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Main Authors: Prus, Maryna, Filová, Lenka, Piepho, Hans-Peter, Malik, Waqas Ahmed
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.27831
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author Prus, Maryna
Filová, Lenka
Piepho, Hans-Peter
Malik, Waqas Ahmed
author_facet Prus, Maryna
Filová, Lenka
Piepho, Hans-Peter
Malik, Waqas Ahmed
contents Plant breeding and variety trials are usually conducted in multiple environments sampled from a defined target population of environments in order to characterize the performance of breeding lines or varieties. When the population is large and heterogeneous, it may be sub-divided into sub-regions or zones according to administrative and agro-ecological criteria. Analysis then focuses on prediction of performance in the individual sub-regions. Modelling the genotype effect in each sub-region as random, information can be borrowed across sub-regions using best linear unbiased prediction based on a suitable variance-covariance matrix for the genotype-zone effects. Here, we consider the important case where kinship of pedigree information is available for the genotypes under test. This information can be integrated into the variance-covariance matrix for genotype-zone effects. The objective we pursue here is to determine the optimal allocation of a fixed budget of trials to sub-regions. This design problem is solved using a combination of theory and explicit equations on one hand and numerical optimization on the other hand. Our proposed novel approach allows obtaining the optimal allocation when the number of genotypes is in the hundreds, a common setting in large plant breeding programs as well as in variety testing for economically important crops.
format Preprint
id arxiv_https___arxiv_org_abs_2604_27831
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Optimal allocation of trials to sub-regions in crop variety testing with multiple years and correlated genotype effects
Prus, Maryna
Filová, Lenka
Piepho, Hans-Peter
Malik, Waqas Ahmed
Applications
Plant breeding and variety trials are usually conducted in multiple environments sampled from a defined target population of environments in order to characterize the performance of breeding lines or varieties. When the population is large and heterogeneous, it may be sub-divided into sub-regions or zones according to administrative and agro-ecological criteria. Analysis then focuses on prediction of performance in the individual sub-regions. Modelling the genotype effect in each sub-region as random, information can be borrowed across sub-regions using best linear unbiased prediction based on a suitable variance-covariance matrix for the genotype-zone effects. Here, we consider the important case where kinship of pedigree information is available for the genotypes under test. This information can be integrated into the variance-covariance matrix for genotype-zone effects. The objective we pursue here is to determine the optimal allocation of a fixed budget of trials to sub-regions. This design problem is solved using a combination of theory and explicit equations on one hand and numerical optimization on the other hand. Our proposed novel approach allows obtaining the optimal allocation when the number of genotypes is in the hundreds, a common setting in large plant breeding programs as well as in variety testing for economically important crops.
title Optimal allocation of trials to sub-regions in crop variety testing with multiple years and correlated genotype effects
topic Applications
url https://arxiv.org/abs/2604.27831