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首页> 外文期刊>Acta Scientiarum. Agronomy >Consideration of the appropriate variation sources of the statistical model and their impacts on plant breeding
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Consideration of the appropriate variation sources of the statistical model and their impacts on plant breeding

机译:考虑适当的统计模型变异源及其对植物育种的影响

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摘要

The present work has aimed to assess the consideration of the appropriate variation sources of the statistical model and their impacts on the conclusions plant breeding. The Value for Cultivation and Use test was conducted to assess three common locations (Lages, Ponte Serrada, and Canoinhas) and four non-common locations (Chapecó, Guatambu, Urussanga, and Campos Novos). The grain yields of six bean genotypes were evaluated in order to represent the imbalance between the common and non-common locations. The statistical analysis considered two situations: i) union of the location factors and cultivation years, with a single variation source called environment and ii) decomposition of the mean square values of the two factors, location and year. According to the simplified analysis (environmental variation source), the F test for the genotype factor was highly significant (p = 0.0006). On the other hand, the hypothesis test for the genotype factor was not significant (p = 0.7370) when the decomposition of mean squares was used. The simplified analysis presents some erroneous points, such as the use of a mean residue to test the hypothesis of the genotype factor, since this factor is composed of several sources of variation, and there is no exact F test. However, approximate F tests can be obtained by constructing linear combinations of average squares. This fact notes the relevance of considering the appropriate sources of variation within the statistical model, with a direct impact on the conclusions and recommendations of cultivars with superior performance.
机译:本工作旨在评估对统计模型的适当变化来源的考虑及其对植物育种结论的影响。进行了“耕种和使用价值”测试,以评估三个常见的地点(拉格斯,蓬特塞拉达和卡诺伊尼亚斯)和四个非常见的地点(查佩柯,瓜塔姆布,乌鲁桑加和坎波斯·诺沃斯)。评价了六种基因型豆的单产,以代表常见和非常见位置之间的不平衡。统计分析考虑了两种情况:i)位置因子和耕种年的结合,只有一个称为环境的变异源; ii)位置和年份这两个因子的均方值分解。根据简化分析(环境变化源),基因型因子的F检验非常显着(p = 0.0006)。另一方面,当使用均方分解时,基因型因子的假设检验不显着(p = 0.7370)。简化的分析提出了一些错误的观点,例如使用均值残基来检验基因型因子的假设,因为该因子由多种变异来源组成,并且没有确切的F检验。但是,可以通过构造平均平方的线性组合来获得近似的F检验。这一事实说明了在统计模型中考虑适当的变异来源的相关性,这直接影响了具有优异表现的品种的结论和建议。

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