Yue Haiwang, Olivoto Tiago, Bu Junzhou, Wei Jianwei, Liu Pengcheng, Wu Wei, Nardino Maicon, Jiang Xuwen
Hebei Provincial Key Laboratory of Crops Drought Resistance Research, Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences, Hengshui, Hebei, 053000, China.
Department of Plant Science, Center of Agrarian Sciences, Federal University of Santa Catarina, Florianópolis, SC, Brazil.
BMC Plant Biol. 2025 Jan 28;25(1):120. doi: 10.1186/s12870-025-06158-w.
The development of superior summer maize hybrids with high-yield potential and essential agronomic traits, such as resistance to lodging, is crucial for ensuring the sustainability of maize cultivation. However, the task of identifying and breeding genotypes that exhibit exceptional performance and stability across multiple environment conditions, while considering a wide range of traits, is challenging. Given the backdrop of global climate change, understanding which climate variables and soil properties most significantly impact environmental similarity is essential for selecting hybrids with improved adaptability to regions with diverse climatic and soil conditions. This study aimed to integrate envirotyping techniques (ETs) with a multi-trait selection approach to carry out a comprehensive evaluation of maize genotypes for performance and stability.
The grain yields of 13 maize hybrids, along with their four critical agronomic parameters, were assessed in the Huang-Huai-Hai Plain of China across 40 locations in eight provinces. By considering 20 years of climatic factors and soil covariates, these 40 locations were divided into six mega-environments (MEs) based on similar long-term weather patterns and soil characteristics. Additive main effects and multiplicative interaction (AMMI) analyses revealed that genotype (G), environment (E), and the GxE interaction had significant effects on all agronomic parameters (P < 0.001). The mean performance and stability of the genotypes in each mega-environment were assessed, allowing for the identification of superior hybrids using the multi-trait stability index (MTSI). In two of the MEs (ME2 and ME3), only two hybrids, HY321 and HY9112, were selected concurrently.
Overall, this study provides valuable insights into the effects of ETs on maize hybrids and enhances our understanding of GxE interactions in multi-environment trials. This understanding is essential for improving maize cultivation practices and breeding program in diverse environments.
培育具有高产潜力和抗倒伏等重要农艺性状的优质夏玉米杂交种对于确保玉米种植的可持续性至关重要。然而，在考虑广泛性状的同时，识别和培育在多种环境条件下表现优异且稳定的基因型是一项具有挑战性的任务。在全球气候变化的背景下，了解哪些气候变量和土壤特性对环境相似性影响最大，对于选择能更好适应不同气候和土壤条件地区的杂交种至关重要。本研究旨在将环境分型技术（ETs）与多性状选择方法相结合，对玉米基因型的性能和稳定性进行全面评估。
在中国黄淮海平原的八个省份的40个地点对13个玉米杂交种的籽粒产量及其四个关键农艺参数进行了评估。通过考虑20年的气候因素和土壤协变量，根据相似的长期天气模式和土壤特征，将这40个地点分为六个大环境（MEs）。加性主效应和乘积互作（AMMI）分析表明，基因型（G）、环境（E）以及G×E互作对所有农艺参数均有显著影响（P < 0.001）。评估了每个大环境中基因型的平均性能和稳定性，从而能够使用多性状稳定性指数（MTSI）鉴定出优良杂交种。在其中两个大环境（ME2和ME3）中，仅同时选出了两个杂交种，即HY321和HY9112。
总体而言，本研究为ETs对玉米杂交种的影响提供了有价值的见解，并增强了我们对多环境试验中G×E互作的理解。这种理解对于改进不同环境下的玉米种植实践和育种计划至关重要。
