Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

Ashok Singamsetti; Pervez H Zaidi; Kaliyamoorthy Seetharam; Madhumal Thayil Vinayan; Tiago Olivoto; Anima Mahato; Kartik Madankar; Munnesh Kumar; Kumari Shikha

doi:10.3389/fpls.2023.1147424

Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

Front Plant Sci. 2023 Mar 3:14:1147424. doi: 10.3389/fpls.2023.1147424. eCollection 2023.

Authors

Ashok Singamsetti¹, Pervez H Zaidi², Kaliyamoorthy Seetharam², Madhumal Thayil Vinayan², Tiago Olivoto³, Anima Mahato⁴, Kartik Madankar¹, Munnesh Kumar¹, Kumari Shikha¹

Affiliations

¹ Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India.
² Asia Regional Maize Programme, The International Maize and Wheat Improvement Center (CIMMYT)-Hyderabad, Patancheru, India.
³ Department of Plant Science, Federal University of Santa Cataria, Florianópolis, Brazil.
⁴ Indian Council of Agricultural Research (ICAR) - Indian Agricultural Research Institute (IARI), Barhi, Jharkhand, India.

Abstract

Unpredictable weather vagaries in the Asian tropics often increase the risk of a series of abiotic stresses in maize-growing areas, hindering the efforts to reach the projected demands. Breeding climate-resilient maize hybrids with a cross-tolerance to drought and waterlogging is necessary yet challenging because of the presence of genotype-by-environment interaction (GEI) and the lack of an efficient multi-trait-based selection technique. The present study aimed at estimating the variance components, genetic parameters, inter-trait relations, and expected selection gains (SGs) across the soil moisture regimes through genotype selection obtained based on the novel multi-trait genotype-ideotype distance index (MGIDI) for a set of 75 tropical pre-released maize hybrids. Twelve traits including grain yield and other secondary characteristics for experimental maize hybrids were studied at two locations. Positive and negative SGs were estimated across moisture regimes, including drought, waterlogging, and optimal moisture conditions. Hybrid, moisture condition, and hybrid-by-moisture condition interaction effects were significant (p ≤ 0.001) for most of the traits studied. Eleven genotypes were selected in each moisture condition through MGIDI by assuming 15% selection intensity where two hybrids, viz., ZH161289 and ZH161303, were found to be common across all the moisture regimes, indicating their moisture stress resilience, a unique potential for broader adaptation in rainfed stress-vulnerable ecologies. The selected hybrids showed desired genetic gains such as positive gains for grain yield (almost 11% in optimal and drought; 22% in waterlogging) and negative gains in flowering traits. The view on strengths and weaknesses as depicted by the MGIDI assists the breeders to develop maize hybrids with desired traits, such as grain yield and other yield contributors under specific stress conditions. The MGIDI would be a robust and easy-to-handle multi-trait selection process under various test environments with minimal multicollinearity issues. It was found to be a powerful tool in developing better selection strategies and optimizing the breeding scheme, thus contributing to the development of climate-resilient maize hybrids.

Keywords: climate-resilient maize; drought; genotype-by-environment interaction (GEI); moisture regimes; multi-trait index; selection gains; waterlogging.