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首页> 外文期刊>Australian Journal of Crop Science >Application of secondary traits in barley for identification of drought tolerant genotypes in multi-environment trials
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Application of secondary traits in barley for identification of drought tolerant genotypes in multi-environment trials

机译:在大麦中的次级特征在多环境试验中鉴定耐旱基因型的应用

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Discriminant function analysis (DFA) is a biometric method that can be used by breeders to distinguish between drought tolerant genotypes. Drought stress is one of the major limiting factors that reduce crop production in semi-arid and arid regions around the world. A multi-environment trial was conducted on barley to investigate various phonological and morphological characteristics under both drought stress and irrigated conditions. Ten indigenous barley genotypes were evaluated in four cropping seasons and in two locations of Iran. Genetic variation was observed in all traits. The traits observed in all genotypes were significantly different. The average broad sense heritability predicted for secondary traits (0.88) was significantly more than grain yield (0.62). The results could significantly discriminate between low and high yield genotypes under drought stress by describing eight secondary traits including biomass, spike weight, grain numbers per main spike, grain numbers per plant, awn length, days to flowering, grain filling period and potential yield. High yield genotypes were selected by discriminant analysis (Eq. (1)). The discriminant score (DS) could explain 67% of grain yield variations and had a significant correlation (r=0.82 ** ) with the average of grain yield examined under drought stress over four years. Consequently, integrated selection can be used as a reliable approach to future breeding programs. Results of DFA indicated that the most important traits, in order of appearance, are awn length, grain filling period, spike weight, and grain numbers per main spike. The results demonstrated that secondary traits could be considered as proper criteria to improve the genetic gain of grain yield and to select tolerant cultivars for environments that are susceptible to drought.
机译:判别函数分析(DFA)是一种生物识别方法,可由育种者使用以区分耐旱性基因型。干旱压力是在世界各地半干旱和干旱地区减少作物生产的主要限制因素之一。在大麦上进行多环境试验,以研究干旱胁迫和灌溉条件下的各种语音和形态特征。在四个种植季节和伊朗的两个地点评估了十个土着大麦基因型。在所有特征中观察到遗传变异。在所有基因型中观察到的特征显着不同。对次级性状(0.88)预测的平均广义遗传性显着大于谷物产量(0.62)。通过描述包括生物质,每种植物穗重量,每株植物穗重量,粒度,长度,开花,谷物灌装周期和潜在产量,可以显着地歧视低产胁迫下的低产量基因型通过判别分析选择高收益基因型(EQ。(1))。判别评分(DS)可以解释粮食产量变化的67%,并且具有显着的相关性(R = 0.82 **),在四年内在干旱胁迫下进行的谷物产量的平均值。因此,综合选择可以用作未来育种计划的可靠方法。 DFA的结果表明,出现的秩序,颗粒灌装周期,穗重量和每个主要尖峰的粒度最重要的特征。结果表明,次级特征可以被认为是改善谷物产量的遗传增益和选择易受干旱的环境的耐受品种的适当标准。

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