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江苏省小麦品种(系)籽粒产量基因型与环境互作分析
引用本文:姚金保,张 鹏,余桂红,马鸿翔,杨学明,周淼平,张平平. 江苏省小麦品种(系)籽粒产量基因型与环境互作分析[J]. 麦类作物学报, 2021, 41(2): 191-202
作者姓名:姚金保  张 鹏  余桂红  马鸿翔  杨学明  周淼平  张平平
作者单位:江苏省农业科学院粮食作物研究所/江苏省农业生物学重点实验室,江苏南京210014;扬州大学江苏省粮食作物现代产业技术协同创新中心,江苏扬州225009;江苏省农业科学院粮食作物研究所/江苏省农业生物学重点实验室,江苏南京210014
基金项目:江苏省重点研发计划项目(BE2018350);江苏省农业重大品种创制项目(PZCZ201705);农业部现代农业产业技术体系项目(CARS-03)
摘    要:为客观评价多点试验中小麦新品种(系)籽粒产量的稳定性、适应性以及试点辨别力,探明适合江苏省小麦多点鉴定试验基因型与环境互作分析方法,采用AMMI模型对2018-2019年度江苏省淮南区试A组15个小麦品种(系)和淮北区试C组14个小麦品种(系)分别在12个试点的籽粒产量数据进行分析。结果表明,在两组试验中,基因型效应(G)、环境效应(E)和基因型与环境互作效应(G×E)均达到极显著水平。环境效应分别占淮南和淮北处理平方和的89.55%和70.71%,基因型效应分别占3.10%和12.89%,互作效应分别占7.35%和16.19%。基因型与环境互作中两条显著的主成分轴分别解释了淮南60.54%和淮北56.53%的互作平方和。在本年度特定的气候条件下,15个淮南小麦品种(系)中,宁红1479、金丰1701和盐麦0816属于高产稳产品系;14个淮北小麦品种(系)中,保麦1702、淮核16174属于高产稳产品系。12个试点中,淮南以南通、扬州和金湖试点的分辨力最强;淮北以响水、徐州和宿豫试点的分辨力最强。由AMMI双标图及互作效应值分析可知,两组试验的高产品系对某些试点具有特殊适应性。

关 键 词:小麦  AMMI模型  稳定性  适应性  试点鉴别力

Genotype by Environment Interaction Effect on Grain Yield of Wheat Cultivars in Jiangsu Province
YAO Jinbao,ZHANG Peng,YU Guihong,MA Hongxiang,YANG Xueming,ZHOU Miaoping,ZHANG Pingping. Genotype by Environment Interaction Effect on Grain Yield of Wheat Cultivars in Jiangsu Province[J]. Journal of Triticeae Crops, 2021, 41(2): 191-202
Authors:YAO Jinbao  ZHANG Peng  YU Guihong  MA Hongxiang  YANG Xueming  ZHOU Miaoping  ZHANG Pingping
Abstract:In order to evaluate the stability and adaptability of the new wheat varieties(lines) in the multi-environment trials,as well as the site discriminability,and to identify the appropriate analytical method for analyzing the genotype and environment interaction of the multi-environment trials of wheat varieties(lines) in Jiangsu Province,15 spring wheat genotypes from Huainan regional trial A group and 14 semi-winter wheat genotypes from Huaibei regional trial C group were grown at 12 various experimental locations,respectively,during 2018-2019 growing season. The stability of genotypes and site discriminability were identified by AMMI(additive main effect and multiplicative interaction) biplot analysis. The AMMI analysis showed that the variance of genotype,environment and GE interaction were significant in the two groups of regional trials and the major treatment sum of squares were significantly affected by environments(89.55% and 70.71%),genotypes(3.10% and 12.89%) and GE interaction(7.35% and 16.19%),respectively. The first two principal component axes(PCA1 and PCA2) explained 60.54% in Huainan and 56.53% in Huaibei of the total GE interaction. Under the specific climatic conditions for the year of 2018-2019,Ninghong 1479,Jiangfeng 1701 and Yanmai 0816 were quite stable as well as high yielding among 15 spring wheat genotypes in Huainan. Of the 14 semi-winter genotypes,Baomai 1702 and Huaihe 16174 exhibited high and stable yield in Huaibei. Environments Nantong,Yangzhou and Jinghu in Huainan,and Xiangshui,Xuzhou and Suyu in Huaibei significantly discriminated wheat genotypes,respectively. Based on the analysis of AMMI biplot and effect value of GE interaction,the wheat genotypes with high yield had specific adaptability to some locations in two groups of regional trial in Jiangsu.
Keywords:Wheat   AMMI model   Stability   Adaptability   Site discriminability
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