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基于高光谱成像技术的培根中菌落总数预测模型研究
食品检测
2026/09/21
摘要：培根中菌落总数（（ TVC）超标会严重危害人体健康，为寻求一种快速、无损的TVC检测方法，将高光谱成像技术 应用于培根中TVC的定量分析。综合比较了多重散射法、导数法等预处理方法，最终采用多重散射法进行预处理，并建 立区间优化法最小二乘模型进行预测，得到了较好的预测结果，定标与预测的相关系数分别为0.808和0.808，交互验证 均方根误差分别为0.115和0.198。因此，结合iPLS的高光谱成像技术可用于培根中TVC的快速检测。
关键词：培根；菌落总数；高光谱成像；区间优化最小二乘
期刊：MATEC Web of Conferences
DOI：10.1051/matecconf/2016 6102009
设备：GaiaSorter
Research on the Forecast Model of Total Viable Count on Bacon Based on Hyper spectral Imaging Technique
Abstract：The total viable count (TVC) in bacon overweight can cause serious damage to human health .In order to find a rapid and nondestructive method of TVC, hyper spectral imaging technique was applied to quantitatively analysis of TVC on bacon .Comprehensively comparing the pretreatment method of multiple scattering, derivative method and so on ,finally the multiple scattering for pretreatment was used. And the interval optimization method of least squares model was set up to predict, and get a good prediction results .The correlation coefficient of the calibration and predictions respectively was 0.808 and 0.808 , interactive authentication root mean square error was 0.115 and 0.198 respectively. Therefore, hyper spectral imaging technique combining iPLS can be used for the rapid detection of TVC on bacon.
Keywords：bacon; total viable count; hyper spectral imaging; interval optimization least-squares
