基于融合光谱的菜籽油氧化稳定性快速评价  

Rapid evaluation of the oxidative stability of rapeseed oil based on fusion spectroscopy

作　　者：王微娜 张炉 尹华全 咸嘉伟 荀拾虎 石林英 刘香 郭时印[1,2] 唐忠海 范伟 WANG Weina;ZHANG Lu;YIN Huaquan;XIAN Jiawei;XUN Shihu;SHI Linying;LIU Xiang;GUO Shiyin;TANG Zhonghai;FAN Wei(College of Food Science and Technology,Hunan Agricultural University,Changsha 410128,China;Hunan Engineering Research Center for Nutrition,Health and Deep Development of Rapeseed Oil,Changsha 410128,China)

机构地区：[1]湖南农业大学食品科学技术学院,长沙410128 [2]湖南省菜籽油营养健康与深度开发工程技术研究中心,长沙410128

出　　处：《中国农业大学学报》2025年第4期81-95,共15页Journal of China Agricultural University

基　　金：国家自然科学基金项目(32360579);湖南省自然科学基金项目(2022JJ30295);湖南省教育厅优秀青年项目(20B286)。

摘　　要：为实现菜籽油氧化稳定性的实时在线监测,采用自主搭建的近红外-拉曼(NIR-Raman)光谱便携设备,结合光谱融合技术对菜籽油的氧化稳定性进行定量评估。采集不同氧化程度菜籽油样本的NIR和Raman光谱数据,通过8种预处理方法和3种特征变量选择法,利用数据层融合、特征层决策融合和多区块融合策略,建立偏最小二乘回归(PLSR)模型,以预测集决定系数(R_(p)^(2))和预测均方根误差(RMSEP)评价模型精度。结果表明:1)以过氧化值(POV)为例,在NIR光谱中,SNV+MSC预处理方法表现最佳,R_(p)^(2)为0.84,RMSEP为1.05;Raman光谱中,SNV预处理方法最优,R_(p)^(2)为0.85,RMSEP为0.99;2)在光谱融合方案中,对比3种融合方式,多区块融合的序贯正交偏最小二乘(SO-PLS)方法表现最佳,R^(2)达到0.978,RMSEP为0.392;3)采用SO-PLS融合NIR和Raman光谱对菜籽油氧化指标,丙二醛(MDA)、茴香胺值(AV)及共轭二烯值(CDV)进行预测,R^(2)分别达到0.98、0.98和0.97,RMSEP分别为0.871、1.039和2.132。综上,本研究利用SO-PLS融合NIR和Raman光谱可对菜籽油氧化程度进行快捷无损的实时动态监测,为菜籽油加工过程的质量控制提供了技术支持。To achieve the real-time online monitoring of rapeseed oil oxidative stability,a custom-built portable near-infrared and Raman spectroscopy(NIR-Raman)device combined with spectral fusion techniques was utilized to assess the oxidative stability of rapeseed oil quantitatively.The NIR and Raman spectral data were collected from rapeseed oil samples exhibiting varying degrees of oxidation.Eight preprocessing methods and three feature selection approaches were applied to construct partial least squares regression(PLSR)models using data-level,feature-level decision and multi-block fusion strategies.The accuracy of the models was evaluated using the prediction set determination coefficient(R_(p)^(2))and the prediction root mean square error(RMSEP).The results demonstrated that:1)Taking peroxide value(POV)as an example,in the NIR spectrum,the SNV+MSC preprocessing method displayed the best performance with an R_(p)^(2) of 0.84 and RMSEP of 1.05;In the Raman spectrum,the SNV preprocessing method was the most optimal with an R_(p)^(2) of 0.85 and an RMSEP of 0.99;2)Among the spectral fusion schemes,the sequential orthogonal partial least squares(SO-PLS)method with multi-block fusion outperformed the other two methods,achieving R^(2) of 0.978 and RMSEP of 0.392;3)The prediction of rapeseed oil oxidation indicators,including malondialdehyde(MDA),anisidine value(AV),and conjugated diene value(CDV),using SO-PLS integrated NIR and Raman spectroscopy,R^(2) values reached 0.98,0.98,and 0.97,respectively,and RMSEP values were 0.871,1.039,and 2.132,respectively.In summary,this study applied the SO-PLS fusion of NIR and Raman spectra for rapid,non-destructive,realtime dynamic and realized the monitoring of the oxidation level of rapeseed oil.This study provided technical support for quality control in the processing of rapeseed oil.

关 键 词：光谱融合技术 近红外光谱 拉曼光谱 菜籽油 氧化稳定性 

分 类 号：S65[农业科学—果树学]