Assessment of Visible Near-Infrared Hyperspectral Imaging as a Tool for Detection of Horsemeat Adulteration in Minced Beef
Assessment of Visible Near-Infrared Hyperspectral Imaging as a Tool for Detection of Horsemeat Adulteration in Minced Beef
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DOI：
10.1007/s11947-015-1470-7
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发表时间：
2015-05-01
影响因子：
5.6
通讯作者：
Liu, Shu
中科院分区：
文献类型：
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作者：
Kamruzzaman, Mohammed;Makino, Yoshio;Liu, Shu
首次研究了一种可见近红外(Vis-NIR)高光谱成像系统(400-1000 nm)，用于牛肉末掺假的快速无损检测。切碎的牛肉样品以大约2%的增量掺入马肉，掺杂量从2%到50%(w/w)不等。通过内部完全交叉验证的偏最小二乘回归(PLSR)建立和优化校正模型，然后使用独立的验证集进行外部验证。采用导数、标准正态变量(SNV)和乘性散射校正(MSC)等光谱前处理技术，考察了光谱变化对预测牛肉末掺假的影响。建立的基于原始光谱的PLSR模型用于校正、交叉验证和预测的决定系数(R(2))分别为0.99、0.99和0.98，标准误差为1.14、1.56和2.23%。使用由最佳PLSR模型得到的回归系数选择了四个重要的波长(515、595、650和880 nm)。通过使用这些重要波长，开发了一种图像处理算法来预测样品整个表面每个像素的掺杂程度。结果表明，高光谱成像与多变量分析相结合可以成功地作为一种快速检测肉末掺假的技术。
For the first time, a visible near-infrared (Vis-NIR) hyperspectral imaging system (400-1000 nm) was investigated for rapid and non-destructive detection of adulteration in minced beef meat. Minced beef meat samples were adulterated with horsemeat at levels ranging from 2 to 50 % (w/w), at approximately 2 % increments. Calibration model was developed and optimized using partial least-squares regression (PLSR) with internal full cross-validation and then validated by external validation using an independent validation set. Several spectral pre-treatment techniques including derivatives, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied to examine the influence of spectral variations for predicting adulteration in minced beef. The established PLSR models based on raw spectra had coefficients of determination (R (2)) of 0.99, 0.99, and 0.98, and standard errors of 1.14, 1.56, and 2.23 % for calibration, cross-validation, and prediction, respectively. Four important wavelengths (515, 595, 650, and 880 nm) were selected using regression coefficients resulting from the best PLSR model. By using these important wavelengths, an image processing algorithm was developed to predict the adulteration level in each pixel in whole surface of the samples. The results demonstrate that hyperspectral imaging coupled with multivariate analysis can be successfully applied as a rapid screening technique for adulterate detection in minced meat.