China Agricultural University, College of Engineering, 17 Qinghua East Road, Haidian, Beijing 100083, China.
China Agricultural University, College of Engineering, 17 Qinghua East Road, Haidian, Beijing 100083, China.
Food Chem. 2017 Dec 15;237:1179-1185. doi: 10.1016/j.foodchem.2017.06.031. Epub 2017 Jun 19.
Total volatile basic nitrogen (TVB-N) content is one of the core indicators for evaluating freshness of duck meat. Visible and near-infrared (Vis/NIR) reflectance spectroscopy was implemented in this study to determine the TVB-N content in duck breast meat. Quantitative calibration models were built by partial least square regression (PLSR) between the spectral data and the measured TVB-N values. The different spectral pre-processing methods were employed and synergy interval partial least squares and principal component analysis methods were used to select important wavelengths. In comparison, the prediction model with full spectra after multiplicative scatter correction pre-processing yielded optimum results with a root mean squared error for the prediction set (RMSEP) of 1.060mg/100g and a correlation coefficient (R) of 0.859. The results of this study demonstrated the feasibility of the quantification method for total volatile basic nitrogen (TVB-N) content in duck meat based on Vis/NIR spectroscopy technique as an objective tool.
总挥发性碱性氮（TVB-N）含量是评估鸭肉新鲜度的核心指标之一。本研究采用可见近红外（Vis/NIR）反射光谱法测定鸭肉中的 TVB-N 含量。通过偏最小二乘回归（PLSR）建立光谱数据与实测 TVB-N 值之间的定量校准模型。采用不同的光谱预处理方法，并采用协同区间偏最小二乘和主成分分析方法选择重要波长。相比之下，经全谱乘性散射校正预处理后的预测模型具有最佳结果，预测集的均方根误差（RMSEP）为 1.060mg/100g，相关系数（R）为 0.859。本研究结果表明，基于 Vis/NIR 光谱技术的鸭肉总挥发性碱性氮（TVB-N）含量定量方法具有可行性，可作为一种客观工具。
