基于高光谱成像的干燥胡萝卜片水分及类胡萝卜素含量无损检测和可视化分析

利用不同波长范围的高光谱成像系统,以热风干燥过程中胡萝卜片水分和类胡萝卜素含量为研究对象,结合多元数据统计分析和化学计量学,分别构建基于偏最小二乘和支持向量机(support vector machine,SVM)算法的无损预测模型,并进行可视化分析。结果表明,水分和类胡萝卜素含量预测模型中,基于400~1000 nm波长范围下多元散射校正的高光谱信息构建的SVM预测模型效果相对最优,对应的预测集决定系数R2 P分别为0.984和0.911,预测集均方根误差(root mean square error of prediction,RMSEP)分别为0.380 g/g和34.836 mg/100 g。经连续投影算法提取特征波长后,最优模型R2 P分别为0.962和0.898,RMSEP分别为0.612 g/g和37.544 mg/100 g,模型剩余预测残差均大于3,精确度和稳定性良好。在最优预测模型的基础上,通过伪彩色成像重现了干燥过程中样品水分及类胡萝卜素的空间分布。实验结果证实高光谱成像技术可以用于胡萝卜片干燥过程水分和类胡萝卜素含量的无损检测,为后续在线检测和胡萝卜片干燥加工提供理论基础和技术支持。

Hyperspectral Imaging for Non-destructive Determination and Visualization of Moisture and Carotenoid Contents in Carrot Slices during Drying

In this experiment,hyperspectral images in different wavelength ranges were acquired for carrot slice samples during hot air drying.Subsequently,using multivariate statistical analysis combined with chemometrics,a predictive model for the non-destructive determination of moisture content(MC)and carotenoid content(CC)in samples was developed separately based on partial least squares(PLS)and support vector machine(SVM)algorithm.The results showed that the SVM models developed using multiplicative scatter correction(MSC)in the 400–1000 nm had the best prediction performance for both MC and CC with coefficient of determination for prediction(R2 P)of 0.984 and 0.911,and root mean square error for prediction(RMSEP)of 0.380 g/g and 34.836 mg/100 g,respectively.The optimal models with the feature wavelengths selected by successive projections algorithm showed R2 P of 0.962 and 0.898 and RMSEP of 0.612 g/g and 37.544 mg/100 g for MC and CC,respectively.The residual predictive deviation(RPD)in the new models was over 3,indicating good accuracy and stability.Moreover,the spatial distribution of moisture and carotenoid during the drying process were generated and visualized as pseudo-color images.The results indicated that the hyperspectral imaging could be used to effectively predict the MC and CC in carrot slices,demonstrating the potential of hyperspectral imaging as an analytical tool in quality control of carrot slices during drying.