基于近红外高光谱成像技术的新鲜与冻融牛肉鉴别技术研究

Application of near infrared hyperspectral imaging to differentiate between fresh and frozen- thawed beef

研究运用近红外高光谱成像技术对新鲜与冻融的牛肉进行判别。将45个牛肉样品随机分为两组,第一组25个为新鲜样品,第二组20个作为冻融样品。本实验通过高光谱成像仪获取样品的光谱图像数据,并对图像校正处理后进行分割,分离出感兴趣区域（ROI,Region of Interest）。然后再提取感兴趣区域的平均光谱,并将其作为样品的高光谱数据。经过对高光谱数据的多元散射校正（MSC,Multiplicative Scatter Correction）预处理,应用偏最小二乘回归（PLSR,Partial Least Squares Regression）,在全光谱范围（950~1500 nm）构建了本实验的最优模型。实验表明,该模型具有较高的预测精度,其判别正确率为94.4%。因此,近红外高光谱成像技术对冻融牛肉的鉴别检测具有适用性。

The objectives of this research were to develop a hyperspectral imaging system to differentiate between fresh and frozen- thawed beef fillets.A total of 45 beef fillets were randomly divided into two groups,including 25 fresh and 20 frozen- thawed samples.In this study,spectral imaging dates were obtained by hyperspectral imaging system.All images were calibrated for reflectance,followed by segmentation to obtain the region of interest（ ROI）,and then the average spectral data was generated from the ROI images.Through multiplicative scatter correction（ MSC） pretreatment to hyperspectral imaging data,optimal model of this test was built in range of full spectrum（ 950~1500 nm） by means of partial least square regression（ PLSR）.The results showed that,the model had high prediction accuracy,the correct classification rate was 94.4%,and the near- infrared hyperspectral imaging technology was suit for recognizing to frozen- thawed beef.