基于高光谱成像的羊肉掺假可视化无损定量检测

目的：快速、准确检测羊肉掺假。方法：利用可见—近红外(400~1 000 nm)和短波近红外(900~1 700 nm)高光谱成像仪对羊肉中掺假不同比例的鸭肉进行数据采集，比较两个波段范围内不同光谱预处理方法的偏最小二乘法(PLS)建模效果，最终在可见—近红外波段选择归一化预处理方法，在短波近红外波段选择标准正态变量变换(SNV)预处理方法。分别对两个波段的光谱数据进行最优的预处理后，采用连续投影算法(SPA)、竞争性自适应重加权算法(CARS)、区间随机蛙跳算法(iRF)和组合区间偏最小二乘法(SiPLS)对特征波长进行选取。结果：在短波近红外(900~1 700 nm)波段采用SNV-SPA-PLS模型的羊肉掺假预测效果最好，预测集决定系数为0.968 4，预测标准偏差为0.058 2，预测集相对分析误差为5.625 4，并得到较好的图像反演结果。结论：利用不同波段的高光谱成像技术可实现对羊肉掺假的快速无损定量检测。

Visualization of lamb adulteration based on hyperspectral imaging for non-destructive quantitative detection

Objective: This study aimed to establisha rapid and accurate prediction method of lamb adulteration by using visible/near-infrared (400~1 000 nm) and short-wave near-infrared (900~1 700 nm) hyperspectral imaging techniques.Methods: The data acquisition of lamb adulterated with different proportions of duck meat using visible/near-infrared (400~1 000 nm) and short-wave near-infrared (900~1 700 nm) hyperspectral imagers was performed to compare the effect of partial least squares (PLS) modeling with different spectral preprocessing methods in the two band ranges. Then the normalized preprocessing method was selected in the visible-NIR band, and the standard normal variate transformation (SNV) preprocessing method was selected in the short-wave infrared band. After the optimal preprocessing of the spectral data on to the two bands separately, the feature wavelengths were selected using the successive projections algorithm (SPA), the competitive adaptive reweighted sampling (CARS), the Interval random frog (iRF) and the Synergy intervals PLS (SiPLS).Results: The best lamb adulteration prediction using SNV-SPA-PLS model in the short-wave near-infrared (900~1 700 nm) bands, was achieved, and with the prediction set model evaluation coefficients of R2p=0.968 4, RMSEP=0.058 2, RPD=5.625 4, relaiable image inversion results were obtained.Conclusion: The rapid and nondestructive quantitative detection of lamb adulteration can be achieved by using hyperspectral imaging techniques in different wavebands.