Relative utility of agronomic, phenological, and morphological traits for assessing genotype-by-environment interaction in maize inbreds

Celeste M. Falcon, Shawn M. Kaeppler, Edgar P. Spalding, Nathan D. Miller, Nicholas Haase, Naser AlKhalifah, Martin Bohn, Edward S. Buckler, Darwin A. Campbell, Ignacio Ciampitti, Lisa Coffey, Jode Edwards, David Ertl, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, Diego Jarquín, Joseph KnollNick Lauter, Carolyn J. Lawrence-Dill, Elizabeth C. Lee, Aaron Lorenz, Jonathan P. Lynch, Seth C. Murray, Rebecca Nelson, M. Cinta Romay, Torbert Rocheford, Patrick S. Schnable, Brian Scully, Margaret Smith, Nathan Springer, Mitchell R. Tuinstra, Renee Walton, Teclemariam Weldekidan, Randall J. Wisser, Wenwei Xu, Natalia de Leon

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Plant breeders face the challenge of genotype × environment interaction (G × E) in comprehensively breeding for expanded geographic regions. An improved understanding of G × E sensitivity of traits and the environmental features that effectively discriminate among genotypes will enable more efficient breeding efforts. In this study of 31 maize (Zea mays L.) inbreds grown in 36 environments that are part of the Genomes to Fields Initiative, we measured 14 traits, including flowering date, height, and yield components (i.e., ear and kernel dimensions) to (i) identify traits that are the most sensitive indicators of G × E; (ii) determine how geographic location and weather factors influence environments’ discriminability of inbreds; and (iii) detect patterns of stability in better and worse discriminating environments. Genotype × environment interaction explained between 9.0–20.4% of the phenotypic variance with greater effects in the yield-component traits. Discriminability of environments varied by trait. Midwest locations (where 26 of the 31 inbreds were developed) were among the most discriminating environments for more traits, while environments in the West and East tended to be less discriminating. Weather factors during silking were significantly different between the most and least discriminating environments more often than average weather across the season or during the period from planting to silking. Stability of genotypes varied by trait, and performance was usually not correlated with stability. The dissection of complex traits, such as yield into component traits, appears to be a useful approach to understand how environmental factors differentially affect phenotype.

Original languageEnglish (US)
Pages (from-to)62-81
Number of pages20
JournalCrop Science
Volume60
Issue number1
DOIs
StatePublished - Jan 1 2020

Bibliographical note

Funding Information:
The authors thank the entire G2F Consortium for their help with this study: Emily Rothfusz and Jane Petzoldt from the University of Wisconsin‐Madison for assisting with coordination of the project; Dustin Eilert and Marina Borsecnik for assistance organizing and conducting field trials at the University of Wisconsin‐Madison; and Miriam Lopez, Grace Kuehne, and Sarah Hennings from the USDA‐ARS Corn Insects and Crop Genetics Research Unit at Iowa State University. We also acknowledge contributions from field manager, Nicholas Kaczmar, at Cornell University. This project was supported by the Iowa Corn Promotion Board, the Nebraska Corn Board, the Minnesota Corn Research and Promotion Council, the Illinois Corn Marketing Board, the Wisconsin Corn Promotion Board, and the National Corn Growers Association. Thanks to USDA‐NIFA Hatch for supporting a large number of the cooperators. USDA‐ARS base funds were also provided for ESB, JE, SF‐G, JBH, JK, NL, and BS. Support was also provided through the Corn Promotion Board Endowed Chair in Maize Genetics for PSS. We thank the support of the USDA Hatch under accession numbers 1003971 for MAG and NSF grant IOS‐1444456 that supports EPS. We thank the Texas Corn Producers Board and Texas A&M AgriLife Research for support for SCM.

Funding Information:
The authors thank the entire G2F Consortium for their help with this study: Emily Rothfusz and Jane Petzoldt from the University of Wisconsin-Madison for assisting with coordination of the project; Dustin Eilert and Marina Borsecnik for assistance organizing and conducting field trials at the University of Wisconsin-Madison; and Miriam Lopez, Grace Kuehne, and Sarah Hennings from the USDA-ARS Corn Insects and Crop Genetics Research Unit at Iowa State University. We also acknowledge contributions from field manager, Nicholas Kaczmar, at Cornell University. This project was supported by the Iowa Corn Promotion Board, the Nebraska Corn Board, the Minnesota Corn Research and Promotion Council, the Illinois Corn Marketing Board, the Wisconsin Corn Promotion Board, and the National Corn Growers Association. Thanks to USDA-NIFA Hatch for supporting a large number of the cooperators. USDA-ARS base funds were also provided for ESB, JE, SF-G, JBH, JK, NL, and BS. Support was also provided through the Corn Promotion Board Endowed Chair in Maize Genetics for PSS. We thank the support of the USDA Hatch under accession numbers 1003971 for MAG and NSF grant IOS-1444456 that supports EPS. We thank the Texas Corn Producers Board and Texas A&M AgriLife Research for support for SCM.

Publisher Copyright:
Published 2019. This article is a U.S. Government work and is in the public domain in the USA. Crop Science published by Wiley Periodicals, Inc. on behalf of Crop Science Society of America

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