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Genotype Recommendations for Multi-Environments Based on AMMI Analysis

机译:基于AMMI分析的多环境基因型建议

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This study was conducted to evaluate the significance and magnitude of the effect of genotype x environment (GE) interaction on corn grain yield, and to determine the best genotype for each major corn-growing region in the Philippines. Replicated grain yield data of corn hybrids common across locations for each time period (consisting of two consecutive seasons) from 1996 to 2003 were examined and interpreted through the additive main effects and multiplicative interaction (AMMI) model and biplot analyses. The nominal yield (expected yield without the location main effect) of each genotype at each environment (location-season combination) was computed. Mega-environments (group of environments within each period that had the same highest nominal yielding genotype) were identified. Genotype (G), environment (E) and GE interaction were significant in all 14 time periods and accounted for an average of 5.3%, 83.8% and 10.5% of the variation in grain yield, respectively. The stability (range in nominalyield across environments) of each of the 55 genotypes (36 cultivars recommended by National Seed Industry Council [NSIC] and 19 non-recommended cultivars) that were identified as the highest nominal yielding genotype for their respective mega-environment was estimated. The highest nominal yielding genotype for the dry season (DS) was different from that for the wet season (WS) in 65 of the 95 location-period combinations. This list would be useful in recommending the appropriate genotype to grow in a particular environment as a cultivar for production or as a check cultivar in breeding or yield trials. It was estimated that nominal yields during the DS and WS would be 7.44 and 7.46 t ha~(-1), respectively, if the highest nominal yielding genotypes areselected and grown specifically in their respective mega-environments. For the 2002WS to the 2003DS time period, which included 14 environments, six mega-environments and their respective highest nominal yielding genotype were identified, CPX818 being the best performer based on its high and stable nominal yield. This study showed that GE interaction should be considered when estimating the yields of genotypes at different locations or when recommending the best genotype for the major corn- growing regions in the Philippines.
机译:进行这项研究是为了评估基因型x环境(GE)相互作用对玉米籽粒产量的影响的重要性和严重性,并确定菲律宾每个主要玉米种植地区的最佳基因型。通过累加主效应和乘性交互作用(AMMI)模型以及双图分析,研究并解释了1996年至2003年每个时段(两个连续的季节组成)的不同地点常见的玉米杂交种的重复谷物产量数据。计算每种基因型在每种环境(位置-季节组合)下的标称产量(无位置主效应的预期产量)。确定了超级环境(每个时期内具有相同最高名义产量基因型的环境组)。基因型(G),环境(E)和GE相互作用在所有14个时间段内均显着,分别分别占谷物产量变化的5.3%,83.8%和10.5%。被确定为各自超级环境的最高名义产量基因型的55个基因型(国家种子产业委员会[NSIC]推荐的36个品种和19个非推荐品种)中的每一个的稳定性(跨环境的名义产量范围)为估计。在95个定位时段组合中,有65个的旱季(DS)最高的名义产量基因型与雨季(WS)的最高名义基因型不同。该清单对于推荐合适的基因型在特定环境中生长作为生产品种或在育种或产量试验中作为检查品种很有用。据估计,如果选择最高的标称产量基因型并在其各自的大环境中专门生长,则在DS和WS期间的标称产量分别为7.44和7.46 t ha〜(-1)。在2002WS至2003DS这段时期内,确定了包括14种环境,6个巨型环境及其各自最高的标称产量基因型,CPX818基于其高且稳定的标称产量而表现最佳。这项研究表明,在估计不同地区的基因型产量或推荐菲律宾主要玉米种植地区的最佳基因型时,应考虑GE的相互作用。

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