage was not able to offset the adverse effect of warming on winter wheat growth and yield.

Effects of space environment on chlorophyll fluorescence and photosynthesis characteristics of wheat

International Nuclear Information System (INIS)

Lu Li; Lv Jinyin; Gong Qingzhu; Gao Junfeng

2006-01-01

The effects of the space environment on the chlorophyll fluorescence parameters and photosynthesis characteristics of wheat cultivars, Xinong 1043 M1 and Shaan253 M 1 , were studied. The results showed that the decrement of contents of PS II primary photochemical efficiency (F v /F m ), potential activity (F v /F 0 ), photochemical quenching coefficient (qP) and photosynthesis rate (Pn) were less than that of control, increment of non-photochemical quenching coefficient (qN) were more than that of control. The results suggested that photosynthetic apparatus were damaged, photosynthetic electron transport, photosynthetic primary reaction were inhibited, rate of photosynthesis decreased and growth of M 1 plant were retarded, which leading to thousand kernel weights decreased. (authors)

Profitability of Integrated Management of Fusarium Head Blight in North Carolina Winter Wheat.

Science.gov (United States)

Cowger, Christina; Weisz, Randy; Arellano, Consuelo; Murphy, Paul

2016-08-01

Fusarium head blight (FHB) is one of the most difficult small-grain diseases to manage, due to the partial effectiveness of management techniques and the narrow window of time in which to apply fungicides profitably. The most effective management approach is to integrate cultivar resistance with FHB-specific fungicide applications; yet, when forecasted risk is intermediate, it is often unclear whether such an application will be profitable. To model the profitability of FHB management under varying conditions, we conducted a 2-year split-plot field experiment having as main plots high-yielding soft red winter wheat cultivars, four moderately resistant (MR) and three susceptible (S) to FHB. Subplots were sprayed at flowering with Prosaro or Caramba, or left untreated. The experiment was planted in seven North Carolina environments (location-year combinations); three were irrigated to promote FHB development and four were not irrigated. Response variables were yield, test weight, disease incidence, disease severity, deoxynivalenol (DON), Fusarium-damaged kernels, and percent infected kernels. Partial profits were compared in two ways: first, across low-, medium-, or high-DON environments; and second, across environment-cultivar combinations divided by risk forecast into "do spray" and "do not spray" categories. After surveying DON and test weight dockage among 21 North Carolina wheat purchasers, three typical market scenarios were used for modeling profitability: feed-wheat, flexible (feed or flour), and the flour market. A major finding was that, on average, MR cultivars were at least as profitable as S cultivars, regardless of epidemic severity or market. Fungicides were profitable in the feed-grain and flexible markets when DON was high, with MR cultivars in the flexible or flour markets when DON was intermediate, and on S cultivars aimed at the flexible market. The flour market was only profitable when FHB was present if DON levels were intermediate and cultivar

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

Science.gov (United States)

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

Digital signal processing with kernel methods

CERN Document Server

Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

2018-01-01

A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

African Journals Online (AJOL)

In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...

Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

African Journals Online (AJOL)

This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

Directory of Open Access Journals (Sweden)

Mohammed D. ABDULMALIK

2008-06-01

Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.

IDENTIFICATION AND MAPPING OF A GENE FOR RICE SLENDER KERNEL USING Oryza glumaepatula INTROGRESSION LINES

Directory of Open Access Journals (Sweden)

Sobrizal Sobrizal

2016-10-01

Full Text Available World demand for superior rice grain quality tends to increase. One of the  criteria of appearance quality of rice grain is grain shape. Rice consumers  exhibit wide preferences for grain shape, but most Indonesian rice consumers prefer long and slender grain. The objectives of this study were to identify and map a gene for rice slender kernel trait using Oryza  glumaepatula introgression lines with O. sativa cv. Taichung 65 genetic background. A segregation analysis of BC4F2 population derived from backcrosses of a donor parent O. glumaepatula into a recurrent parent Taichung 65 showed that the slender kernel was controlled by a single recessive gene. This new identified gene was designated as sk1 (slender kernel 1. Moreover, based on the RFLP analyses using 14 RFLP markers located on chromosomes 2, 8, 9, and 10 in which the O. glumaepatula chromosomal segments were retained in BC4F2 population, the sk1 was located between RFLP markers C679 and C560 on the long arm of chromosome 2, with map distances of 2.8 and 1.5 cM, respectively. The wild rice O. glumaepatula carried a recessive allele for slender kernel. This allele may be useful in breeding of rice with slender kernel types. In addition, the development of plant materials and RFLP map associated with slender kernel in this study is the preliminary works in the effort to isolate this important grain shape gene.

Analysis of grain filling process to the varied meteorological conditions in winter wheat [Triticum aestivum] cultivars

International Nuclear Information System (INIS)

Inoue, K.; Nakazono, K.; Wakiyama, Y.

2005-01-01

This paper describes effects of varied meteorological conditions on the grain filling periods, stabilities of yield and quality of winter wheat cultivars with different maturity characteristics (cv. Ayahikari, Norin61, Bandowase, and Tsurupikari). In the field experiments, the meteorological treatments were made during the first heading time on 17 April 2001 and the middle heading time on 24 April 2000. Air temperature, global solar radiation and soil moisture were controlled using a rain shelter, cheesecloth and irrigation system. The growth speed and growth period of wheat grains varied among four winter wheat cultivars, depending on meteorological conditions. The growth speed increased within 1 8.4 deg C of mean air temperature over the 30 days after the anthesis. On the other hand, it was found that the growth speed of wheat grains and the maximum number of wheat grains (Ymax) decreased greatly with the 44.4% interception of global solar radiation. Logistic functions were fitted to the relationship between the relative thousand-kernel-weight (Y/Ymax) and the total integrated temperature (sigmaTa) after heading for all treatment conditions. The maximum weight of grains (Ymax) achieved at the harvest time varied somewhat clearly among four winter wheat cultivars and meteorological conditions. Multiple regression analysis showed that the grain yield (Ymax) of four wheat cultivars correlated positively with daily mean solar radiation. It was also found that the cultivar Ayahikari had a highly significant negative correlation between its grain weight and soil moisture. Namely, the grain weight of high soil moisture plot with pF=1.5 was lower by about 9% than that of a control plot with pF=3.5. On the other hand, the grain yield of cultivar Norin61 responded inversely to a wet environment, indicating that its grain weight was higher for high soil moisture and high wet-bulb temperature than for a dry environment. The grain yield of early varieties of Bandowase and

An analysis of 1-D smoothed particle hydrodynamics kernels

International Nuclear Information System (INIS)

Fulk, D.A.; Quinn, D.W.

1996-01-01

In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

Putting Priors in Mixture Density Mercer Kernels

Science.gov (United States)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Identification and validation of single nucleotide polymorphic markers linked to Ug99 stem rust resistance in spring wheat

Science.gov (United States)

Wheat stem rust (Puccinia graminis f. sp. tritici Eriks. and E. Henn.) is one of the most destructive diseases world-wide. Races belonging to Ug99 (or TTKSK) continue to cause crop losses in East Africa and threaten global wheat production. Developing and deploying wheat varieties with multiple race...

Consistent Valuation across Curves Using Pricing Kernels

Directory of Open Access Journals (Sweden)

Andrea Macrina

2018-03-01

Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

NLO corrections to the Kernel of the BKP-equations

Energy Technology Data Exchange (ETDEWEB)

Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)

2012-10-02

We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.

A Fast and Simple Graph Kernel for RDF

NARCIS (Netherlands)

de Vries, G.K.D.; de Rooij, S.

2013-01-01

In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster

Kernel based eigenvalue-decomposition methods for analysing ham

DEFF Research Database (Denmark)

Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

2010-01-01

methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...... useful factor of PCA and kernel based PCA respectively in Figure 2. The factor of the kernel based PCA turned out to be able to segment the two types of meat and in general that factor is much more distinct, compared to the traditional factor. After the orthogonal transformation a simple thresholding...

Dual purpose wheat production with different levels of nitrogen topdressing

Directory of Open Access Journals (Sweden)

Éderson Luis Henz

2016-04-01

Full Text Available Currently, the practice of Crop-Livestock Integration is stimulated as a way of increasing the generation of foreign exchange for Brazil. Integrated systems improve land use efficiency as well as preserve, recover and increment or soil fertility. The aim of this research was to evaluate how different doses of nitrogen fertilization can affect production and quality of dual purpose wheat submitted to grazing. The experimental designed was randomized block with five treatments (0, 75, 150, 225 and 300 Kg N ha-1, like ammonium nitrate and four repetitions. The forage yield, the percentage crude protein (P=.0001 and acid detergent insoluble protein (P=.0054 had a linear increased because of the nitrogen addition doses. The crude protein percentage changed the estimate of all soluble carbohydrates (P=.0001 and non-fibrous carbohydrates (P=.0186, but did not influence the, nitrogen detergent fiber corrected with ash and proteins percentage contributing for content cell. The crops production (P=.0001 and the number of kernels per ear (P=.0001 showed significantly difference because of the nitrogen additions dose, increasing the number of fertile flowers. The nitrogen topdressing alters forage production, the chemical composition and the production of dual purpose wheat grains subjected to grazing.

Kernel principal component analysis for change detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Morton, J.C.

2008-01-01

region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....

7 CFR 981.61 - Redetermination of kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of almonds...

Eucalyptus-Palm Kernel Oil Blends: A Complete Elimination of Diesel in a 4-Stroke VCR Diesel Engine

Directory of Open Access Journals (Sweden)

Srinivas Kommana

2015-01-01

Full Text Available Fuels derived from biomass are mostly preferred as alternative fuels for IC engines as they are abundantly available and renewable in nature. The objective of the study is to identify the parameters that influence gross indicated fuel conversion efficiency and how they are affected by the use of biodiesel relative to petroleum diesel. Important physicochemical properties of palm kernel oil and eucalyptus blend were experimentally evaluated and found within acceptable limits of relevant standards. As most of vegetable oils are edible, growing concern for trying nonedible and waste fats as alternative to petrodiesel has emerged. In present study diesel fuel is completely replaced by biofuels, namely, methyl ester of palm kernel oil and eucalyptus oil in various blends. Different blends of palm kernel oil and eucalyptus oil are prepared on volume basis and used as operating fuel in single cylinder 4-stroke variable compression ratio diesel engine. Performance and emission characteristics of these blends are studied by varying the compression ratio. In the present experiment methyl ester extracted from palm kernel oil is considered as ignition improver and eucalyptus oil is considered as the fuel. The blends taken are PKE05 (palm kernel oil 95 + eucalyptus 05, PKE10 (palm kernel oil 90 + eucalyptus 10, and PKE15 (palm kernel 85 + eucalyptus 15. The results obtained by operating with these fuels are compared with results of pure diesel; finally the most preferable combination and the preferred compression ratio are identified.

Adaptive metric kernel regression

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

2000-01-01

Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

Consistent Estimation of Pricing Kernels from Noisy Price Data

OpenAIRE

Vladislav Kargin

2003-01-01

If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

Stable Kernel Representations as Nonlinear Left Coprime Factorizations

NARCIS (Netherlands)

Paice, A.D.B.; Schaft, A.J. van der

1994-01-01

A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

7 CFR 981.60 - Determination of kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which settlement...

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Ling-Yu Duan

2010-01-01

Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Tian Yonghong

2010-01-01

Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

ADSORPTION OF COPPER FROM AQUEOUS SOLUTION BY ELAIS GUINEENSIS KERNEL ACTIVATED CARBON

Directory of Open Access Journals (Sweden)

NAJUA DELAILA TUMIN

2008-08-01

Full Text Available In this study, a series of batch laboratory experiments were conducted in order to investigate the feasibility of Elais Guineensis kernel or known as palm kernel shell (PKS-based activated carbon for the removal of copper from aqueous solution by the adsorption process. Investigation was carried out by studying the influence of initial solution pH, adsorbent dosage and initial concentration of copper. The particle size of PKS used was categorized as PKS–M. All batch experiments were carried out at a constant temperature of 30°C (±2°C using mechanical shaker that operated at 100 rpm. The single component equilibrium data was analyzed using Langmuir, Freundlich, Redlich-Peterson, Temkin and Toth adsorption isotherms.

Determination compliance abilities of some triticale varieties and comparison with wheat in Southeastern Anatolia conditions of Turkey.

Science.gov (United States)

Kendal, Enver; Tekdal, Sertaç; Aktas, Hüsnü; Karaman, Mehmet

2014-01-01

In this research, were used 3 triticale varieties (Tacettinbey, Karma 2000 and Presto), one durum (Sariçanak 98) and one bread (Nurkent) wheat varieties. The study, was randomized as complete block design with four replications in 4 location (southeastern Anatolia of Turkey) and under rainfed conditions during the growing season 2010-2011. With an analysis of variance, significant differences were determined among locations, genotypes and genotype x location interactions at the 1% and 5% level. Following results were obtained: period to heading 109 till 113 days, plant height between 96 and 127 cm, hectoliter weight between 68.2 and 81.7 kg/hl, thousand grain weight between 32.9 and 42.7 g, protein content between 13.3 and 14.7%, humidty kernels at harvest between 9.2 and 9.5% and grain yield between 4409 and 6119 kg/ha(-1). The highest grain yield was obtained with Sariçanak 98 (durum wheat variety) while the best thousant grain weight was obtained by the triticale variety Tacettinbey. The triticale variety Karma 2000 showed higher protein content (14.7%) than other the other triticale varieties as well as durum and bread wheat varieties included trial. For the Southeastern Anatolia Region he results of this study demonstrated that the grain yield of triticale varieties were lower compared to common wheat. Nevertheless the triticale grain yield was higher than these of durum and bread wheat varieties under the more extrem (higher temperature and drought) growing conditions of the Kiziltepe region. For triticale the highest mean grain yield has been obtained fwith the variety Tacettinbey which is spring type. New sping type vatieties are more suitable than wheat for the more extreme growing conditions of the Southeastern Anatolia Region.

Discrete non-parametric kernel estimation for global sensitivity analysis

International Nuclear Information System (INIS)

Senga Kiessé, Tristan; Ventura, Anne

2016-01-01

This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

The Effect of High Concentrations of Glufosinate Ammonium on the Yield Components of Transgenic Spring Wheat (Triticum aestivum L.) Constitutively Expressing the bar Gene

OpenAIRE

Áy, Zoltán; Mihály, Róbert; Cserháti, Mátyás; Kótai, Éva; Pauk, János

2012-01-01

We present an experiment done on a bar + wheat line treated with 14 different concentrations of glufosinate ammonium—an effective component of nonselective herbicides—during seed germination in a closed experimental system. Yield components as number of spikes per plant, number of grains per spike, thousand kernel weight, and yield per plant were thoroughly analysed and statistically evaluated after harvesting. We found that a concentration of glufosinate ammonium 5000 times the lethal dose w...

The fatty acid profile in different wheat cultivars depending on the level of contamination with microscopic fungi.

Science.gov (United States)

Stuper-Szablewska, Kinga; Buśko, Maciej; Góral, Tomasz; Perkowski, Juliusz

2014-06-15

Analyses were conducted on 30 winter wheat samples growing under controlled conditions and following inoculation with fungi Fusarium culmorum. In inoculated samples the mean concentration of 30 analysed fatty acids was significantly higher in relation to the control and amounted to 1,396 mg/kg vs. 1,046 mg/kg in the control kernels. Recorded concentrations for individual cultivars were significantly correlated with the concentration of fungal biomass. Higher concentration in the control was recorded only for the acid trans C18:2n-6. It was also found that the acid profiles are characteristic of individual cultivars. Statistical analysis showed that trans C18:2n-6, C18:1, C18:3n-3 and C18:3n-6 were the acids with the greatest discriminatory power in distinguishing inoculated samples from the control. Discriminatory analysis separated individual cultivars into quality classes of winter wheat cultivars depending on the presence of a specific fatty acid profile. Copyright © 2014 Elsevier Ltd. All rights reserved.

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

Science.gov (United States)

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Improved modeling of clinical data with kernel methods.

Science.gov (United States)

Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

2012-02-01

Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

QTL Mapping of Kernel Number-Related Traits and Validation of One Major QTL for Ear Length in Maize.

Science.gov (United States)

Huo, Dongao; Ning, Qiang; Shen, Xiaomeng; Liu, Lei; Zhang, Zuxin

2016-01-01

The kernel number is a grain yield component and an important maize breeding goal. Ear length, kernel number per row and ear row number are highly correlated with the kernel number per ear, which eventually determines the ear weight and grain yield. In this study, two sets of F2:3 families developed from two bi-parental crosses sharing one inbred line were used to identify quantitative trait loci (QTL) for four kernel number-related traits: ear length, kernel number per row, ear row number and ear weight. A total of 39 QTLs for the four traits were identified in the two populations. The phenotypic variance explained by a single QTL ranged from 0.4% to 29.5%. Additionally, 14 overlapping QTLs formed 5 QTL clusters on chromosomes 1, 4, 5, 7, and 10. Intriguingly, six QTLs for ear length and kernel number per row overlapped in a region on chromosome 1. This region was designated qEL1.10 and was validated as being simultaneously responsible for ear length, kernel number per row and ear weight in a near isogenic line-derived population, suggesting that qEL1.10 was a pleiotropic QTL with large effects. Furthermore, the performance of hybrids generated by crossing 6 elite inbred lines with two near isogenic lines at qEL1.10 showed the breeding value of qEL1.10 for the improvement of the kernel number and grain yield of maize hybrids. This study provides a basis for further fine mapping, molecular marker-aided breeding and functional studies of kernel number-related traits in maize.

Linear and kernel methods for multi- and hypervariate change detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Canty, Morton J.

2010-01-01

. Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...... formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution......, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...

Kernel based orthogonalization for change detection in hyperspectral images

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... analysis all 126 spectral bands of the HyMap are included. Changes on the ground are most likely due to harvest having taken place between the two acquisitions and solar effects (both solar elevation and azimuth have changed). Both types of kernel analysis emphasize change and unlike kernel PCA, kernel MNF...

Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge; Schuster, Gerard T.

2012-01-01

The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently

Semi-Supervised Kernel PCA

DEFF Research Database (Denmark)

Walder, Christian; Henao, Ricardo; Mørup, Morten

We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least...... squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets....

Adaptive Metric Kernel Regression

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

1998-01-01

Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

21 CFR 176.350 - Tamarind seed kernel powder.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

Aphid-parasitoid community structure on genetically modified wheat.

Science.gov (United States)

von Burg, Simone; van Veen, Frank J F; Álvarez-Alfageme, Fernando; Romeis, Jörg

2011-06-23

Since the introduction of genetically modified (GM) plants, one of the main concerns has been their potential effect on non-target insects. Many studies have looked at GM plant effects on single non-target herbivore species or on simple herbivore-natural enemy food chains. Agro-ecosystems, however, are characterized by numerous insect species which are involved in complex interactions, forming food webs. In this study, we looked at transgenic disease-resistant wheat (Triticum aestivum) and its effect on aphid-parasitoid food webs. We hypothesized that the GM of the wheat lines directly or indirectly affect aphids and that these effects cascade up to change the structure of the associated food webs. Over 2 years, we studied different experimental wheat lines under semi-field conditions. We constructed quantitative food webs to compare their properties on GM lines with the properties on corresponding non-transgenic controls. We found significant effects of the different wheat lines on insect community structure up to the fourth trophic level. However, the observed effects were inconsistent between study years and the variation between wheat varieties was as big as between GM plants and their controls. This suggests that the impact of our powdery mildew-resistant GM wheat plants on food web structure may be negligible and potential ecological effects on non-target insects limited.

Systematic approach in optimizing numerical memory-bound kernels on GPU

KAUST Repository

Abdelfattah, Ahmad

2013-01-01

The use of GPUs has been very beneficial in accelerating dense linear algebra computational kernels (DLA). Many high performance numerical libraries like CUBLAS, MAGMA, and CULA provide BLAS and LAPACK implementations on GPUs as well as hybrid computations involving both, CPUs and GPUs. GPUs usually score better performance than CPUs for compute-bound operations, especially those characterized by a regular data access pattern. This paper highlights a systematic approach for efficiently implementing memory-bound DLA kernels on GPUs, by taking advantage of the underlying device\\'s architecture (e.g., high throughput). This methodology proved to outperform existing state-of-the-art GPU implementations for the symmetric matrix-vector multiplication (SYMV), characterized by an irregular data access pattern, in a recent work (Abdelfattah et. al, VECPAR 2012). We propose to extend this methodology to the general matrix-vector multiplication (GEMV) kernel. The performance results show that our GEMV implementation achieves better performance for relatively small to medium matrix sizes, making it very influential in calculating the Hessenberg and bidiagonal reductions of general matrices (radar applications), which are the first step toward computing eigenvalues and singular values, respectively. Considering small and medium size matrices (≤4500), our GEMV kernel achieves an average 60% improvement in single precision (SP) and an average 25% in double precision (DP) over existing open-source and commercial software solutions. These results improve reduction algorithms for both small and large matrices. The improved GEMV performances engender an averge 30% (SP) and 15% (DP) in Hessenberg reduction and up to 25% (SP) and 14% (DP) improvement for the bidiagonal reduction over the implementation provided by CUBLAS 5.0. © 2013 Springer-Verlag.

Effects of moulds on the safety and processing quality of Triticum aestivum

Directory of Open Access Journals (Sweden)

Šarić Marija D.

2008-01-01

Full Text Available Wheat and wheat products are frequently subjected to mould infestations. Many of them are potential producers of various mycotoxins. Some of the consequences, due to the infestations by genus Fusarium and Alternaria, are mostly: yield loss, decrease of biological and technological quality, and unacceptable quality of infected kernels for the production and processing into human food because of the possible presence of mycotoxins. It is unknown whether and how the contaminated grains are distributed during milling into various flour streams and finished products. Wholegrain flours and related products contain all anatomic parts of kernels, including mycotoxins. It is a known fact that mycotoxins are resistant to thermal degradation, so they do not loose their toxicity during processing. Moulds from genus Fusarium spp. and Alternaria spp. synthesize mycotoxins, mostly zearalenon and ochratoxin A. The aim of the investigation was to examine mould contamination of wheat grain, as well as to identify the isolated species, especially those capable of producing toxins, and to determine their impact on technological quality, safety and sanitary condition of wheat. Six varieties of wheat, contaminated with moulds, were investigated. Each sample was separated manually into four fractions: sound kernels, black germ kernels, kernels infected slightly and those infected severely with Fusarium spp.

Dense Medium Machine Processing Method for Palm Kernel/ Shell ...

African Journals Online (AJOL)

ADOWIE PERE

Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In ... machine processing method using dense medium, a separator, a shell collector and a kernel .... efficiency, ease of maintenance and uniformity of.

A comparative ideotype, yield component and cultivation value analysis for spring wheat adaptation in Finland

Directory of Open Access Journals (Sweden)

Heikki Laurila

2012-12-01

Full Text Available In this study Mixed structural covariance, Path and Cultivation Value analyses and the CERES-Wheat crop model were used to evaluate vegetation and yield component variation affecting yield potential between different high-latitude (> 60° N lat. and mid-European (< 60° N lat. spring wheat (Triticum aestivum L. genotypes currently cultivated in southern Finland. Path modeling results from this study suggest that especially grains/ear, harvest index (HI and maximum 1000 kernel weight were significant factors defining the highest yield potential. Mixed and Cultivation value modeling results suggest that when compared with genotypes introduced for cultivation before 1990s, modern spring wheat genotypes have a significantly higher yielding capacity, current high yielding mid-European genotypes even exceeding the 5 t ha-1 non-potential baseline yield level (yb. Because of a forthcoming climate change, the new high yielding wheat genotypes have to adapt for elevated temperatures and atmospheric CO2 growing conditions in northern latitudes. The optimized ideotype profiles derived from the generic high-latitude and mid-European genotypes are presented in the results. High-latitude and mid-European ideotype profiles with factors estimating the effects of concurrent elevated CO2 and temperature levels with photoperiodical daylength effects can be utilized when designing future high yielding ideotypes adapted to future growing conditions. The CERES-Wheat ideotype modeling results imply, that with new high yielding mid-European ideotypes, the non-potential baseline yield (yb would be on average 5150 kg ha-1 level (+ 108 % vs. new high-latitude ideotypes (yb 4770 kg ha-1, 100% grown under the elevated CO2(700ppm×temperature(+3ºC growing conditions projected by the year 2100 climate change scenario in southern Finland.

High-Throughput Phenotyping of Wheat and Barley Plants Grown in Single or Few Rows in Small Plots Using Active and Passive Spectral Proximal Sensing

OpenAIRE

Barmeier, Gero;Schmidhalter, Urs

2017-01-01

In the early stages of plant breeding, breeders evaluate a large number of varieties. Due to limited availability of seeds and space, plot sizes may range from one to four rows. Spectral proximal sensors can be used in place of labour-intensive methods to estimate specific plant traits. The aim of this study was to test the performance of active and passive sensing to assess single and multiple rows in a breeding nursery. A field trial with single cultivars of winter barley and winter wheat w...

Method: a single nucleotide polymorphism genotyping method for Wheat streak mosaic virus.

Science.gov (United States)

Rogers, Stephanie M; Payton, Mark; Allen, Robert W; Melcher, Ulrich; Carver, Jesse; Fletcher, Jacqueline

2012-05-17

The September 11, 2001 attacks on the World Trade Center and the Pentagon increased the concern about the potential for terrorist attacks on many vulnerable sectors of the US, including agriculture. The concentrated nature of crops, easily obtainable biological agents, and highly detrimental impacts make agroterrorism a potential threat. Although procedures for an effective criminal investigation and attribution following such an attack are available, important enhancements are still needed, one of which is the capability for fine discrimination among pathogen strains. The purpose of this study was to develop a molecular typing assay for use in a forensic investigation, using Wheat streak mosaic virus (WSMV) as a model plant virus. This genotyping technique utilizes single base primer extension to generate a genetic fingerprint. Fifteen single nucleotide polymorphisms (SNPs) within the coat protein and helper component-protease genes were selected as the genetic markers for this assay. Assay optimization and sensitivity testing was conducted using synthetic targets. WSMV strains and field isolates were collected from regions around the world and used to evaluate the assay for discrimination. The assay specificity was tested against a panel of near-neighbors consisting of genetic and environmental near-neighbors. Each WSMV strain or field isolate tested produced a unique SNP fingerprint, with the exception of three isolates collected within the same geographic location that produced indistinguishable fingerprints. The results were consistent among replicates, demonstrating the reproducibility of the assay. No SNP fingerprints were generated from organisms included in the near-neighbor panel, suggesting the assay is specific for WSMV. Using synthetic targets, a complete profile could be generated from as low as 7.15 fmoles of cDNA. The molecular typing method presented is one tool that could be incorporated into the forensic science tool box after a thorough

Multivariate and semiparametric kernel regression

OpenAIRE

Härdle, Wolfgang; Müller, Marlene

1997-01-01

The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

Notes on the gamma kernel

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.

The density function of the gamma distribution is used as shift kernel in Brownian semistationary processes modelling the timewise behaviour of the velocity in turbulent regimes. This report presents exact and asymptotic properties of the second order structure function under such a model......, and relates these to results of von Karmann and Horwath. But first it is shown that the gamma kernel is interpretable as a Green’s function....

Mechanism of Resistance in two Bread Wheat (Triticum Aestivum L.) Lines to Russian Wheat Aphid (Diuraphis Noxia: Homoptra: Aphididae) in Kenya

International Nuclear Information System (INIS)

Malinga, J.N.

2002-01-01

Russian wheat aphid (Diuraphis noxia) is a recent pest of small cereals that is causing severe yield losses in farmers' fields and farmers have demanded a resistant wheat line. In wheat the pest causes both direct and indirect damage resulting in losses of up to 90%. Control of the aphid is a major constraint in the production of wheat in Kenya requiring the use of more than one systematic insecticide application.This cost is prohibitive.Breeding wheat for resistance to Russian wheat is the cheapest alternative and is the international trend. The use of Russian wheat aphid resistant cultivars may reduce the impact of these pest on cereal production. A study was therefore conducted in Kenya to understand and determine the genetics of inheritance pattern of D. noxia present in two new sources of resistance (RWA 8 and RWA 16). These two new sources would be potential donors of D. noxia resistance in breeding programmes. The two resistant donors with unknown resistance genes for Diuraphis noxia were crossed with susceptible Kenyan commercial wheat cultivar, Heroe. Resistant reaction of F 1 ,BC 1 and F2 indicated that resistance in the two lines differed. Resistant in RWA 8 may be controlled by a single dominant genes while RWA 16 by two incomplete dominant genes. It is unknown wether these genes are identical to any known, designated resistance genes. However, their resistance has been shown to be effective on the RWA population in Kenya. As studies continue on these genes at molecular level, it is recommended that resistant populations are carried on through the breeding programme to possibly identify and release a resistant variety for commercial production

Calculation of the thermal neutron scattering kernel using the synthetic model. Pt. 2. Zero-order energy transfer kernel

International Nuclear Information System (INIS)

Drozdowicz, K.

1995-01-01

A comprehensive unified description of the application of Granada's Synthetic Model to the slow-neutron scattering by the molecular systems is continued. Detailed formulae for the zero-order energy transfer kernel are presented basing on the general formalism of the model. An explicit analytical formula for the total scattering cross section as a function of the incident neutron energy is also obtained. Expressions of the free gas model for the zero-order scattering kernel and for total scattering kernel are considered as a sub-case of the Synthetic Model. (author). 10 refs

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn by Measurement of Oil Content.

Directory of Open Access Journals (Sweden)

Hongzhi Wang

Full Text Available One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed.

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn) by Measurement of Oil Content

Science.gov (United States)

Xu, Xiaoping; Huang, Qingming; Chen, Shanshan; Yang, Peiqiang; Chen, Shaojiang; Song, Yiqiao

2016-01-01

One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed. PMID:27454427

Convergence of barycentric coordinates to barycentric kernels

KAUST Repository

Kosinka, Jiří

2016-02-12

We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

Convergence of barycentric coordinates to barycentric kernels

KAUST Repository

Kosinka, Jiří ; Barton, Michael

2016-01-01

We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

Science.gov (United States)

Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

Biological efficiency of component crops in different geometrical patterns of wheat-linseed intercropping

International Nuclear Information System (INIS)

Nazir, M. S.; Saeed, M.; Khan, I.; Ghaffar, A.

2005-01-01

An experiment to determine the biological efficiency and agro-economic relationships of component crops in wheat-linseed intercropping under different geometrical patterns, was conducted on sandy-clay loam soil at Faisalabad (Pakistan). Wheat was sown in 100-cm spaced 4, 6, 8, and 10 row strips and was intercropped with three rows of linseed. The component crops were also grown alone in 30-cm spaced single row. Wheat grain yield was reduced by 25.6%, 19.2%, 14.7% and 11.9% by intercropping linseed in wheat grown in the pattern of 4, 6 and 10-row strips, respectively. However, at the cost of this much reduction in wheat yield, linseed gave an additional yields of 516, 412, 335 kg/ha in the respective patterns which resulted in yield advantages of 41%, 31%, 29% and 27%, respectively over sole cropping of wheat. Intercropping also generated higher net monetary gain/ha (Rs. 12378-12826) than monocropped wheat (Rs. 11034) and linseed (Rs. 4249). (author)

Aflatoxin contamination of developing corn kernels.

Science.gov (United States)

Amer, M A

2005-01-01

Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

Frequency and spectrum of mutations induced by gamma irradiation in single, double and triple dwarf wheats

International Nuclear Information System (INIS)

Dhonukshe, B.L.

1981-01-01

Induced mutation studies were carried with three dwarf wheat varieties viz., ''Sonalika'', ''Chhoti Lerma'' and ''Hira'', considered to be single, double and trible dwarfs, respectively. Gamma-rays were used as a source of irradiation. Frequency of chlorophyll mutations were comparatively low and the spectrum was narrow. Chlorophyll mutations were altogether absent in the variety ''Sonalika''. A very wide spectrum of viable mutations affecting stem, leaf, ear growth habit, maturity and fertility characteristics was observed in the M 2 . The cumulative frequency of all the mutants together was quite high, which varied with the varieties. There were varietal differences in the composition and width of the spectrum induced by gamma-rays. The dwarf mutants having desirable leaf and spike characters were isolated in all the three varieties. (author)

Wheat: The Whole Story.

Science.gov (United States)

Oklahoma State Dept. of Education, Oklahoma City.

This publication presents information on wheat. Wheat was originally a wild grass and not native to the United States. Wheat was not planted there until 1777 (and then only as a hobby crop). Wheat is grown on more acres than any other grain in this country. Soft wheats are grown east of the Mississippi River, and hard wheats are grown west of the…

Kernel Korner : The Linux keyboard driver

NARCIS (Netherlands)

Brouwer, A.E.

1995-01-01

Our Kernel Korner series continues with an article describing the Linux keyboard driver. This article is not for "Kernel Hackers" only--in fact, it will be most useful to those who wish to use their own keyboard to its fullest potential, and those who want to write programs to take advantage of the

The heating of UO_2 kernels in argon gas medium on the physical properties of sintered UO_2 kernels

International Nuclear Information System (INIS)

Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

2015-01-01

The heating of UO_2 kernels in argon gas medium on the physical properties of sinter UO_2 kernels was conducted. The heated of the UO_2 kernels was conducted in a sinter reactor of a bed type. The sample used was the UO_2 kernels resulted from the reduction results at 800 °C temperature for 3 hours that had the density of 8.13 g/cm"3; porosity of 0.26; O/U ratio of 2.05; diameter of 1146 μm and sphericity of 1.05. The sample was put into a sinter reactor, then it was vacuumed by flowing the argon gas at 180 mmHg pressure to drain the air from the reactor. After that, the cooling water and argon gas were continuously flowed with the pressure of 5 mPa with 1.5 liter/minutes velocity. The reactor temperature was increased and variated at 1200-1500 °C temperature and for 1-4 hours. The sinters UO_2 kernels resulted from the study were analyzed in term of their physical properties including the density, porosity, diameter, sphericity, and specific surface area. The density was analyzed using pycnometer with CCl_4 solution. The porosity was determined using Haynes equation. The diameters and sphericity were showed using the Dino-lite microscope. The specific surface area was determined using surface area meter Nova-1000. The obtained products showed the the heating of UO_2 kernel in argon gas medium were influenced on the physical properties of sinters UO_2 kernel. The condition of best relatively at 1400 °C temperature and 2 hours time. The product resulted from the study was relatively at its best when heating was conducted at 1400 °C temperature and 2 hours time, produced sinters UO_2 kernel with density of 10.14 gr/ml; porosity of 7 %; diameters of 893 μm; sphericity of 1.07 and specific surface area of 4.68 m"2/g with solidify shrinkage of 22 %. (author)

Cytogenetic and molecular identification of a wheat-Leymus mollis alien multiple substitution line from octoploid Tritileymus x Triticum durum.

Science.gov (United States)

Pang, Y H; Zhao, J X; Du, W L; Li, Y L; Wang, J; Wang, L M; Wu, J; Cheng, X N; Yang, Q H; Chen, X H

2014-05-23

Leymus mollis (Trin.) Pilger (NsNsXmXm, 2n = 28), a wild relative of common wheat, possesses many traits that are potentially valuable for wheat improvement. In order to exploit and utilize the useful genes of L. mollis, we developed a multiple alien substitution line, 10DM50, from the progenies of octoploid Tritileymus M842-16 x Triticum durum cv. D4286. Genomic in situ hybridization analysis of mitosis and meiosis (metaphase I), using labeled total DNA of Psathyrostachys huashanica as probe, showed that the substitution line 10DM50 was a cytogenetically stable alien substitution line with 36 chromosomes from wheat and three pairs of Ns genome chromosomes from L. mollis. Simple sequence repeat analysis showed that the chromosomes 3D, 6D, and 7D were absent in 10DM50. Expressed sequence tag-sequence tagged sites analysis showed that new chromatin from 3Ns, 6Ns, and 7Ns of L. mollis were detected in 10DM50. We deduced that the substitution line 10DM50 was a multiple alien substitution line with the 3D, 6D, and 7D chromosomes replaced by 3Ns, 6Ns, and 7Ns from L. mollis. 10DM50 showed high resistance to leaf rust and significantly improved spike length, spikes per plant, and kernels per spike, which are correlated with higher wheat yield. These results suggest that line 10DM50 could be used as intermediate material for transferring desirable traits from L. mollis into common wheat in breeding programs.

Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge

2012-01-01

The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

Trichothecene chemotype diversity of Fusarium graminearum isolated from wheat, maize and barley in Serbia

Directory of Open Access Journals (Sweden)

Obradović Ana

2017-01-01

Full Text Available Diversity of trichothecene chemotypes of Fusarium graminearum isolated from kernels of wheat, barley and maize grown under various agro-ecological conditions on 13 locations was analysed. Sixteen strains were tested for the effective capability to produce 15-ADON, 3-ADON and NIV, by using the liquid chromatography-tandem mass spectrometry (LC-MS/MS system. Fourteen out of sixteen analyzed strains produced 15-ADON, while remaining two were of the 3-ADON chemotype. Multiplex PCR reaction with two sets of specific primers for TRI3 and TRI12 genes was applied to identify trichothecene chemotypes (3-ADON, 15-ADON and NIV. The expected sizes of amplified fragments for TRI3 gene primer set are 840 bp (NIV, 610 bp (15-ADON and 243 bp (3-ADON. The amplified fragments for TRI12 gene primer set should be 840 bp (NIV, 670 bp (15-ADON and 410 bp (3-ADON. All F. graminearum isolates were of the 15-ADON chemotype, i.e. their bands were 610 bp and 670 bp size for TRI3 and TRI12 genes, respectively. The results indicate that genotypic characterisation does not correspond to determined chemotypes and this is a reason why the analyses for the risk of mycotoxins contamination should not be based only on trichotecene genotype determination. Due to high temperature differences in cereal growing regions in Serbia, the presence of other chemotypes could be expected. In order to determine whether besides 15-ADON there are other F. graminearum chemotypes on wheat, barley and maize kernels, further studies should include a large number of isolates from different agro-ecological conditions. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR31023

Realized kernels in practice

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger

2009-01-01

and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...

Anatomically-aided PET reconstruction using the kernel method.

Science.gov (United States)

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2016-09-21

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Embedded real-time operating system micro kernel design

Science.gov (United States)

Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

2005-12-01

Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

Kernel Temporal Differences for Neural Decoding

Science.gov (United States)

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

Collision kernels in the eikonal approximation for Lennard-Jones interaction potential

International Nuclear Information System (INIS)

Zielinska, S.

1985-03-01

The velocity changing collisions are conveniently described by collisional kernels. These kernels depend on an interaction potential and there is a necessity for evaluating them for realistic interatomic potentials. Using the collision kernels, we are able to investigate the redistribution of atomic population's caused by the laser light and velocity changing collisions. In this paper we present the method of evaluating the collision kernels in the eikonal approximation. We discuss the influence of the potential parameters Rsub(o)sup(i), epsilonsub(o)sup(i) on kernel width for a given atomic state. It turns out that unlike the collision kernel for the hard sphere model of scattering the Lennard-Jones kernel is not so sensitive to changes of Rsub(o)sup(i) as the previous one. Contrary to the general tendency of approximating collisional kernels by the Gaussian curve, kernels for the Lennard-Jones potential do not exhibit such a behaviour. (author)

Classification of maize kernels using NIR hyperspectral imaging

DEFF Research Database (Denmark)

Williams, Paul; Kucheryavskiy, Sergey V.

2016-01-01

NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

Mutation induction in durum wheat

International Nuclear Information System (INIS)

Senay, A.; Sekerci, S.

2009-01-01

The aim of this research was to determine the separate and combine effects of different doses of gamma rays and EMS concentrations on some characteristics of M1 plants of durum wheat, cv. Kunduru 1149. The seeds of durum wheat, cv. Kunduru 1149 which were irradiated with 50 Gy, 150 Gy and 250 Gy gamma rays and/or treated EMS for 6 hours at 30 C in 0,2 % and 0,4 % concentrated. According to the results of this research; separate and combine treatments of different doses of gamma rays and EMS have shown significant difference all of the observed traits at M1 plants of durum wheat cv. Kunduru 1149. The negative effects of increasing doses of mutagens on all plant characteristics for M1 plants were found statistically significant. Combined treatments were found to be more efficient than the sum of effects of the single treatments. In followed generation 3 mutant lines were selected according to plant height, spike height, number of seed, leaf relative water lost, and some quality traits. In M6 generation 3 desirable lines have been sown for preliminary field yield tests.

Evolution kernel for the Dirac field

International Nuclear Information System (INIS)

Baaquie, B.E.

1982-06-01

The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)

Gradient-based adaptation of general gaussian kernels.

Science.gov (United States)

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

The pangenome of hexaploid bread wheat

Czech Academy of Sciences Publication Activity Database

Montenegro, J. D.; Golicz, A. A.; Bayer, P.E.; Hurgobin, B.; Lee, H. T.; Chan, C. K. K.; Visendi, P.; Lai, K.; Doležel, Jaroslav; Batley, J.; Edwards, D.

2017-01-01

Roč. 90, č. 5 (2017), s. 1007-1013 ISSN 0960-7412 R&D Projects: GA MŠk(CZ) LO1204 Institutional support: RVO:61389030 Keywords : database * diversity * genome * pangenome * single nucleotide polymorphisms * Triticum aestivum * wheat Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Plant sciences, botany Impact factor: 5.901, year: 2016

Improved wheat for baking.

Science.gov (United States)

Faridi, H; Finley, J W

1989-01-01

To bakers, wheat quality means the performance characteristics of the flour milled from the wheat when used in specific wheat products. The tremendous increase in the number of wheat cultivars grown in the U.S. in recent years, along with the unusual climate, new advances in milling technology, and increased automation of baking lines, have resulted in bakery production problems partly attributed to wheat flour quality. In this review various factors affecting wheat quality are explained. Concerns of bread and cookie/cracker manufacturers on deterioration of the wheat quality are discussed, and, finally, some solutions are proposed.

Open Problem: Kernel methods on manifolds and metric spaces

DEFF Research Database (Denmark)

Feragen, Aasa; Hauberg, Søren

2016-01-01

Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....

Kernel-based noise filtering of neutron detector signals

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

2007-01-01

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

Science.gov (United States)

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...

African Journals Online (AJOL)

Estimated error of ± 0.18 and ± 0.2 are envisaged while applying the models for predicting palm kernel and sesame oil colours respectively. Keywords: Palm kernel, Sesame, Palm kernel, Oil Colour, Process Parameters, Model. Journal of Applied Science, Engineering and Technology Vol. 6 (1) 2006 pp. 34-38 ...

Heat kernel analysis for Bessel operators on symmetric cones

DEFF Research Database (Denmark)

Möllers, Jan

2014-01-01

. The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...

A multi-scale kernel bundle for LDDMM

DEFF Research Database (Denmark)

Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard

2011-01-01

The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...

The effect of high concentrations of glufosinate ammonium on the yield components of transgenic spring wheat (Triticum aestivum L.) constitutively expressing the bar gene.

Science.gov (United States)

Áy, Zoltán; Mihály, Róbert; Cserháti, Mátyás; Kótai, Éva; Pauk, János

2012-01-01

We present an experiment done on a bar(+) wheat line treated with 14 different concentrations of glufosinate ammonium-an effective component of nonselective herbicides-during seed germination in a closed experimental system. Yield components as number of spikes per plant, number of grains per spike, thousand kernel weight, and yield per plant were thoroughly analysed and statistically evaluated after harvesting. We found that a concentration of glufosinate ammonium 5000 times the lethal dose was not enough to inhibit the germination of transgenic plants expressing the bar gene. Extremely high concentrations of glufosinate ammonium caused a bushy phenotype, significantly lower numbers of grains per spike, and thousand kernel weights. Concerning the productivity, we observed that concentrations of glufosinate ammonium 64 times the lethal dose did not lead to yield depression. Our results draw attention to the possibilities implied in the transgenic approaches.

Training Lp norm multiple kernel learning in the primal.

Science.gov (United States)

Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

2013-10-01

Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

Science.gov (United States)

Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

2018-02-13

Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Stochastic subset selection for learning with kernel machines.

Science.gov (United States)

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Determination of Zinc in Wheat and Wheat Bran by Neutron Activation Analysis

International Nuclear Information System (INIS)

Ghazi Zahedi, M.; Bahrami Samani, A.; Sedaghati Zadeh, M.; Ghannadi Maragheh, M.

2012-01-01

The knowledge of concentration of elements in foodstuffs is of significant interest. Wheat is one of the most consumed food stuffs in Iran and zinc is also considered as one of the necessary and vital elements. Since the measurement of some trace elements is not practical by the conventional analytical methods, due to the lower detection limit, the neutron activation analysis was applied to determine the zinc in wheat and wheat bran. Food sample of roughly 50 mg was irradiated for 24 hours. After cooling, the interval samples were counted by a gamma spectrometry system. The concentration of zinc in wheat without bran and the wheat bran were 18.444±0.656 and 19.927±0.698 ppm, respectively. The amount of zinc in wheat bran was noticeable so it showed that consuming wheat with bran is more beneficial than the wheat with no bran for the human-beings body requirements.

Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

Science.gov (United States)

Skakun, S.; Franch, B.; Roger, J.-C.; Vermote, E.; Becker-Reshef, I.; Justice, C.; Santamaría-Artigas, A.

2016-01-01

Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

RTOS kernel in portable electrocardiograph

Science.gov (United States)

Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.

2011-12-01

This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

RTOS kernel in portable electrocardiograph

International Nuclear Information System (INIS)

Centeno, C A; Voos, J A; Riva, G G; Zerbini, C; Gonzalez, E A

2011-01-01

This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

RKRD: Runtime Kernel Rootkit Detection

Science.gov (United States)

Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.

In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.

Denoising by semi-supervised kernel PCA preimaging

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

2014-01-01

Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...

Sentiment classification with interpolated information diffusion kernels

NARCIS (Netherlands)

Raaijmakers, S.

2007-01-01

Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of

Laboratory, greenhouse and field methods for screening rust-resistant wheat cultivars

International Nuclear Information System (INIS)

Mashaal, S.F.; Kiraly, Z.; Barabas, Z.; Barna, B.; Cereal Research Inst., Szeged, Hungary)

1977-01-01

Detached flag leaf cultures were not suitable for evaluation of stem-rust resistance in our screening programme. On the basis of yield evaluation it was possible to screen out ten stem-rust ''tolerant'' wheat lines in field experiments. Rusted and protected microplots of each line were paired within a replicate. After artificial inoculation, the protected plants were sprayed with fungicides (benomyl plus dithiocarbamate plus copper salt) at weekly intervals until maturation to keep each protected plot rust-free. The thousand-kernel weights of rusted and protected plots were compared. When the thousand-kernel weight of protected plot increased only slightly and the rust reaction type of plants was susceptible in the rusted plot, the line was screened out as putative ''tolerant''. On the basis of three-year field trial ten ''tolerant'' lines were selected. Nine out of ten lines proved to be resistant to two stem-rust races in greenhouse tests in the seedling stage, when resistance was determined on the basis of reduced spore production instead of infection types. Resistance of these seedlings related partly to the reduced number of pustules and partly to a slow rusting character of plants. It seems possible to screen resistant cultivars in the greenhouse by the method outlined in this paper, when resistance is determined on the basis of a reduced number of infection sites and/or by the slow rusting capacity. (author)

Linear and kernel methods for multivariate change detection

DEFF Research Database (Denmark)

Canty, Morton J.; Nielsen, Allan Aasbjerg

2012-01-01

), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...

Panel data specifications in nonparametric kernel regression

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

Scuba: scalable kernel-based gene prioritization.

Science.gov (United States)

Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

2018-01-25

The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

MULTITASKER, Multitasking Kernel for C and FORTRAN Under UNIX

International Nuclear Information System (INIS)

Brooks, E.D. III

1988-01-01

1 - Description of program or function: MULTITASKER implements a multitasking kernel for the C and FORTRAN programming languages that runs under UNIX. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the development, debugging, and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessor hardware. The performance evaluation features require no changes in the application program source and are implemented as a set of compile- and run-time options in the kernel. 2 - Method of solution: The FORTRAN interface to the kernel is identical in function to the CRI multitasking package provided for the Cray XMP. This provides a migration path to high speed (but small N) multiprocessors once the application has been coded and debugged. With use of the UNIX m4 macro preprocessor, source compatibility can be achieved between the UNIX code development system and the target Cray multiprocessor. The kernel also provides a means of evaluating a program's performance on model multiprocessors. Execution traces may be obtained which allow the user to determine kernel overhead, memory conflicts between various tasks, and the average concurrency being exploited. The kernel may also be made to switch tasks every cpu instruction with a random execution ordering. This allows the user to look for unprotected critical regions in the program. These features, implemented as a set of compile- and run-time options, cause extra execution overhead which is not present in the standard production version of the kernel

Variations in grain lipophilic phytochemicals, proteins and resistance to Fusarium spp. growth during grain storage as affected by biological plant protection with Aureobasidium pullulans (de Bary).

Science.gov (United States)

Wachowska, Urszula; Tańska, Małgorzata; Konopka, Iwona

2016-06-16

Modern agriculture relies on an integrated approach, where chemical treatment is reduced to a minimum and replaced by biological control that involves the use of active microorganisms. The effect of the antagonistic yeast-like fungus Aureobasidium pullulans on proteins and bioactive compounds (alkylresorcinols, sterols, tocols and carotenoids) in winter wheat grain and on the colonization of wheat kernels by fungal microbiota, mainly Fusarium spp. pathogens, was investigated. Biological treatment contributed to a slight increase contents of tocols, alkylresorcinols and sterols in grain. At the same time, the variation of wheat grain proteins was low and not significant. Application of A. pullulans enhanced the natural yeast colonization after six months of grain storage and inhibited growth of F. culmorum pathogens penetrating wheat kernel. This study demonstrated that an integrated approach of wheat grain protection with the use of the yeast-like fungus A. pullulans reduced kernel colonization by Fusarium spp. pathogens and increased the content of nutritionally beneficial phytochemicals in wheat grain without a loss of gluten proteins responsible for baking value. Copyright © 2016. Published by Elsevier B.V.

Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

International Nuclear Information System (INIS)

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays

Generation of amphidiploids from hybrids of wheat and related species from the genera Aegilops, Secale, Thinopyrum, and Triticum as a source of genetic variation for wheat improvement.

Science.gov (United States)

Nemeth, Csilla; Yang, Cai-yun; Kasprzak, Paul; Hubbart, Stella; Scholefield, Duncan; Mehra, Surbhi; Skipper, Emma; King, Ian; King, Julie

2015-02-01

We aim to improve diversity of domesticated wheat by transferring genetic variation for important target traits from related wild and cultivated grass species. The present study describes the development of F1 hybrids between wheat and related species from the genera Aegilops, Secale, Thinopyrum, and Triticum and production of new amphidiploids. Amphidiploid lines were produced from 20 different distant relatives. Both colchicine and caffeine were successfully used to double the chromosome numbers. The genomic constitution of the newly formed amphidiploids derived from seven distant relatives was determined using genomic in situ hybridization (GISH). Altogether, 42 different plants were analysed, 19 using multicolour GISH separating the chromosomes from the A, B, and D genomes of wheat, as well as the distant relative, and 23 using single colour GISH. Restructuring of the allopolyploid genome, both chromosome losses and aneuploidy, was detected in all the genomes contained by the amphidiploids. From the observed chromosome numbers there is an indication that in amphidiploids the B genome of wheat suffers chromosome losses less frequently than the other wheat genomes. Phenotyping to realize the full potential of the wheat-related grass germplasm is underway, linking the analyzed genotypes to agronomically important target traits.

Method: a single nucleotide polymorphism genotyping method for Wheat streak mosaic virus

Science.gov (United States)

2012-01-01

Background The September 11, 2001 attacks on the World Trade Center and the Pentagon increased the concern about the potential for terrorist attacks on many vulnerable sectors of the US, including agriculture. The concentrated nature of crops, easily obtainable biological agents, and highly detrimental impacts make agroterrorism a potential threat. Although procedures for an effective criminal investigation and attribution following such an attack are available, important enhancements are still needed, one of which is the capability for fine discrimination among pathogen strains. The purpose of this study was to develop a molecular typing assay for use in a forensic investigation, using Wheat streak mosaic virus (WSMV) as a model plant virus. Method This genotyping technique utilizes single base primer extension to generate a genetic fingerprint. Fifteen single nucleotide polymorphisms (SNPs) within the coat protein and helper component-protease genes were selected as the genetic markers for this assay. Assay optimization and sensitivity testing was conducted using synthetic targets. WSMV strains and field isolates were collected from regions around the world and used to evaluate the assay for discrimination. The assay specificity was tested against a panel of near-neighbors consisting of genetic and environmental near-neighbors. Result Each WSMV strain or field isolate tested produced a unique SNP fingerprint, with the exception of three isolates collected within the same geographic location that produced indistinguishable fingerprints. The results were consistent among replicates, demonstrating the reproducibility of the assay. No SNP fingerprints were generated from organisms included in the near-neighbor panel, suggesting the assay is specific for WSMV. Using synthetic targets, a complete profile could be generated from as low as 7.15 fmoles of cDNA. Conclusion The molecular typing method presented is one tool that could be incorporated into the forensic

Performance and Emission of VCR-CI Engine with palm kernel and eucalyptus blends

Directory of Open Access Journals (Sweden)

Srinivas kommana

2016-09-01

Full Text Available This study aims at complete replacement of conventional diesel fuel by biodiesel. In order to achieve that, palm kernel oil and eucalyptus oil blend has been chosen. Eucalyptus oil was blended with methyl ester of palm kernel oil in 5%, 10% and 15% by volume. Tests were conducted with diesel fuel and blends on a 4 stroke VCR diesel engine for comparative analysis with 220 bar injection pressure and 19:1 compression ratio. All the test fuels were used in computerized 4 stroke single cylinder variable compression ratio engine at five different loads (0, 6, 12, 18 and 24 N m. Present investigation depicts the improved combustion and reduced emissions for the PKO85% + EuO15% blend when compared to diesel at full load conditions.

The integral first collision kernel method for gamma-ray skyshine analysis[Skyshine; Gamma-ray; First collision kernel; Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Sheu, R.-D.; Chui, C.-S.; Jiang, S.-H. E-mail: shjiang@mx.nthu.edu.tw

2003-12-01

A simplified method, based on the integral of the first collision kernel, is presented for performing gamma-ray skyshine calculations for the collimated sources. The first collision kernels were calculated in air for a reference air density by use of the EGS4 Monte Carlo code. These kernels can be applied to other air densities by applying density corrections. The integral first collision kernel (IFCK) method has been used to calculate two of the ANSI/ANS skyshine benchmark problems and the results were compared with a number of other commonly used codes. Our results were generally in good agreement with others but only spend a small fraction of the computation time required by the Monte Carlo calculations. The scheme of the IFCK method for dealing with lots of source collimation geometry is also presented in this study.

Prehaustorial and posthaustorial resistance to wheat leaf rust in diploid wheat

NARCIS (Netherlands)

Anker, C.C.

2001-01-01

In modern wheat cultivars, resistance to wheat leaf rust, Puccinia triticina , is either based on hypersensitivity resistance or on partial resistance. Hypersensitivity resistance in wheat is monogenic, often complete and posthaustorial: it is induced after the

Evaluation of Spring Wheat Recombinant Inbred Lines under Drought Stress

Directory of Open Access Journals (Sweden)

M. Moghaddaszadeh-Ahrabi

2012-07-01

Full Text Available Iran is one of arid and semi-arid regions of the world. Wheat as a strategic agricultural products faces water deficiency in most areas of the country. Therefore, identification of the resistant varieties to drought stress is one of main aims for breeders. To assess effect of drought stress at heading on 72 spring wheat recombinant inbred lines derived from American Yecora Rojo (high yielder, dwarf and early maturity as paternal parent and Iranian No. 49 line (tall and late maturiting as maternal parent cross were studied. The experiment was conducted at the Research Station of the University of Tabriz using a randomized complete block design with two replications during 2009 growing season. Based on the results from combined analysis of variance significant difference was observed among lines for all of traits studied, except for harvest index, grain number per spike and days to heading. There was significant difference between normal and drought stress conditions. Since the interaction between line and conditions was insignificant for all traits, it does therefore, provide the possibility of comparing the lines without regard to irrigation levels. Based on the means of, the traits it was found that the lines 96, 122, 123 and 155 were superior. MP, GMP and STI indices were recognized to be suitable indices to identify superior lines. With respect to these indices, lines 96, 122, 123, 138, 149 and 155 were found superior as compared with remaining lines. Based on stepwise regression analysis of grain yield with other traits, respectively grain number per spike, number of spikes/m2 and 1000 kernel weight were inserted into final model as effective variables on grain yield, which made 81/9 percent of the grain yield variation. Path analysis of grain yield and related traits, based on stepwise regression, demonstrated the significant positive direct effect for grain number per spike, number of spikes/m2 and 1000 kernel weight on grain yield

Landslide Susceptibility Mapping Based on Particle Swarm Optimization of Multiple Kernel Relevance Vector Machines: Case of a Low Hill Area in Sichuan Province, China

Directory of Open Access Journals (Sweden)

Yongliang Lin

2016-10-01

Full Text Available In this paper, we propose a multiple kernel relevance vector machine (RVM method based on the adaptive cloud particle swarm optimization (PSO algorithm to map landslide susceptibility in the low hill area of Sichuan Province, China. In the multi-kernel structure, the kernel selection problem can be solved by adjusting the kernel weight, which determines the single kernel contribution of the final kernel mapping. The weights and parameters of the multi-kernel function were optimized using the PSO algorithm. In addition, the convergence speed of the PSO algorithm was increased using cloud theory. To ensure the stability of the prediction model, the result of a five-fold cross-validation method was used as the fitness of the PSO algorithm. To verify the results, receiver operating characteristic curves (ROC and landslide dot density (LDD were used. The results show that the model that used a heterogeneous kernel (a combination of two different kernel functions had a larger area under the ROC curve (0.7616 and a lower prediction error ratio (0.28% than did the other types of kernel models employed in this study. In addition, both the sum of two high susceptibility zone LDDs (6.71/100 km2 and the sum of two low susceptibility zone LDDs (0.82/100 km2 demonstrated that the landslide susceptibility map based on the heterogeneous kernel model was closest to the historical landslide distribution. In conclusion, the results obtained in this study can provide very useful information for disaster prevention and land-use planning in the study area.

A kernel adaptive algorithm for quaternion-valued inputs.

Science.gov (United States)

Paul, Thomas K; Ogunfunmi, Tokunbo

2015-10-01

The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.

Improving the Bandwidth Selection in Kernel Equating

Science.gov (United States)

Andersson, Björn; von Davier, Alina A.

2014-01-01

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

Investigation of seed damaging pathogens associated with wheat crop in bhimber azad kashmir, pakistan and their managements

International Nuclear Information System (INIS)

Hussain, T.; Ishtiaq, M.; Azam, S.; Maqbool, M.; Mushtaq, W.

2017-01-01

Mycopathogens were explored from wheat germplasm cultivars from District Bhimber of Azad Kashmir. In this study, 10 different seed-borne pathogens were isolated from District of Bhimber, Azad Jammu and Kashmir, Pakistan. The Agar Plate Method (APM) and Towel Paper Method (TPM) were used for detection of seed borne pathogens. The disease incidence (percentage) and disease severity of fungi varied with respect to type of pathogen and seed sampling sites. Kernel bunt caused by Tilletia indica showed highest incidence (67.25%) and severity (7.0) on 0-9 rating scale. Fusarium graminearum showed the highest infection rate in three sub-divisions of district Bhimber as compared to others. The fungal attacking pathogens on wheat crop were control through fungicides treatment and treatments with plant extracts. Maximum germination rates were calculated in three sub-divisions of Bhimber after treatment of Tilt fungicide. As 86% germination rate in Samahni, 87.5% in Bhimber and 84.5% in Bernala was calculated. Antifungal activity of five plant extracts (Acacia nilotica L., Azadirachta indica L. Juss., Eucalyptus citriodora Hook, Ficus bengalensis L. and Allium sativum L.) were evaluated in four different solvents. Highest minimum inhibitory concentration (MIC) was calculated of all plants in methanolic extracts. Maximum MIC (57.38 mcg/ml) exhibited by extracts of Acacia nilotica leaves against ten fungi. Azadirachta indica extracts in different solvents against wheat-seed fungal pathogens was shown more antimicrobial activity as compared to other four plants. Azadirachta indica extract in methanol showed the highest mean of antifungal activity (62.20 mcg/ml) against ten different fungal pathogens. Antimicrobial activity (MIC) of Ficus bengalensis in different solvents against nine wheat-seed fungal pathogens was also investigated. Highest MIC was measured against B. graminis (57.50 mcg/ml) and S. macrospora (57.00 mcg/ml) by using methanolic extract of Ficus bengalensis

Online learning control using adaptive critic designs with sparse kernel machines.

Science.gov (United States)

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Starch facilitates enzymatic wheat gluten hydrolysis

NARCIS (Netherlands)

Hardt, N.A.; Boom, R.M.; Goot, van der A.J.

2015-01-01

Wheat gluten can be hydrolyzed by either using (vital) wheat gluten or directly from wheat flour. This study investigates the influence of the presence of starch, the main component of wheat, on enzymatic wheat gluten hydrolysis. Wheat gluten present in wheat flour (WFG) and vital wheat gluten (VWG)

Analysis of deoxynivalenol and deoxynivalenol-3-glucosides content in Canadian spring wheat cultivars inoculated with Fusarium graminearum.

Science.gov (United States)

Amarasinghe, Chami C; Simsek, Senay; Brûlé-Babel, Anita; Fernando, W G Dilantha

2016-07-01

Contamination of wheat grains with Fusarium mycotoxins and their modified forms is an important issue in wheat industry. The objective of this study was to analyse the deoxynivalenol (DON) and deoxynivalenol-3-glucosides (D3G) content in Canadian spring wheat cultivars grown in two locations, inoculated with a mixture of 3-acetyldeoxynivalenol (3-ADON)-producing Fusarium graminearum strains and a mixture of 15-acetlyldeoxynivalenol (15-ADON)-producing F. graminearum strains. According to the analysis of variance, significant differences were observed among the cultivars for Fusarium head blight (FHB) disease index, Fusarium-damaged kernel percentage (%FDK), DON content and D3G content. When the effect of chemotype was considered, significant differences were observed for FHB disease index, FDK percentage and DON content. The D3G content and D3G/DON ratio were not significantly different between the chemotypes, except for D3G content at the Winnipeg location. The Pearson correlation coefficient between DON and D3G was 0.84 and 0.77 at Winnipeg and Carman respectively. The highest D3G/DON ratio was observed in cultivars Carberry (44%) in Carman and CDC Kernen (63.8%) in Winnipeg. The susceptible cultivars showed lower D3G/DON ratio compared with the cultivars rated as moderately resistant and intermediate. The current study indicated that Canadian spring cultivars produce D3G upon Fusarium infection.

A multi-label learning based kernel automatic recommendation method for support vector machine.

Science.gov (United States)

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

Effects of climate change, CO2 and O3 on wheat productivity in Eastern China, singly and in combination

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Tao, Fulu; Feng, Zhaozhong; Tang, Haoye; Chen, Yi; Kobayashi, Kazuhiko

2017-03-01

Air pollution and climate change are increasing threats to agricultural production and food security. Extensive studies have focused on the effect of climate change, but the interactive effects of multiple global change factors are poorly understood. Here, we incorporate the interactions between climate change, carbon dioxide (CO2) and ozone (O3) into an eco-physiological mechanistic model based on three years of O3 Free-Air Concentration Elevation (O3-FACE) experiments. We then investigate the effects of climate change, elevated CO2 concentration ([CO2]) and rising O3 concentration ([O3]) on wheat growth and productivity in eastern China in 1996-2005 (2000s) and 2016-2025 (2020s) under two climate change scenarios, singly and in combination. We find the interactive effects of climate change, CO2 and O3 on wheat productivity have spatially explicit patterns; the effect of climate change dominates the general pattern, which is however subject to the large uncertainties of climate change scenarios. Wheat productivity is estimated to increase by 2.8-9.0% due to elevated [CO2] however decline by 2.8-11.7% due to rising [O3] in the 2020s, relative to the 2000s. The combined effects of CO2 and O3 are less than that of O3 only, on average by 4.6-5.2%, however with O3 damage outweighing CO2 benefit in most of the region. This study demonstrates a more biologically meaningful and appropriate approach for assessing the interactive effects of climate change, CO2 and O3 on crop growth and productivity. Our findings promote the understanding on the interactive effects of multiple global change factors across contrasting climate conditions, cast doubt on the potential of CO2 fertilization effect in offsetting possible negative effect of climate change on crop productivity as suggested by many previous studies.

Using the Intel Math Kernel Library on Peregrine | High-Performance

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Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

Discovery of Consistent QTLs of Wheat Spike-Related Traits under Nitrogen Treatment at Different Development Stages

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Zhiying Deng

2017-12-01

Full Text Available Spike-related traits such as spike length (Sl, fertile spikelet number (Fsn, sterile spikelet number (Ssn, grain number per spike (Gns, and thousand-kernel weight (Tkw are important factors influencing wheat yield. However, reliably stable markers that can be used for molecular breeding in different environments have not yet been identified. In this study, a double haploid (DH population was used for quantitative trait locus (QTL mapping of five spike-related traits under four different nitrogen (N supply dates in two locations and years. Seventy additive QTLs with phenotypic variation ranging from 4.12 to 34.74% and 10 major epistatic QTLs were identified. Eight important chromosomal regions on five chromosomes (1B, 2B, 2D, 5D, and 6A were found. Sixteen stable QTLs were detected for which N application had little effect. Among those stable QTLs, QSl.sdau-2D-1, and QSl.sdau-2D-2, with phenotypic variation explained (PVE of 10.4 and 24.2%, respectively, were flanked by markers Xwmc112 and Xcfd53 in the same order. The QTLs QSsn.sdau-2B-1, QFsn.sdau-2B-1, and QGns.sdau-2B, with PVE ranging from 4.37 to 28.43%, collocated in the Xwmc179-Xbarc373 marker interval. The consistent kernel wheat QTL (QTkw.sdau-6A on the long arm of chromosome 6A, flanked by SSR markers Xbarc1055 and Xwmc553, showed PVE of 5.87–15.18%. Among these stable QTLs, the two flanking markers Xwmc112 and Xcfd53 have been validated using different varieties and populations for selecting Sl. Therefore, these results will be of great value for marker-assisted selection (MAS in breeding programs and will accelerate the understanding of the genetic relationships among spike-related traits at the molecular level.

Discovery of Consistent QTLs of Wheat Spike-Related Traits under Nitrogen Treatment at Different Development Stages.

Science.gov (United States)

Deng, Zhiying; Cui, Yong; Han, Qingdian; Fang, Wenqi; Li, Jifa; Tian, Jichun

2017-01-01

Spike-related traits such as spike length (Sl), fertile spikelet number (Fsn), sterile spikelet number (Ssn), grain number per spike (Gns), and thousand-kernel weight (Tkw) are important factors influencing wheat yield. However, reliably stable markers that can be used for molecular breeding in different environments have not yet been identified. In this study, a double haploid (DH) population was used for quantitative trait locus (QTL) mapping of five spike-related traits under four different nitrogen (N) supply dates in two locations and years. Seventy additive QTLs with phenotypic variation ranging from 4.12 to 34.74% and 10 major epistatic QTLs were identified. Eight important chromosomal regions on five chromosomes (1B, 2B, 2D, 5D, and 6A) were found. Sixteen stable QTLs were detected for which N application had little effect. Among those stable QTLs, QSl.sdau-2D-1 , and QSl.sdau-2D-2 , with phenotypic variation explained (PVE) of 10.4 and 24.2%, respectively, were flanked by markers Xwmc112 and Xcfd53 in the same order. The QTLs QSsn.sdau-2B-1, QFsn.sdau-2B-1 , and QGns.sdau-2B , with PVE ranging from 4.37 to 28.43%, collocated in the Xwmc179 - Xbarc373 marker interval. The consistent kernel wheat QTL ( QTkw.sdau-6A ) on the long arm of chromosome 6A, flanked by SSR markers Xbarc1055 and Xwmc553 , showed PVE of 5.87-15.18%. Among these stable QTLs, the two flanking markers Xwmc112 and Xcfd53 have been validated using different varieties and populations for selecting Sl. Therefore, these results will be of great value for marker-assisted selection (MAS) in breeding programs and will accelerate the understanding of the genetic relationships among spike-related traits at the molecular level.

Relationship between grain colour and preharvest sprouting-resistance in wheat.

OpenAIRE

BASSOI, M.C.; FLINTHAM, J.

2006-01-01

Since red alleles (R) of the genes that control grain colour are important for the improvement of preharvest sprouting resistance in wheat and there are three independently inherited loci, on chromosomes 3A, 3B and 3D of hexaploid wheat, it is possible to vary the dosage of dominant alleles in a breeding program. The objective of this work was to evaluate the dosage effect of R genes on preharvest sprouting, in a single seed descent population, named TRL, derived from the cross between Timgal...