冷却肉微生物污染和肉色变化的Vis/NIR光谱无损检测
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“十二五”国家科技支撑计划资助项目(2012BAH04B00);公益性行业(农业)科研专项经费资助项目(201003008);中央高校基本科研业务费专项资金资助项目(2013YJ007)


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

    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400~1100nm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0.600lg CFU/g和0.702lg 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。

    Abstract:

    Vis/NIR spectroscopy was used to detect TVC and color of chilled pork rapidly and non-invasively. Vis/NIR scattering image in the range of 400nm to 1100nm 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 (Rv) 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 0.702lg CFU/g, respectively. For color L*, the prediction model based on combination β and δ could give satisfactory results with Rv of 0.930 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.

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张雷蕾,彭彦昆,刘媛媛,赵娟,郭辉.冷却肉微生物污染和肉色变化的Vis/NIR光谱无损检测[J].农业机械学报,2013,44(Supp1):159-164. Zhang Leilei, Peng Yankun, Liu Yuanyuan, Zhao Juan, Guo Hui. Non-invasive Detection to TVC and Color of Chilled Pork Based on Vis/NIR Spectroscopy[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(Supp1):159-164.

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  • 在线发布日期: 2013-10-22
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