K value is an important freshness index.It indicates nucleotide degradation,which is usually employed to assess meat spoilage.High-performance liquid chromatography (HPLC) is a common analytical method to estimate K value.However,it is time-consuming,destructive,and is not suitable to monitor pork freshness rapidly,non-invasively and in real-time.The feasibility of Terahertz (THz) spectroscopy in predicting K value of pork non-destructively was studied.The THz spectra (0.2 ～ 2 THz) of 80 pork samples with different freshness in the attenuated total reflectance (ATR) mode were acquired.Their K values were also measured by HPLC.Three models were established to predict K value,such as principal component regression (PCR),partial least squares regression (PLSR),and back propagation artificial neural network (BP-ANN) after the sample spectra were preprocessed by the first order derivative and filtered smoothly by Savitzky-Golay.Comparative research results showed that the nonlinear algorithm model of BP-ANN was the most superior way among three models whose root mean square error of prediction (RMSEP) was 14.36％ and correlation coefficient (RP) was 0.75 in the prediction set.The THz spectral combined with BP-ANN model can be used to predict pork K value although it was not perfect.Compared with HPLC,the THz spectral was non-destructive,rapid and simple.The research would lay a theoretical foundation for developing portable THz inspection equipment based on the THz spectroscopy.%K值是评价猪肉新鲜度的重要指标,能够反映猪肉内核苷酸的分解情况,从而评定肉的变质程度.一般采用高效液相色谱法测定K值,此方法过程耗时,需破坏被测样品,不能满足生产和流通环节的快速检测需求.本文利用太赫兹(THz)光谱分析技术无损检测猪肉K值,探索快速检测K值的可行性.在0.2～2 THz范围内,采用衰减全反射模式提取80份不同新鲜度的猪肉THz光谱数据,同时用高效液相色谱法测定每份样品的K值.THz光谱原始数据经过一阶微分和Savitzky-Golay平滑滤波后,分别用主成分回归(PCR)、偏最小二乘回归(PLSR)和反向传播神经网络回归(BP-ANN)建立了THz光谱预测猪肉K值的数学模型.研究表明:非线性BP-ANN模型预测精度最高,相关系数为0.75,均方根误差为14.36％;采用THz光谱数据BP-ANN模型能够检测猪肉的新鲜度K值.与HPLC方法相比,该方法具有快速、无损、简单的特点.
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