为了实现快速无损地检测猪肉新鲜度的目的,应用近红外光谱法测定猪肉新鲜度重要指标—挥发性盐基氮(TVB-N)的含量。猪肉原始光谱经标准偏差归一化方法(SNV)预处理后,用联合区间偏最小二乘法(siPLS)建立猪肉预处理后光谱和TVB-N含量的校正模型并与经典偏最小二乘法(PLS)模型、间隔偏最小二乘法(iPLS)模型作比较。试验结果表明,利用联合区间偏最小二乘法所建的预测模型最佳,其校正集相关系数(Rc)和交互验证均方根误差(fRV)分别为0.8332和3.75,预测集的相关系数(Rp)和预测均方根误差(fRP)分别为0.8238和4.17。研究结果表明利用近红外光谱和联合区间偏最小二乘法可以快速地测定猪肉中挥发性盐基氮的含量。

To non-destructively determine the freshness of pork rapidly,near-infrared (NIR) spectroscopy was applied to quantitative the content of total volatile basic nitrogen (TVB-N) in pork which was an important index of pork freshness. The raw spectra of pork was preprocessed by the normaliyation method of standard deviation (SNV). Synergy interval partial least squares (siPLS) algorithm was used to build the precessed spectra of pork and calibration model of TVB-N content and that model was compared with the models respectively built by classical partial least squares (PLS) and interval PLS (iPLS) algorithms. Experimental results showed that the performance of siPLS model was the best in contrast to PLS and iPLS. The optimal calibration model was achieved with correlation coefficient (Rc=0.8332),root mean square error of cross-validation (fRV=3.75) in calibration set and correlation coefficient (Rp=0.8238),root mean squared error of prediction (fRP=4.17) in prediction set. This study demonstrated that NIR spectroscopy with siPLS can be successfully applied as a rapid method to determine the TVB-N of pork rapidly.