中文摘要：

选用49份不同蛋白质和棉酚含量的陆地棉种质资源和188份陆地棉重组近交系为材料,以多年份、多地点种植收获的种子材料组成原始样品集,分别对棉仁粉中蛋白质含量和棉酚含量进行化学测定,采用改进的偏最小二乘法（Modified PLS）和（2,4,4,1）的数学转换方法建立近红外反射光谱（NIRS）定标模型,以寻找棉籽蛋白质含量和棉酚含量的快速测定方法。结果表明,蛋白质含量的定标决定系数（RSQ=0.933）和交叉检验决定系数（1-VR=0.929）较高,定标标准误差（SEC=0.623）和交互校验标准误差（SECV=0.638）较小,预测模型的建模效果较好,可替代化学分析。棉酚含量预测模型的RSQ,1-VR,SEC和SECV分别为0.836,0.811,0.074和0.079,模型预测效果略差于蛋白质模型,但仍可用于棉仁粉中棉酚含量的测定。

英文摘要：

Near-infrared reflectance spectroscopy （NIRS） was used as a rapid and nondestructive method to determine the protein content and gossypol content in cotton kernel powder samples, using 49 upland cotton （Gossypium hirsutum L. ） germplasms and 188 recombinant inbred hines （RILs）. The cottonseed samples harvested from the upland cotton germplasms and RILs grown in different cotton growing regions in different years were analyzed chemically for protein and gossypol contents, as well as scanned in the reflectance mode of a scanning monochromator. Using ISI software for scanning and data analysis, protein and gossypol calibration equations were obtained with a standard normal variate ＋ detrending scatter correction and a 2, 4, 4, 1 math treatment and modified partial least square （MPLS） as the regression method. The protein content calibration results revealed that the multiple correlation coefficients （RSQ） and statistic 1-variance ratio （1-VR） for the determination of protein content in cottonseed kernels were 0. 933 and 0. 929, respectively, and its standard error of calibration （SEC） and standard error of cross validation （SECV） were 0. 623 and 0. 638, respectively. As the calibration equations were judged by the calibration RSQ （or 1-VR） and SEC （or SECV）, the results indicated that NIRS is comparable to chemical methods in both accuracy and prediction and is reliable in the determination of protein content in cottonseed kernels. However, the RSQ, SEC, 1-VR and SECV for gossypol content determination of NIRS were 0. 836, 0. 811, 0. 074 and 0. 079, respectively. Although it was weaker than that of protein content, the NIRS method is still good enough for the determination and prediction of the gossypol content in cotton- seed kernels. Therefore, NIRS models were successfully developed for protein content and gossypol content analysis of cotton kernel powder sample in the present study and they could be introduced into the cotton germplasm evaluation and breeding program for