牡丹籽油掺伪现象严重，需要加强监管和打击力度，如何鉴别牡丹籽油的真伪成为了一个亟待解决的问题。该研究旨在探究基于PCA-SVR算法和共聚焦拉曼光谱的牡丹籽油掺伪定量分析方法。首先，采集牡丹籽油样品，并进行共聚焦拉曼光谱分析以确定其化学成分和结构，分别测试不同掺伪浓度的牡丹籽油的混合油。然后，利用拉曼光谱数据建立PCA-SVR定量分析模型，以区分牡丹籽油和其他植物油的掺伪情况。最后，通过实验验证该方法的准确性和可行性，结果表明该方法可以有效地鉴别牡丹籽油和其他植物油的掺伪情况，模型测试集量化效果的决定系数R2优于0.98，均方根误差RMSE小于0.04。该方案检测牡丹籽油掺伪浓度的理论极限为0.011 52，即对于预测混合油品中牡丹籽油所含体积比大于0.011 52的样品是可信的。基于PCA-SVR算法和共聚焦拉曼光谱相结合的检测方案具有较高的准确性和可靠性，该研究对于提高牡丹籽油的质量控制和保障消费者的健康具有重要意义。

It is imperative to implement more stringent punitive measures to combat the adulteration of peony seed oil, and establish quantitative methods to determine the authenticity of peony seed oil. A quantitative analysis model, based on principal component analysis and support vector regression (PCA-SVR) and Raman spectroscopy was developed, to determine the chemical composition and structure of samples of peony seed oil mixed with different proportions of soybean oil. The method effectively identified adulteration of peony seed oil. The coefficient of determination (R2) of the quantitative effect of the model test set exceeded 0.98 and the root-mean-square error (RMSE) was less than 0.04. The theoretical limit for detecting the adulteration in peony seed oil in this model was 0.011 52, indicating that the method was reliable for measuring mixed oil samples with a volume ratio of peony seed oil that was greater than 0.011 52. The detection model combining PCASVR and confocal Raman spectroscopy demonstrated high accuracy and reliability. The findings of this study have important implications for improving the quality of peony seed oil to ensure consumer health.

国家自然科学基金项目（61802107）；广西高校中青年教师科研基础能力提升项目（2019KY1215）