Yan Jing, Jiao Zibin, Song Lifan, Yao Surong, Jiménez Antonio, Peng Changmeng, Qin Wen
College of Food Science, Sichuan Agricultural University, 625014 Ya'an, China.
College of Food Science, Sichuan Agricultural University, 625014 Ya'an, China.
Food Chem. 2025 Sep 1;485:144481. doi: 10.1016/j.foodchem.2025.144481. Epub 2025 Apr 28.
This study applies ultrasonic detection technology combined with temperature compensation models to evaluate the quality of thermally oxidized rapeseed oil, which was continuously heated at 180 °C for 72 h. The results indicate that the effects of heating treatment and increased detection temperature on ultrasonic indicators exhibit opposite trends, with the impact of detection temperature on ultrasonic signals being significantly higher than that of thermal treatment. The total polar component prediction model, which integrated the random forest algorithm with the global temperature compensation model, exhibited the best predictive performance, with external validation results of R = 0.906, RMSE = 1.402, and MAE = 1.007. These findings confirm that the temperature compensation mechanism effectively mitigates the temperature effects during detection. This proposed temperature compensation mechanism exhibits significant potential for application in the edible oil production industry, aiming to achieve online, rapid, and non-destructive monitoring of oil quality.
本研究应用超声检测技术并结合温度补偿模型,对在180℃连续加热72小时的热氧化菜籽油的品质进行评估。结果表明,加热处理和检测温度升高对超声指标的影响呈现相反趋势,检测温度对超声信号的影响显著高于热处理。将随机森林算法与全局温度补偿模型相结合的总极性成分预测模型表现出最佳的预测性能,外部验证结果为R = 0.906、RMSE = 1.402和MAE = 1.007。这些发现证实温度补偿机制有效地减轻了检测过程中的温度影响。所提出的温度补偿机制在食用油生产行业具有显著的应用潜力,旨在实现油脂品质的在线、快速和无损监测。