可见/近红外反射光谱法检测马铃薯抗性淀粉含量的研究

摘要

目的：利用可见/近红外反射光谱技术无损检测新鲜马铃薯茎块中抗性淀粉的含量。方法使用光谱仪获取新鲜马铃薯在345~1100 nm波段范围内的漫反射光谱；分别使用Savitzky–Golay(S-G)平滑处理、多元散射校正(MSC)法和一阶导数法(1st-D)对反射光谱进行预处理；对(S-G)反射光谱、MSC处理光谱和1st-D光谱使用逐步回归法判别法选择最优波长组合,建立多元线性回归模型,使用全交叉验证法验证模型。结果结果表明,可见/近红外反射光谱经过一阶导数处理后,确定的8个最优波长(370、569、576、866、868、886、922和963 nm)组合建立模型的校正和验证结果最好：模型的校正结果为相关系数 R=0.996,标准差 SEC=0.521%；模型交叉验证相关系数 Rcv=0.982,验证标准差 SECV=0.791%。结论可见/近红外反射光谱技术可以较好地预测新鲜马铃薯茎块的抗性淀粉含量,本研究可为可见近红外光谱技术在马铃薯功能成分的快速检测提供一定的技术基础。%Objective To determine whole potato tubers resistant starch (RS) content nondestructively by visualear infrared reflectance (VIS/NIR) spectroscopy. Methods The VIS/NIR reflectance spectrum were collected in 345~1100 nm using spectrography. The spectrum was pretreated by using Savitzky–Golay smoothing (S-G), multiplicative scattering correction (MSC) and first derivative (1st-Der) methods, respectively. The optimal wavelength combinations from S-G, MSC and 1st-Der spectrum were selected by step-wise discrimination method and used to establish multi-linear regression (MLR) models to predict the potato tuber RS contents. Then, the full cross validation were used to examine the effect of model. Results The results showed that the revise and verification result of MLR model based on 8 optimal wavelengths (370, 569, 576, 866, 868, 886, 922 and 963 nm) was the best after 1st-Der reflectance. It showed that correlation coefficient and standard deviation of revise result was 0.996 and 0.521%, respectively, the correlation coefficient and the standard error of cross validation (SECV) of cross validation (Rcv) were 0.982 and 0.791%,respectively. Conclusion The VIS/NIR reflectance spectral technique was useful for nondestructive determination of potato RS content. And this study could provide an efficient means for the rapid and nondestructive determination of potato starch quality.