基于近红外技术测定不同鲜肉中挥发性盐基氮含量

Detection of total volatile basic nitrogen in different kinds of meat based on near infrared spectroscopy

中文关键词:  近红外光谱技术  挥发性盐基氮  偏最小二乘算法  鲜肉

英文关键词:near infrared spectroscopy  total volatile basic nitrogen  partial least squares  fresh meat

中文摘要:

      目的 应用近红外光谱技术快速检测猪肉、羊肉和牛肉的挥发性盐基氮含量。方法 本实验采集各种肉类的近红外光谱, 运用偏最小二乘法(partial least squares, PLS), 光谱经多种不同预处理方式并通过比较选择最优处理后, 建立挥发性盐基氮含量的近红外校正模型。结果 猪肉选择一阶导、S-G平滑方式, 羊肉选择二阶导、S-G平滑方式, 牛肉选择一阶导、Norris平滑方式。猪肉、羊肉和牛肉的挥发性盐基氮建模集相关系数分别为0.9069、0.9106和0.9587, 方根误差分别为1.12、1.64和2.20。结论 所建立的模型取得了较好的结果, 验证了近红外光谱技术对猪肉、羊肉和牛肉挥发性盐基氮进行定量分析的巨大应用潜力。

英文摘要:

      Objective To quickly detect total volatile basic nitrogen (TVB-N) in pork, mutton and beef by near infrared spectroscopy. Methods The near infrared spectra of all kinds of meat were collected, and the partial least squares (PLS) spectrum was used. The near infrared correction model of the content of TVB-N was established after a variety of different preprocessing methods and comparative selection of the optimal treatment. Results The model of pork was optimized by selecting the first derivative and S-G smoothing method, the model of mutton was optimized by selecting the second derivative and S-G smoothing method, and the model of beef was optimized by selecting the first derivative and Norris smoothing method. The TVB-N calibration coefficients of pork, mutton and beef were 0.9069, 0.9106 and 0.9587, respectively, with the variances of 1.12, 1.64 and 2.20, respectively. Conclusion The established model achieves good results, which verifies the great potential of near infrared spectroscopy for quantitative analysis of TVB-N in pork, mutton and beef.