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Evaluating Genotype × Environment Interactions of Yield Traits and Adaptability in Rice Cultivars Grown under Temperate, Subtropical and Tropical Environments

Author

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  • Xing Huang

    (Department of Agriculture, Forestry and Bioresources, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea
    Xing Huang and Su Jang contributed equally to this work.)

  • Su Jang

    (Department of Agriculture, Forestry and Bioresources, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea
    Xing Huang and Su Jang contributed equally to this work.)

  • Backki Kim

    (Department of Agriculture, Forestry and Bioresources, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea)

  • Zhongze Piao

    (Crop Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China)

  • Edilberto Redona

    (Delta Research and Extension Center, Mississippi State University, Stoneville, MS 38776, USA)

  • Hee-Jong Koh

    (Department of Agriculture, Forestry and Bioresources, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea)

Abstract

Rice yield is a complex trait that is strongly affected by environment and genotype × environment interaction (GEI) effects. Consideration of GEI in diverse environments facilitates the accurate identification of optimal genotypes with high yield performance, which are adaptable to specific or diverse environments. In this study, multiple environment trials were conducted to evaluate grain yield (GY) and four yield-component traits: panicle length, panicle number, spikelet number per panicle, and thousand-grain weight. Eighty-nine rice varieties were cultivated in temperate, subtropical, and tropical regions for two years. The effects of both GEI (12.4–19.6%) and environment (23.6–69.6%) significantly contributed to the variation of all yield-component traits. In addition, 37.1% of GY variation was explained by GEI, indicating that GY performance was strongly affected by the different environmental conditions. GY performance and genotype stability were evaluated using simultaneous selection indexing, and 19 desirable genotypes were identified with high productivity and broad adaptability across temperate, subtropical, and tropical conditions. These optimal genotypes could be recommended for cultivation and as elite parents for rice breeding programs to improve yield potential and general adaptability to climates.

Suggested Citation

  • Xing Huang & Su Jang & Backki Kim & Zhongze Piao & Edilberto Redona & Hee-Jong Koh, 2021. "Evaluating Genotype × Environment Interactions of Yield Traits and Adaptability in Rice Cultivars Grown under Temperate, Subtropical and Tropical Environments," Agriculture, MDPI, vol. 11(6), pages 1-12, June.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:6:p:558-:d:577442
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    References listed on IDEAS

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    1. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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    1. Haiwang Yue & Hugh G. Gauch & Jianwei Wei & Junliang Xie & Shuping Chen & Haicheng Peng & Junzhou Bu & Xuwen Jiang, 2022. "Genotype by Environment Interaction Analysis for Grain Yield and Yield Components of Summer Maize Hybrids across the Huanghuaihai Region in China," Agriculture, MDPI, vol. 12(5), pages 1-17, April.
    2. Seung Young Lee & Hyun-Sook Lee & Chang-Min Lee & Su-Kyung Ha & Hyang-Mi Park & So-Myeong Lee & Youngho Kwon & Ji-Ung Jeung & Youngjun Mo, 2023. "Multi-Environment Trials and Stability Analysis for Yield-Related Traits of Commercial Rice Cultivars," Agriculture, MDPI, vol. 13(2), pages 1-13, January.

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