近红外光谱技术预测猪肉的pH、嫩度和蒸煮损失  

Predicting pH values,tenderness and cooking loss of chilled pork based on near infrared spectroscopy

作　　者：董庆利[1] 熊成[1] 胡孟晗[1] 姚远[1] 

机构地区：[1]上海理工大学医疗器械与食品学院,上海200093

出　　处：《生物加工过程》2012年第6期51-55,共5页Chinese Journal of Bioprocess Engineering

基　　金：国家自然科学基金资助项目(31271896);上海市自然科学基金资助项目(12ZR1420500)

摘　　要：以冷却猪肉为研究对象,评价近红外光谱(NIR)技术用于肉类物理特性预测的可行性以及不同的光谱处理方法和建模方法对预测准确性的影响。试样取自排酸24 h的同一批猪胴体的小里脊肉,采集4 000～10 000cm-1的光谱。经外部验证的偏最小二乘(PLS)模型在预测pH时表现出良好的相关性(R2C=0.88,R2P=0.80,SEC=0.08,SEP=0.084),嫩度与蒸煮损失模型的相关性分别是R2C=0.50和0.57,R2P=0.34和0.50。在各种光谱预处理方法中,平滑处理结合多元散射校正(MSC)或标准正态变量变换(SNV)的效果最好。The feasibility by using near infrared spectroscopy （NIR） to predict physical attributes of chilled pork was focused on, and the effects of different methods of preprocessing spectra and modeling on the accuracy of the established models were studied. The samples were selected from the undercut of one batch carcasses after 24 h post-mortem,the diffuse reflectance spectrams with 4 000-10 000 cm-1 scan- ning information were collected for modeling. The results showed that the mathematical model for predic- ting pH values of chilled pork by PLS after validation test was proved and it had higher correlation param- eters （Rc^2=0. 88 ,Rp^2 =0. 80 ,SEC =0. 08 ,SEP =0. ones （Rc2 = 0. 50 and 0.57, Rp^2 = 0. 34 and 0.50）. 08 ）, while for tenderness and cooking loss with lower Moreover, the study also indicated that the method for smoothing spectra combined with multiplicative scatter correction （MSC） or standard normal variable transformation （SNV） was better than other methods of pre-treatment spectra.

关 键 词：近红外光谱 物理特性 猪肉 偏最小二乘法 

分 类 号：O657.3[理学—分析化学]