玉米粉淀粉含量近红外模型建立与优化

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。研究标明，该模型可显著提高子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（R_cal²）、交叉验证相关系数（R_cv²）、外部验证相关系数（R_cv²）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子粒淀粉含量，应用于育种材料早期筛选及群体水平粗淀粉分析。

Establishment and Optimization of a Near-Infrared Model of Maize Starch Content

In this paper, 230 maize inbred lines were set as samples, using the method of polarimeter and pretreatment 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 (R_cal²) is 0.909, the cross-validation correlation coefficient(R_cv²) is 0.864, and the external verification correlation coefficient(R_cv²) 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 application in breeding inbred line selection or crude starch content analysis at the group level.