Now showing items 1-10 of 21
A general Bayesian estimation method of linear-bilinear models applied to plant breeding trials with genotype × environment interaction
(Springer Verlag; American Statistical Association; International Biometrics Society, 2012)
Statistical analyses of two-way tables with interaction arise in many different fields of research. This study proposes the von Mises-Fisher distribution as a prior on the set of orthogonal matrices in a linear-bilinear ...
Genomic-enabled prediction accuracies increased by modeling genotype × environment interaction in durum wheat
(Crop Science Society of America, 2018)
Genomic prediction studies incorporating genotype × environment (G×E) interaction effects are limited in durum wheat. We tested the genomic-enabled prediction accuracy (PA) of Genomic Best Linear Unbiased Predictor (GBLUP) ...
IBFIELDBOOK, an integrated breeding field book for plant breeding
(Sociedad Mexicana de Fitogenética, 2013)
The development of an integrated breeding field book (IBFieldbook) for different crops involves the generation, handling and analysis of large amounts of data. Managing the integration of environmental, pedigree, and ...
A hierarchical bayesian estimation model for multienvironment plant breeding trials in successive years
(Crop Science Society of America (CSSA), 2016)
In agriculture and plant breeding, multienvironment trials over multiple years are conducted to evaluate and predict genotypic performance under different environmental conditions and to analyze, study, and interpret ...
Genomic prediction with pedigree and genotype X environment interaction in spring wheat grown in South and West Asia, North Africa, and Mexico
(Genetics Society of America, 2017)
Developing genomic selection (GS) models is an important step in applying GS to accelerate the rate of genetic gain in grain yield in plant breeding. In this study, seven genomic prediction models under two cross-validation ...
Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea
(Nature Research; Springer Nature, 2018)
Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve ...
Genomic-enabled prediction in maize using kernel models with genotype x environment interaction
(Genetics Society of America, 2017)
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: ...
Genomic prediction of gene bank wheat landraces
(Genetics Society of America, 2016)
This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including ...
A genomic selection index applied to simulated and real data
(Genetics Society of America, 2015)
A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors ...
Pedigree-based prediction models with genotype × environment interaction in multi-environment trials of CIMMYT wheat
(Crop Science Society of America (CSSA), 2017)
Genotype × environment (G × E) interaction can be studied through multienvironment trials used to select wheat (Triticum aestivum L.) lines. We used spring wheat yield data from 136 international environments to evaluate ...