高光谱无损检测辣椒粉中苏丹红浓度

为无损检测辣椒粉中苏丹红一号浓度 (C), 本文运用高光谱成像检测技术得到 120个含有不同 C的辣椒粉高光谱图像, 其中 60个作为校正集剩余为预测集, 采用连续投影算法(SPA)从校正集的海量光谱数据中优选出 45个特征波长, 再通过偏最小二乘回归法 (PLSR)、多元线性回归法 (MLR)和主成分回归法 (PCR)建立预测模型。结果表明, MLR模型较优, 其校正集相关系数为 0.998, 校正均方根误差为 0.737 3 μg/ml, 预测集相关系数为 0.987, 预测均方根误差为 1.921 3 μg/ml, 该方法可以实现辣椒粉中 C的无损检测。

Abstract

To detect the concentration of Sudan red No. 1 (C) in chili powders non-destructively, the hyper-spectral imaging technique was used to extract 120 chili powder images that had different C, including 60 for calibration set and rest for prediction set. Successive Projections Algorithm (SPA) was used to extract 45 effective wavelengths from large amount of spectra data in calibration set. Partial Least Squares Regression (PLSR), Multiple Linear Regression (MLR) and Principal Component Regression (PCR) were applied to set prediction models. As a result, better model to detect the C in chili powders was based on MLR. The Correlation Coefficient Calibration (Rc) and Root Mean Square Error of Calibration (ERMSC) were 0.998 and 0.737 3 μg/ml. The Correlation Coefficient Prediction (Rp) and Root Mean Square Error of Prediction (ERMSP) was 0.987 and 1.921 3 μg/ml. This demonstrates that the method can be successfully used for detecting the C in chili powders non-destructively.

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