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Book
El análisis AMMI y la gráfica del biplot en SAS
(CIMMYT, 2000)
En este documento se presentan tres ejemplos de casos en los que se emplearon programas creados en SAS para obtener Modelos AMMI, asi como la prueba de Gollob (Gollob, 1967) para determinar la significancia de cada termino ...
Book
Modelos estadísticos multiplicativos para el análisis de la interacción genotipo x ambiente
(CIMMYT, 2000)
En los últimos 1O años se han logrado avances importantes en el uso de los modelos estadísticos multiplicativos para el análisis de ensayos de genotipos en ambientes múltiples y el estudio del complicado fenómeno de la ...
Handbook
User's guide for spatial analysis of field variety trials using ASREML
(CIMMYT, 2000)
This manual describes an approach to the spatial analysis of field experiments based on the software package AS residual maximum likelihood (ASREML; Gilmour et al. 1999). It describes common sources of spatial variation ...
Article
Handbook
SAS macro for analysing unreplicated designs
(CIMMYT, 2000)
Augmented or unreplicated experiment designs have two type of treatments, the replicated checks and the unreplicated new entries. The latter are usually considered to be random effects while the checks treatments are ...
Report
The AMMI analysis and graphing the biplot
(CIMMYT, 2000)
With the objective of facilitating researchers of CIMMYT and National Programs to compute the AMMI model and the biplot of multi-environment trials, three programs were written in SAS for computing the AMMI analysis and ...
Article
Sashaydiall: A SAS program for hayman’s diallel analysis
(Crop Science Society of America (CSSA), 2018)
Different methods of diallel crossing are commonly used in plant breeding. The diallel cross analysis method proposed by Hayman is particularly useful because it provides information, among others, on additive and dominance ...
Article
A bayesian genomic regression model with skew normal random errors
(Genetics Society of America, 2018)
Genomic selection (GS) has become a tool for selecting candidates in plant and animal breeding programs. In the case of quantitative traits, it is common to assume that the distribution of the response variable can be ...
Article
Genomic prediction of genotype x environment interaction kernel regression models
(Crop Science Society of America, 2016)
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this ...
Article
Prediction of multiple-trait and multiple-environment genomic data using recommender systems
(Genetics Society of America, 2018)
In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. ...