Faculty of Commodity Science, Poznań University of Economics, al. Niepodległości 10, 61-875 Poznań, Poland.
Universidade do Algarve, FCT, DQF, and CIQA, Campus de Gambelas, Faro 8005-139, Portugal.
Food Chem. 2015 Nov 15;187:416-23. doi: 10.1016/j.foodchem.2015.04.046. Epub 2015 Apr 21.
Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1).
采用红外光谱技术和化学计量学方法研究了橄榄油、葵花籽油和菜籽油的氧化。使用过氧化物值和 FT-MIR ATR 和 FT-NIR 透射光谱监测了在 60°C 下油的加速氧化降解。主成分分析 (PCA) 有助于可视化和解释氧化过程中发生的光谱变化。多变量曲线分辨 (MCR) 方法在近红外和中红外光谱矩阵中发现了三个光谱分量，分别对应于氧化产物、饱和和不饱和结构。使用基于近红外 (R(2) = 0.890)、中红外 (R(2) = 0.707) 和近红外和中红外组合 (R(2) = 0.747) 数据的 MCR 评估，发现过氧化物值与氧化产物的贡献之间存在良好的定量关系。使用偏最小二乘 (PLS) 回归建立的预测过氧化物值的校准模型，其特征在于中红外 (R(2) = 0.701，RPD = 1.7)、近红外 (R(2) = 0.970，RPD = 5.3) 和近红外和中红外组合数据 (R(2) = 0.954，RPD = 3.1)。
