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中国精品科技期刊2020
马静静,田春,陈江琳,等. 基于拉曼光谱技术的山茶油不饱和度快速评价方法[J]. 华体会体育,2024,45(11):205−212. doi: 10.13386/j.issn1002-0306.2023060306.
引用本文: 马静静,田春,陈江琳,等. 基于拉曼光谱技术的山茶油不饱和度快速评价方法[J]. 华体会体育,2024,45(11):205−212. doi: 10.13386/j.issn1002-0306.2023060306.
MA Jingjing, TIAN Chun, CHEN Jianglin, et al. A Rapid Evaluation Method for Unsaturation of Camellia Oil Based on Raman Spectroscopy Technology[J]. Science and Technology of Food Industry, 2024, 45(11): 205−212. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023060306.
Citation: MA Jingjing, TIAN Chun, CHEN Jianglin, et al. A Rapid Evaluation Method for Unsaturation of Camellia Oil Based on Raman Spectroscopy Technology[J]. Science and Technology of Food Industry, 2024, 45(11): 205−212. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023060306.

基于拉曼光谱技术的山茶油不饱和度快速评价方法

A Rapid Evaluation Method for Unsaturation of Camellia Oil Based on Raman Spectroscopy Technology

  • 摘要: 为评价不同品种山茶油不饱和程度,有必要建立一种窄碘值范围(碘值差异小于10)的快速评价方法。本文以39组山茶油样品,10组市售油脂为研究对象,建立了一种基于线性回归、梯度下降法的高分辨拉曼光谱油脂碘值快速定量预测模型。采集不同饱和度的油脂样品在785 nm的拉曼谱图,采用平滑算法最小二乘平滑滤波(Savitzky-Golay)、多项式拟合和去卷积算法洛伦兹(Lorentzian)处理谱图信息。以筛选出的两个拉曼特征峰(1656 cm−1和1440 cm−1)的峰强比值(I1656/1440)作为不饱和度评价指标,结合传统滴定法测得的碘值数据进行相关性分析,所建定量模型测试集的决定系数(R2)>0.82,均方误差(MSE)<0.73,均方根误差(RMSE)<0.85,可准确、快速地评价山茶油等油脂的不饱和度。

     

    Abstract: To evaluate the degree of unsaturation of different varieties of Camellia oil, it was necessary to establish a rapid evaluation method with a narrow iodine value range (iodine value difference less than 10). In this study, a rapid quantitative prediction model for iodine value of oil in high-resolution Raman spectroscopy based on linear regression and gradient descent method was established. The Raman signals (785 nm) about 39 group of Camellia oil samples and 10 group of commercially oils were firstly collected. Then, the intensity ratio of peaks of 1656 cm−1 and 1440 cm−1 (I1656/1440) were selected through smoothing algorithm least squares smoothing filter (Savitzky-Golay), polynomial fitting and deconvolution algorithm Lorentzian. A credible model was obtained through correlation analysis with the iodine value of corresponding oil samples. The coefficient of determination (R2) of the test set of the constructed quantitative model was >0.82, the mean square error (MSE) was <0.73 and the root mean square error (RMSE) was <0.85. This quantitative model of edible oil iodine value can accurately and efficiently predict the unsaturation degree of Camellia oil, etc.

     

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