淀粉是玉米产量和品质的重要性状,在群体水平准确测定淀粉含量是研究淀粉遗传与生理的重要基础。本文以230份玉米自交系为样本,采用旋光法与一阶导数及去一条直线的光谱预处理法,构建玉米粉样淀粉含量的近红外分析(NIRS)模型,可显著提高籽粒淀粉含量预测的准确性。该模型的定标标准偏差(RMSEE)、交叉验证标准偏差(RMSECV)、外部验证标准偏差(RMSEP)、定标相关系数(R2cal)、交叉验证相关系数(R2cv)、外部验证相关系数(R2cv)分别为0.609、0.722、0.738、0.909、0.864和0.854。建立的玉米粉样NIRS模型可将预测值与化学值偏差控制在1.7%内,能够准确定量分析玉米籽粒淀粉含量，应用于育种材料早期筛选及群体水平粗淀粉分析。
英文摘要:
Starch content is an important trait of maize (Zea mays L.) kernels as it accounts for the seed yield and quality. Analysis starch content accurately at the population level is the important foundation when we study genetic and physiological of starch quality. In this paper, 230 maize inbred lines were set as samples, using the method of polarimeter and pre-treatment of the first derivative add minus one line separately to establish and optimize a Near-infrared spectroscopy (NIRS) model of maize starch content successfully, which can improve the accuracy of the prediction significantly. Of the model, the calibration standard deviation (RMSEE) is 0.609, the cross-validation standard deviation (RMSECV) is 0.722, the external verification standard deviation (RMSEP) is 0.738, the calibration correlation coefficient (R2cal) is 0.909, the cross-validation correlation coefficient (R2cv) is 0.864, and the external verification correlation coefficient (R2cv) is 0.854. Of the model, the deviation between the predicted value and the chemical value can be controlled within 1.7%, which can improve the accuracy largely when it was used in quantitative analysis of grain starch content and then can be applicated in breeding inbred line selection or crude starch content analysis at the group level.
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