冷却肉微生物污染和肉色变化的Vis/NIR光谱无损检测

Non-invasive Detection to TVC and Color of Chilled Pork Based on Vis /NIR Spectroscopy

利用可见/近红外光谱技术对冷却肉菌落总数和颜色进行快速、无损检测。采用400~1 100 nm可见/近红外光谱成像系统,获取54个冷却肉样本表面的光谱图像,采用主成分分析结合马氏距离方法对异常光谱进行判别及剔除。通过Gompertz分布函数对散射特征曲线进行拟合,得到表征光谱信息的Gompertz参数,结合支持向量机算法建立冷却肉菌落总数和肉色L*的预测模型。α、β、θ、δ组合和α、β、δ组合建模对细菌总数预测效果最好,预测相关系数分别为0.937和0.935,预测标准差为0.600 lg CFU/g和0.702 lg CFU/g。β、δ组合建模对肉色L*预测效果较好,预测相关系数达到0.930,预测标准差为1.515。研究结果表明利用Vis/NIR光谱散射特征结合支持向量机可以实现冷却肉品质的快速、高效、无损伤检测。

Vis /NIR spectroscopy was used to detect TVC and color of chilled pork rapidly and noninvasively.Vis/NIR scattering image in the range of 400 nm to 1 100 nm were collected from 54 chilled pork samples.The scattering profiles were fitted accurately by four-parameter Gompertz function.The TVC and color L*prediction models were built with support vector machines( SVM) regression.The regression coefficient( R v) of combination α,β,θ,δ and combination α,β,δ were 0.937 and 0.935,and the standard error of prediction( SEP) were 0.600 lg CFU/g and 0.702 lg CFU/g,respectively.For color L*,the prediction model based on combination β and δ could give satisfactory results with R v of0.930 and SEP of 1.515.The results demonstrated that Vis/NIR spectroscopy combined with SVM was precise and potential for valid,rapid,non-invasive detection of chilled pork.