玉米杂交种品质性状的近红外光谱分析技术研究

以我国常用玉米自交系、杂交种样品为材料，采用偏最小二乘（PLS）回归法，建立了近红外反射光谱测定玉米完整籽粒的粗蛋白、粗淀粉和油分含量的校正模型。并利用40个玉米杂交后代材料对3个模型的实际预测效果进行了验证，预测值与化学值间的相关系数（r）可达0．98（粗蛋白）、0．93（粗淀粉）和0．97（油分），最大相对误差仅为2．46％（粗淀粉）～7％（油分）。文章还从理论上研究了以数量相对较少的亲本自交系为建模样品、建立可适用于分析大量杂交种样品的近红外数学模型的可行性，提出了作物近红外光谱某些特征具有遗传性这一新的观点。

Predicting the Chemical Composition of Intact Kernels in Maize Hybrids by Near Infrared Reflectance Spectroscopy

Intact-kernel samples of normal maize inbred lines and hybrids were collected from field experiments of three locations. Calibration equations were developed by partial least square regression (PLS) of chemical values of near infrared reflectance spectroscopy(NIRS) data and tested through both cross and external validation. In addition, 40 progenies of F_1 and F_2 generation not included in calibration and validation sets were verified to further evaluate the reliability of three calibration equations. The authors found the coefficients of correlation(r) of 0.98, 0.93 and 0.97 between NIRS predicted and actual protein, starch and oil content in these materials, respectively. However, the greatest relative errors were 2.7% (protein), 2.46% (starch) and 7% (oil). Thus, the accuracy of prediction could be comparable to chemical methods. The feasibility of developing NIRS equations with samples of inbred lines to determine grain quality of hybrids was also examined. The analysis of principal components of spectrum of the inbred lines and hybrids supported a new theory that plant spectrum properties could be heritable.