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Utilization of Multiyear Plant Breeding Data to Better Predict Genotype Performance

OAR@ICRISAT

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Field Value
 
Relation http://oar.icrisat.org/11076/
http://dx.doi.org/10.2135/cropsci2018.03.0182
10.2135/cropsci2018.03.0182
 
Title Utilization of Multiyear Plant Breeding Data to Better Predict Genotype Performance
 
Creator Arief, V N
Desmae, H
Hardner, C
DeLacy, I H
Gilmour, A
Bull, J K
Basford, K E
 
Subject Plant Breeding
Genetics and Genomics
Maize
 
Description Despite the availability of multiyear, multicycle, and multiphase data in plant breeding programs for annual crops, selection is often based on single-year, single-cycle, and single-phase data. As genotypes in the same fields are usually grown under the same management practice, data from these fields can and should be analyzed together. In Monsanto’s North American maize (Zea mays L.) breeding program, this approach enables a spatial model to be fitted in each field, providing an estimate of spatial trend and a better estimate of residual variance in each field. Multiyear, multicycle analysis showed that the estimates of genotype × year variance (VGY) and genotype × year × location variance (VGYL) were still the largest components of the estimated phenotypic variance. Analysis of any single-year subset of the data inflated the estimate of genotypic variance (VG) by the size of the estimate of VGY, resulting in potential bias in the estimates of genotype performance. These results demonstrate the advantage of a combined analysis of data across years and cycles to make selection decisions for genotype advancement.
 
Publisher Crop Science Society of America
 
Date 2019
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Identifier http://oar.icrisat.org/11076/1/cs-0-0-cropsci2018.03.0182.pdf
Arief, V N and Desmae, H and Hardner, C and DeLacy, I H and Gilmour, A and Bull, J K and Basford, K E (2019) Utilization of Multiyear Plant Breeding Data to Better Predict Genotype Performance. Crop Science (TSI), 59. pp. 1-11. ISSN 0011-183X