基于拉曼光谱的食用调和油原料组分快速定量检测方法

应用激光拉曼光谱技术结合偏最小二乘法实现了食用调和油中5种原料油（花生油、芝麻油、菜籽油、大豆油和玉米油）的定量检测。首先选取食用油脂肪酸信息丰富的169.58～1813.61cm-1谱区，再通过一阶导数+Norris 3点预处理对该谱区进行滤波去噪，净化拉曼光谱信息，采用偏最小二乘法建立食用调和油中各原料组分的拉曼定量检测模型，其中花生油、芝麻油、菜籽油、大豆油和玉米油的检测模型的校正集相关系数分别为0.9998、0.9418、0.9988、0.9998、0.9961，验证集相关系数分别为0.9435、0.8593、0.9542、0.9676、0.9429，均方根误差分别为0.117、0.218、0.128、0.125、0.179。研究结果表明，激光拉曼光谱法结合化学计量学方法快速、准确地测定食用调和油中各原料组分的含量具有可行性，且预测能力良好。

Rapid Quantitative Determination of Raw Material Components in Blended Edible Oil Based on Raman Spectroscopy

Quantitative detection of five kinds of raw materials (peanut oil, sesame oil, rapeseed oil, soybean oil and corn oil) in blended edible oil was realized by laser Raman spectroscopy combined with Partial Least Squares method. Firstly, the 169.58 ~ 1813.61cm-1 spectral region with abundant fatty acid information was selected, and the spectral denoising and purification of the spectral region were carried out by first derivative + Norris 3 preconditioning. Then, Raman quantitative detection model was established for raw material components of blended edible oil by using Partial Least Squares. The correlation coefficients of calibration set of peanut oil, sesame oil, rapeseed oil, soybean oil and corn oil were 0.9998, 0.9418, 0.9988, 0.9998,0.9961, respectively. And the correlation coefficients of the verification set were 0.9435, 0.8593, 0.9542, 0.9676,0.9429, respectively. The root mean square error (RMSE) were 0.117, 0.218, 0.128, 0.125,0.179, respectively. The results showed that laser Raman spectroscopy combined with chemometric resolution method can be used to determine the contents of raw material components in blended edible oil quickly and accurately. The good prediction ability can provide a theoretical basis for rapid detection of the content of blended edible oil.