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An application of linear regression technique for predicting bulgur yield and quality of wheat cultivars

机译:线性回归技术在预测小麦品种小麦产量和品质中的应用

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摘要

Grains of 26 Turkish wheat cultivars and advanced breeding lines were used in this study. Simple correlations between a number of quality parameters to predict bulgur yield and bulgur cooking quality were determined. Highly significant correlations between bulgur yield and each of the thousand-kernel weight and the sum of the grain over 2.8 + 2.5 mm sieves were obtained for both durum and bread wheat samples (p < 0.01). The regression equations showed that the models involving two variables (the thousand-kernel weight and the thickness of the grain for durum wheat samples; the thousand-kernel weight and the length of the grain for bread wheat samples) resulted in the highest R-2 values. For an assessment of the influence of all factors on bulgur cooking properties (total organic matter: TOM and colorimetric test values), simple and multiple regression analyses were used to find equations that predict best the relationship between various quality parameters and bulgur cooking properties. The models involving two variables; the vitreousness and the dry gluten contents for the durum wheat samples and SDS sedimentation test value and wheat protein content for the bread wheat samples resulted in the highest R-2 for the TOM value.
机译:本研究使用了26个土耳其小麦品种和高级育种系的籽粒。确定了预测小麦产量和小麦烹饪质量的许多质量参数之间的简单相关性。对于硬粒小麦和面包小麦样品,均获得了小麦产量与千粒重和2.8 + 2.5 mm筛子上谷物总和之间的极显着相关性(p <0.01)。回归方程表明,涉及两个变量(硬粒小麦样品的千粒重和籽粒厚度;面包小麦样品的千粒重和籽粒长度)的模型得出最高的R-2价值观。为了评估所有因素对小麦烹调特性的影响(总有机物:TOM和比色法测试值),使用了简单的多元回归分析来找到方程,这些方程可以最佳地预测各种质量参数与小麦烹调特性之间的关系。该模型涉及两个变量;硬粒小麦样品的玻璃化度和干面筋含量以及面包小麦样品的SDS沉降测试值和小麦蛋白质含量导致TOM值的R-2最高。

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