基于多项式拟合对煎炸油质量的预测

解久莹; 吉静筠; 李裕梅; 杨雪莲; 曹雁平

doi:10.13386/j.issn1002-0306.2019.14.002

基于多项式拟合对煎炸油质量的预测

解久莹^1,2,
吉静筠²,
李裕梅^3,,
杨雪莲^1,2,,
曹雁平^1,2,

1. 北京市食品营养与人类健康高精尖创新中心, 北京工商大学食品学院, 北京 100048;
2. 北京工商大学食品学院, 食品质量与安全北京实验室, 北京 100048;
3. 北京工商大学理学院, 北京 100048

基金项目:

北京市科技计划项目(Z171100001317004)。

详细信息

作者简介:
解久莹(1994-),女,硕士研究生,研究方向:食品安全检测与控制,E-mail:2324656601@qq.com。

通讯作者:
李裕梅(1976-),女,博士,副教授,研究方向:机器学习与统计应用,E-mail:liyum@th.btbu.edu.cn

杨雪莲(1980-),女,博士,副教授,研究方向:食品安全检测与控制,E-mail:yangxuelian@th.btbu.edu.cn

曹雁平(1961-),男,博士,教授,研究方向:食品化学与安全,E-mail:caoyp@th.btbu.edu.cn。

中图分类号: TS229
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出版历程
- 收稿日期: 2018-11-08
- 网络出版日期: 2020-11-12
- 刊出日期: 2019-07-14

Prediction of Frying Oil Quality Based on Polynomial Curve Fitting

1. Beijing Advanced Innovation Center for Food Nutrition and Human Health, School of Food and Chemical Engineering, Beijing Technology and Business University(BTBU), Beijing 100048, China;
2. School of Food and Chemical Engineering, Beijing Technology and Business University, Beijing Laboratory of Food Quality and Safety, Beijing 100048, China;
3. School of Science, Beijing Technology and Business University, Beijing 100048, China

摘要

摘要: 通过测定煎炸油理化指标确定煎炸油质量过程较为繁琐,因此寻找一种方法快速确定煎炸油质量情况十分必要。通过在160、175、190、205、220 ℃等五个温度下进行大豆油煎炸实验获得酸价、羰基价、极性组分等理化指标数据,进行多项式拟合建模。在初次拟合模型的基础上,对删除学生化残差绝对值 > 3或Cook距离 > 1的异常数据进行剔除,并用其余数据再次进行多项式拟合建模,使用模型预测其他未知时间点的理化指标值。酸价和极性组分均采用二次多项式拟合,羰基价采用三次多项式拟合,通过拟合结果,R²在0.8628以上。各温度分别取三个未知油样,测定它们的三个理化指标作为测量值,计算各模型获得的拟合方程作为拟合值进行验证实验,相关性达到0.9968以上。表明模型稳定,能够很好地对未知油样进行预测。
- 煎炸油 /
- 酸价 /
- 羰基价 /
- 极性组分 /
- 多项式拟合建模 /
- 指标预测
Abstract: It is cumbersome to determine the quality of frying oil by measuring the physical and chemical indicators of frying oil.It is necessary to find a way to quickly determine the quality of frying oil. The physicochemical index data such as acid value, carbonyl value and polar component were obtained by performing soybean frying experiments at five temperatures of 160, 175, 190, 205, and 220℃, and polynomial fitting modeling was performed. On the basis of the initial fitting model, the abnormal data with the absolute value of the studentized residual > 3 or the Cook distance > 1 were deleted, and the polynomial fitting modeling was performed again with the remaining data. The model was used to predict the physical and chemical physics of other unknown time points. Both the acid value and polar component were fitted by a quadratic polynomial, and the carbonyl value was fitted by a cubic polynomial. By fitting the result, R² was above 0.8628. Three unknown oil samples were taken at each temperature, and their three physical and chemical indicators were measured as the measured values, the fitting equation obtained by each model was calculated as the fitted value for the verification experiment, and the correlation was above 0.9968. It indicated that the model was stable and could forecast the unknown oil sample well.
- frying oil /
- acid value /
- carbonyl value /
- polar component /
- polynomial curve fitting /
- indicator prediction