用近红外透射光谱技术测定精米直链淀粉含量研究

Study on Calibration of Polished Rice Amylose By NITS

应用近红外透射光谱技术,采用3种不同回归统计分析方法建立精米直链淀粉含量(AC)定量分析预测模型。结果表明,用改进的最小二乘法(MPLS)、偏最小二乘法(PLS)和主成分回归法(PCR)进行校正时,校正标准误(SEC)、交叉检验标准误(SECV)分别为0.9524、1.2494(MPLS),0.9372、1.2426(PLS),1.2734、1.5828(PCR)。校正相关系数(RSQ)和交叉验证相关系数(1-VR)分别为0.9640、0.9383(MPLS),0.9654、0.9395(PLS),0.9362、0.9016(PCR)。由此可见,用PLS技术建立PC回归方程最佳。近红外透射光谱法作为一种快速而准确的定量分析手段,在米厂品质管理、人米品质分析和人米贸易检测上有广阔的应用前景。

With the technique of near infrared transmittance spectroscopy(NITS), the predicted models for quantitative analysisof amylose content in ground were studied by using three different regression techniques.The results indicated that by the standarderrors (SEC for calibration, SECV for cross validation) and determination coefficiets (RSQ for calibration and-VR for validation)the modelscould be calibrated by using modified Partial Least Square (MPLS), Partial Least Square (PLS), and Principal Component Regression(PCR).The SEC and SECV were 0.1258, 0.1340 for MPLS;0.1177, 0.1275 for PLS; 0.1207 and 0.1275 for PCR; while RSQ and l-VR were respectively 0.9941 and 0.9933 for MPLS; 0.9950 and 0.9942 for PLS;0.9947 and 0.9942 for PCR.These results indicatedthat PLS was the best statistic method for calibration of amylose chent by MITS.As a rapid and acuracy measurement, the NITSmethod showed a potential application in quality control of rice mill, quality analysis of rice and trade verification of rice.