利用近红外技术结合化学计量学的方法建立了稻谷新陈度近红外光谱定量模型。 对90个稻谷样本, 通过近红外光谱仪扫描获得了从950～1 650 nm的光谱信息。 运用UNSCRAMBLER9.7软件进行计算, 选择全谱区, 结合偏最小二乘法(PLS)算法, 得到光谱最佳预处理方法为一阶导加Savizky-Golay平滑, 最佳主成分数为7。 进行内部交叉验证, 决定系数r2为0.967 9, 预测误差为54.51, 且预测结果与真实值通过t检验, 说明模型是可行的。 为稻谷新陈度的快速无损检测提供了一种新的方法。

A prediction model of paddy storage time was established based on near infrared reflectance(NIRS)and chemometrics. A spectroradiometer was used for collecting spectra in the wavelength range from 950 to 1 650 nm. The NIR spectra were collected from 90 samples of paddy. The best pretreatment method was obtained while choosing the total spectra area combined with PLS using the UNSCRAMBLER 9.7. The best pretreatment method is first derivative combined with S. Golay, and the number of principal components is 7. The model is feasible, because the r2 is 0.967 9, RMSEP is 54.51 and the result of T-test is passable while validation method is cross validation. In this paper, a feasible method is established to measure the storage time of paddy based on near infrared reflectance(NIRS)and chemometrics.