Predicting the chemical composition of intact kernels in maize hybrids by near infrared reflectance spectroscopy

文献类型： 外文期刊

第一作者： Wei, LR

作者： Wei, LR;Jiang, HY;Li, JH;Yan, YL;Dai, JR

作者机构：

关键词： maize;near infrared reflectance spectroscopy (NIRS);calibration equations;prediction;inbred lines;quality

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2005 年 25 卷 9 期

页码：

收录情况： SCI

摘要： 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 I 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 fines 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.

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