scholarly journals Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

2018 ◽  
Author(s):  
Margaret R. Krause ◽  
Lorena González-Pérez ◽  
José Crossa ◽  
Paulino Pérez-Rodríguez ◽  
Osval Montesinos-López ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genomic Selection ◽  
Bread Wheat ◽  
Pedigree Information ◽  
Hyperspectral Reflectance ◽  
Improvement Program ◽  
Selection Models ◽  
Wheat Improvement ◽  
Wide Range ◽  
Kernel Models

ABSTRACTHyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and biochemical processes in plants. Genomic selection models utilize genome-wide marker or pedigree information to predict the genetic values of breeding lines. In this study, we propose a multi-kernel GBLUP approach to genomic selection that uses genomic marker-, pedigree-, and hyperspectral reflectance-derived relationship matrices to model the genetic main effects and genotype × environment (G × E) interactions across environments within a bread wheat (Triticum aestivum L.) breeding program. We utilized an airplane equipped with a hyperspectral camera to phenotype five differentially managed treatments of the yield trials conducted by the Bread Wheat Improvement Program, International Maize and Wheat Improvement Center (CIMMYT) at Ciudad Obregón, México over four breeding cycles. We observed that single-kernel models using hyperspectral reflectance-derived relationship matrices performed similarly or superior to marker-and pedigree-based genomic selection models when predicting within and across environments. Multi-kernel models combining marker/pedigree information with hyperspectral reflectance phentoypes had the highest prediction accuracies; however, improvements in accuracy over marker-and pedigree-based models were marginal when correcting for days to heading. Our results demonstrates the potential of hyperspectral imaging in predicting grain yield within a multi-environment context, it also supports further studies on integration of hyperspectral reflectance phenotyping in breeding programs.

scholarly journals Expected genetic gains from mono trait and indexbased selection in advanced bread wheat (Triticum aestivum L.) populations

2020 ◽  
Vol 73 (2) ◽  
pp. 9131-9141
Author(s):  
Zine El Abidine Fellahi ◽  
Abderrahmane Hannachi ◽  
Hamenna Bouzerzour
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Flag Leaf ◽  
Block Design ◽  
Triticum Aestivum L ◽  
Research Unit ◽  
Kernel Weight ◽  
Wide Range ◽  
Wheat Lines ◽  
Selection Of

This study aimed at evaluating the expected gains from selection obtained based upon direct, indirect, and index-based selection in a set of 599 bread wheat lines. The experiment was carried out at the experimental field of INRAA institute, Setif research unit (Algeria), in a Federer augmented block design including three controls. A wide range of genetic variability was observed among lines for the eleven traits assessed. The results indicated that index-based selection and selection based on grain yield expressed higher expected genetic gain than direct and indirect mono-trait-based selection. The best 15 selected lines exhibited higher grain yield than the control varieties, and they were clustered in three groups that contrasted mainly for the flag-leaf area, thousand-kernel weight, biomass, and harvest index. The index-based selection appears as a useful tool for the rapid selection of early filial generations, enriching selected breeding materials with desirable alleles and reducing the number of years required to combine these traits in elite varieties.

scholarly journals Phenotypic characterization of wheat landraces from mid and far western districts of Nepal

2015 ◽  
Vol 4 (4) ◽  
pp. 32-44
Author(s):  
Sangharash Raj Dangi ◽  
Ramesh Raj Puri ◽  
Nutan Raj Gautam
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Phenotypic Variability ◽  
Block Design ◽  
Wheat Breeding ◽  
Phenotypic Characterization ◽  
Improvement Program ◽  
Wide Range ◽  
Wheat Landraces

The study was conducted to evaluate phenotypic variation in one hundred and sixty six wheat landraces from mid and far western districts of Nepal. They were sown in randomized complete block design with two replications at National Wheat Research Program in 2014/15. The observed traits were analyzed using descriptive statistics and multivariate analysis using MINITAB v. 14. The results showed a wide range of phenotypic variability in observed parameters. The results also showed that the highest value of the standard deviation from mean (Sd) was for grain yield (±290.10) followed by plant height (±7.21). Among the traits the lowest deviation from mean (Sd) was for thousand grain weight TGW (±2.68). Wheat landraces grouped in four clusters depending on similarity of the studied traits. The results in this cluster, showed that days to maturity ranged from 97 to111 days, TGW ranged from 16 to17 gm, plant height ranged from 76 to 85 cm, and grain yield ranged from 2800 to 3000 Kg ha-1. Wheat landraces under study are grouped depending on specific traits useful for wheat improvement program. Results of this study can be supportive to detect wheat landraces within species with similar traits. In addition it can be useful for sampling in successive studies and parental selection in wheat breeding program.International Journal of Environment Vol.4(4) 2015: 32-44

scholarly journals Evaluation of Yield and its Components in Bread Wheat (Triticum aestivum L.) Genotypes

2021 ◽  
Vol 2 (1) ◽  
pp. 76-82
Author(s):  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Triticum Aestivum L ◽  
Morphological Characters ◽  
Considerable Variability ◽  
Thousand Grain Weight ◽  
Important Food ◽  
Wheat Genotypes ◽  
Wheat Improvement ◽  
Plot Yield

Bread wheat is an important food crop of world and Pakistan. An experiment was conducted in winter wheat growing season to assess yield and yield related traits of newly evolved wheat genotypes. The 16 wheat genotypes includes 14 advanced lines viz., CIM-04-5, CIM-04-21, CIM-04-3, C7-98-11, 5-02, V2-10-12, CIM-03-2, C2-98- 6, 6-12, V3-10-9, C6-98-5, V3-10-32, C2-98-8, V2-10-21 and 2 local checks NIA Sunhari and Kiran 95 were tested. Experimental design was laid out in RCBD with 3 replicates. Mean square for genotypes showed high significantly differences for most of agro-morphological characters. Mean and range of all wheat genotypes for all the traits indicated a considerable variability between genotypes. Mean performance for the trait grain yield showed that newly developed genotypes C2-98-8, CIM-04-21, V3-10-32 and CIM-04-3 produced higher grain yield (3 to 3.25 kg plot-1) than both the contesting check varieties. High significantly and positively correlation of the plot yield to thousand grain weight (0.41**), biomass (0.41**) and harvest index (0.86***) with grain yield were found. It indicated that by improving these three traits, we can significantly improve grain yield. Selected genotypes and traits can be used in breeding program for wheat improvement.

scholarly journals Genetic analysis for various yield components and gluten content in bread wheat (Triticum aestivum L.)

2017 ◽  
Vol 9 (2) ◽  
pp. 879-882
Author(s):  
Sandeep Kumar ◽  
Pradeep Kumar ◽  
S. A. Kerkhi
Keyword(s):  
Triticum Aestivum ◽  
Genetic Analysis ◽  
Grain Yield ◽  
Bread Wheat ◽  
Coefficient Of Variation ◽  
Triticum Aestivum L ◽  
Gluten Content ◽  
Diallel Mating Design ◽  
Wide Range ◽  
Positive Direct

Genetic analysis was carried out in 55 genotypes (10 parents and 45 F1s) through diallel mating design excluding reciprocals in bread wheat (Triticum aestivum L.). Analysis of variance showed wide range of variability among the breeding material for all the traits under study. The highest value of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were recorded for grain yield (PCV= 9.07 and GCV= 8.08). Highest heritability with genetic advance was recorded for grain yield (h2=10.60 and GA=14.84), therefore selection will be effective based on grain yield for further study. Grains per spike (gr = 0.77 and pr = 0.67) and spikelets per spike (gr= 0.63 and pr = 0.52) were found significantly correlated (at <1 % level of significance) with grain yield whereas gluten content showed nonsignificant but positive correlation with grain yield at both genotypic as well as phenotypic level. Similarly, path coefficient analysis estimates for gluten content (g= 0.08 and p= 0.03) and grains per spike (g=0.36 and p=0.23) showed high positive direct effects on grain yield therefore these traits may be used as an index for selection to high yield in bread wheat genotypes.

scholarly journals Combining grain yield, protein content and protein quality by multi-trait genomic selection in bread wheat

2019 ◽  
Vol 132 (10) ◽  
pp. 2767-2780
Author(s):  
Sebastian Michel ◽  
Franziska Löschenberger ◽  
Christian Ametz ◽  
Bernadette Pachler ◽  
Ellen Sparry ◽  
...  
Keyword(s):  
Grain Yield ◽  
Protein Content ◽  
Genomic Selection ◽  
Bread Wheat ◽  
Protein Quality

scholarly journals Prospects and Challenges of Applied Genomic Selection—A New Paradigm in Breeding for Grain Yield in Bread Wheat

2018 ◽  
Vol 11 (3) ◽  
pp. 180017 ◽  
Author(s):  
Philomin Juliana ◽  
Ravi P. Singh ◽  
Jesse Poland ◽  
Suchismita Mondal ◽  
José Crossa ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genomic Selection ◽  
Bread Wheat ◽  
New Paradigm

scholarly journals Estimation of Indian and Turkish Hexaploid Wheat Population Structure to be a Part of Improved Breeding Program

2015 ◽  
Vol 43 (1) ◽  
pp. 70-78
Author(s):  
Anamika PANDEY ◽  
Mohd Kamran KHAN ◽  
George THOMAS ◽  
Erdogan E. HAKKI ◽  
Seyit Ali KAYIS ◽  
...  
Keyword(s):  
Population Structure ◽  
Hexaploid Wheat ◽  
Population Based ◽  
Modern World ◽  
Improvement Program ◽  
Wheat Improvement ◽  
Wheat Population ◽  
Population Structure Analysis ◽  
Wide Range ◽  
Improvement Programs

Bread wheat (Triticum aestivum) is the most commonly grown crop due to its adaptation in a wide range of eco-geographical conditions and providing enhanced food assurance to the modern world. A diverse and rich collection is the foundation of each successful wheat improvement program. Therefore, major efforts are in progress worldwide to boost wheat production by broadening genetic diversity. Accepting this issue as a target, present study gives an overview of the major progress in the diversity and population evaluation of Indian and Turkish hexaploid wheat employing ISSR and RAPD primers. Various statistical analyses were employed for determining the hexaploid wheat population structure of India and Turkey. Results of dendrogram, scatterplots, Analysis of Molecular Variance (AMOVA) and population structure analysis were found in accordance with each other. All the experimental genotypes were clustered in two main groups, one group containing Indian varieties and another group containing both Indian and Turkish varieties reflecting the direct or indirect interbreeding among the populations of the two countries. Utilizing the genetic association of Indian and Turkish hexaploid wheat population, based on genetic distance estimated in the study, researchers worldwide may include Indian and Turkish hexaploid varieties in the wheat improvement programs and can evade the likelihood of selected germplasm becoming hereditarily consistent.

scholarly journals GGE Biplot Analysis of Genotype by Environment Interaction and Grain Yield Stability of Bread Wheat Genotypes in Central Ethiopia

2019 ◽  
Vol 7 (2) ◽  
pp. 75-85
Author(s):  
Gadisa A. Wardofa ◽  
Dawit Asnake ◽  
Hussein Mohammed
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Principal Component ◽  
Moisture Stress ◽  
Genotype By Environment Interaction ◽  
Large Contribution ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Wheat Genotypes ◽  
Wide Range

GGE biplot is an effective method based on principal component analysis to fully explore mega-environments trials data. The study conducted was to identify the best performing, high yielding stable advanced bread wheat genotype for selection environments, the identification of mega-environments and analysis of the ideal genotype and environment by GGE biplot method. Fifteen bread wheat genotypes were evaluated using RCBD with four replications at six locations in Ethiopia. The results of combined analysis of variance for grain yield of fifteen bread wheat genotypes indicated that genotype, environment and GEI were highly significant (P0.001). The factors explained showed bread wheat genotypes grain yield was affected by environment (35.28%), genotype (33.46%) and GEI (31.45%). The first two PC axes of GGE explained 88.7% of G+GEI and divided the six locations into three major groups: Group1 included Asasa, Kulumsa and Arsi Robe (moderately discriminating locations); Group2 had the highland wheat producing locations Holeta and Bekoji (most discriminating locations), while Group3 contain Dhera (least discriminating location), a moisture stress location in the rift valley. Locations within the same group were closely correlated and provided redundant information about the genotypes. Testing can be performed in any one of the locations within a group. Genotype ETBW8078 and ETBW8459 were more stable as well as low yielding. Considering simultaneously yield and stability, genotype ETBW9045 and Hiddase showed the best performances suggesting their adaptation to a wide range of environments. Lemu, ETBW8084 and ETBW8065 were considered as desirable. Genotype ETBW8075 was the least stable with low yield and had a large contribution to the GEI, having the longest distance from the average environment. ETBW9470 was specifically adapted to Group1 locations while ETBW8070 was adapted to Group2 environments. Based on yield performance advanced lines ETBW9470 and ETBW8070 are recommended to be included in variety verification trials for further release.

Effectiveness of mechanical mass selection in wheat (Triticum aestivum L.)

1972 ◽  
Vol 23 (5) ◽  
pp. 761 ◽  
Author(s):  
NF Derera ◽  
GM Bhatt
Keyword(s):  
Triticum Aestivum ◽  
Grain Yield ◽  
Seed Size ◽  
Triticum Aestivum L ◽  
Kernel Weight ◽  
Mass Selection ◽  
Improvement Program ◽  
Wheat Improvement ◽  
Mechanical Mass ◽  
Practical Implications

The efficiency of mechanical mass selection in wheat was tested on genetically heterogeneous and homogeneous populations. The populations were mechanically stratified according to seed size and field-tested for 2 years. Shifts in means and reductions in variances for kernel weight, grain weight per ear, and grain yield per plot were observed in the mass-selected populations of heterogeneous bulks. No such shift in means or reduction in variance was observed in stratified homogeneous populations. Populations selected for high seed size in heterogeneous bulks expressed themselves into higher grain yields per plot. Practical implications of these findings in formulating a wheat improvement program are discussed.

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