College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, Hubei, People's Republic of China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), Wuhan 430023, People's Republic of China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, Wuhan 430023, People's Republic of China.
College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, Hubei, People's Republic of China.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 May 15;293:122477. doi: 10.1016/j.saa.2023.122477. Epub 2023 Feb 10.
The health risks posed by harmful substances resulting from the thermal degradation of frying oils are of great concern. Characteristic peak intensity ratios (PIRs) screened from Raman spectra were used to characterize the thermal degradation. High correlation coefficients between PIRs and acid values (AVs) of 0.972 (linear fitting), 0.984 (logarithmic function fitting), and 0.954 (linear fitting) for fried soybean oil, canola oil, and palm oil, were obtained at the PIRs of I/I, I/I, and I/I, respectively. The highly correlated PIRs common to the three oils were determined by Pearson's correlation coefficient combined with heat maps. To accommodate both linear and nonlinear features, a global model for predicting AVs of multi-varieties frying oils was constructed using a least-squares support vector machine algorithm, and the results performed well with a root mean square error of prediction of 0.016 and a ratio of prediction to deviation of 11.351. The whole results demonstrate that Raman spectroscopy could characterize the thermal degradation and has excellent quantitative analysis ability for food control based on AV in frying oils, thus providing a new approach to quality control of frying oils.
食用油热降解产生有害物质对健康造成的危害引起了极大关注。本研究采用拉曼光谱筛选出特征峰强度比(PIR)来对热降解进行特征化。在三种油(大豆油、菜籽油和棕榈油)中,PIR 与酸值(AV)的线性拟合、对数函数拟合和线性拟合的相关系数分别为 0.972、0.984 和 0.954。通过皮尔逊相关系数结合热图确定了三种油共有的高度相关的 PIR。为了兼顾线性和非线性特征,使用最小二乘支持向量机算法构建了用于预测多品种煎炸油 AV 的全局模型,预测均方根误差为 0.016,预测与偏差比为 11.351,结果表现良好。整体结果表明,拉曼光谱可以对热降解进行特征化,并且对基于煎炸油 AV 的食品控制具有出色的定量分析能力,为煎炸油的质量控制提供了新方法。