DataSheet_1_Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection.docx

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.

亚洲热带地区难以预判的气象异常往往会提升玉米种植区一系列非生物胁迫（abiotic stresses）的发生风险，阻滞了玉米产量达成预期目标的育种工作。培育兼具干旱与渍涝交叉耐性的气候韧性玉米杂交种既是必要之举，却也颇具挑战——这是由于基因型与环境互作（genotype-by-environment interaction, GEI）的存在，以及当前缺乏高效的基于多性状的选择技术。
本研究旨在针对75份热带预审定玉米杂交种，基于新型多性状基因型-理想型距离指数（multi-trait genotype–ideotype distance index, MGIDI）开展基因型选择，进而估算不同土壤水分环境下的方差组分、遗传参数、性状间关联以及预期选择进展（selection gains, SGs）。本研究在两个试验地点对供试玉米杂交种的12个性状（包括籽粒产量及其他次要性状）进行了考察。研究分别在干旱、渍涝与适宜水分三种水分环境下估算了正向与负向选择进展。
对于绝大多数考察性状而言，杂交种效应、水分环境效应以及杂交种-水分环境互作效应均达到极显著水平（p ≤ 0.001）。本研究以15%的选择强度，通过MGIDI在每种水分环境下筛选出11份基因型，其中两个杂交种ZH161289与ZH161303在所有水分环境下均被选中，这表明二者具备水分胁迫耐性，在雨养胁迫敏感生态区具备更广泛适配的独特潜力。
被筛选出的杂交种展现出了预期的遗传进展：籽粒产量呈正向进展（适宜水分与干旱环境下约11%，渍涝环境下达22%），开花相关性状则呈负向进展。MGIDI所揭示的优势与短板可协助育种者培育具备目标性状的玉米杂交种，例如特定胁迫环境下的籽粒产量及其他产量构成性状。
MGIDI是一种稳健且易于操作的多性状选择方法，可在各类测试环境中应用，且多重共线性（multicollinearity）问题极少。该方法是制定更优选择策略、优化育种方案的有力工具，可为气候韧性玉米杂交种的培育提供助力。