Optimizing the choice of test locations for multitrait genotypic evaluation

Jeffrey Neyhart, Lucia Gutierrez, Kevin P. Smith

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Plant breeding programs expend significant resources on multilocation testing to evaluate genotypes for advancement or potential cultivar release. The selection of genotype entries for these trials is typically based on previous phenotypic data or predictions; yet locations, important contributors to nongenetic variation, are often chosen in a less data-driven manner. Using agronomic and quality trait data from two long-term regional barley (Hordeum vulgare L.) nurseries, our objectives were (a) to measure the precision, repeatability, and representativeness of test locations based on multitrait data and (b) to optimize the selection of test locations for use in future trials. When considering traits individually, ideal locations could be identified simply, but a combined analysis of 11 traits indicated that very few locations were broadly favorable, and considerable tradeoffs are necessary. We developed a flexible optimization procedure to select the locations based on their precision, repeatability, and representativeness for multiple traits while simultaneously constraining the total number of locations. Optimization led to a 58–75% reduction in the number of locations, and therefore phenotyping costs, with little loss in data utility. Importantly, our approach allowed locations to be selected for phenotyping different sets of traits (e.g., either agronomic or both agronomic and malting quality), mimicking the often nested structure of trait data collection. This approach may be useful for individual plant breeding programs or collaborations wishing to increase the resource efficiency of these important regional evaluation trials.

Original languageEnglish (US)
Pages (from-to)192-202
Number of pages11
JournalCrop Science
Volume62
Issue number1
DOIs
StatePublished - Jan 1 2022

Bibliographical note

Publisher Copyright:
© 2021 The Authors Crop Science © 2021 Crop Science Society of America. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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