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首页> 外文期刊>Mysore journal of agricultural sciences >Multiple stepwise regression analysis to estimate the root length, seed yield per plant and number of capsules per plant in sesame (Sesamum indicum L.).
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Multiple stepwise regression analysis to estimate the root length, seed yield per plant and number of capsules per plant in sesame (Sesamum indicum L.).

机译:多重逐步回归分析,以估算芝麻的根长,每株植物的种子产量和每株植物的荚膜数量(Sesamum indicum L.)。

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摘要

Ten genotypes of Sesamum (Sesamum indicum L.) were grown in poly vinyl chloride pipes at Gandhi Krishi Vignan Kendra and observations made on shoot and root morphological traits. Multiple stepwise regression analysis technique was used to find the contribution of root and shoot morphological characters on root length, seed yield per plant and number of seeds per capsule. The yield per plant and number of seeds per capsule were obtained at 90 DAS. Regression model was fitted; root length, seed yield per plant and number of capsules per plant was taken as dependent variable and other root and shoot characters are taken as independent variables in the model. The root, shoot length, plant height, capsule length and number of seeds per capsule were made the significant contribution towards seed yield per plant.
机译:在甘地克里希·维格南·肯德拉(Gandhi Krishi Vignan Kendra)的聚氯乙烯管中种植了十个芝麻(Sesamum indicum L.)基因型,并观察了茎和根的形态特征。采用多元逐步回归分析技术,研究了根和茎形态特征对根长,单株种子产量和每粒种子数量的贡献。在90 DAS下获得了每株植物的产量和每个胶囊的种子数。拟合回归模型;在模型中,将根长,每株植物的种子产量和每株植物的荚膜数量作为因变量,并将其他根和芽性状作为自变量。根,茎长,植物高度,荚膜长度和每粒种子的数量对每株植物的种子产量具有重要影响。

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