应用近红外光谱分析技术定量检测植物油脂肪酸含量的研究

Quantitative Detection Research for the Fatty Acid of Vegetable Oil Using Near Infrared Spectroscopy

[目的]建立一种简单、快速、准确且无损的脂肪酸含量的定量检测方法。[方法]应用近红外光谱分析技术快速准确定量检测植物油中3种脂肪酸含量,采用偏最小二乘法PLS建立植物油中3种脂肪酸(油酸、亚油酸、亚麻酸)含量的近红外定量分析模型,并对比分析了10种光谱预处理方法对植物油中3种脂肪酸含量定量分析校正模型结果的影响。[结果]一阶导数(FD)结合多元散射校正(MSC)法的光谱预处理效果最优,经FD+MSC法预处理后采用PLS建立的植物油脂肪酸含量检测的校正模型,对油酸的验证决定系数R2为0.969 3,预测标准差RMSEP为1.3%;对亚油酸的验证决定系数R2为0.960 6,预测标准差RMSEP为1.66%;对亚麻酸的验证决定系数R2为0.973 1,预测标准差RMSEP为0.479%。[结论]研究表明,所建模型可较好地检测植物油中油酸、亚油酸、亚麻酸含量。

[Objective] To establish a new method for the quantitative detection research for the fatty acid of vegetable oil using near infrared spectroscopy.[Method] Using partial least squares（PLS） to establish near-infrared quantitative analysis model,and compare and analysis the results of the calibration model for quantitative detection of fatty acids（oleic acid,linoleic acid,linolenic acid）using 10 kinds of pretreatment methods on vegetable oil.[Result] Results showed that FD＋MSC is the best pretreatment method,determination coefficient R2 of oleic acid validation model was 0.969 3,RMSEP was1.3%;determination coefficient R2 of linoleic acid validation model was 0.960 6,RMSEP was 1.66%;determination coefficient R2 of linolenic acid validation model was 0.973 1,RMSEP was 0.479%,they all have high determination coefficient.[Conclusion] It shows that the model can detect oleic acid,linoleic acid,linolenic acid simultaneously very well.