基于近红外光谱的煎炸油极性组分定量分析模型构建  

Quantitative Analysis Calibration of Polar Components of Frying Oils Based on Near Infrared Spectroscopy

作　　者：陈秀梅[1] 于修烛[1] 王亚鸽[1] 张静亚[1] 

机构地区：[1]西北农林科技大学食品科学与工程学院,陕西杨凌712100

出　　处：《食品科学》2014年第2期238-242,共5页Food Science

基　　金：陕西省科技攻关项目(2012K02-11)

摘　　要：为了建立煎炸油中极性组分的快速检测方法，通过热处理和模拟煎炸方式，采集氧化程度不同的油样并用国标法分析样品极性组分，采集样品近红外透射光谱，经光谱预处理，利用偏最小二乘法建立煎炸油极性组分定量分析模型并对模型进行验证。结果表明：在波长范围为4963-4616、5222～5037cm-1和5688-5499cm-1，采用一阶求导和Savitzky．Golay（7，5）平滑光谱处理，校正集相关系数为0．9965，校正均方根差为1．84％，验证集R为0．9936，验证均方根差为1．92％，模型预测效果良好，利用近红外透射光谱测定煎炸油极性组分可行。This study established a quick method for determining the polar components of frying oil. The oil samples with different degrees of oxidation through heating and simulated frying were collected and their polar components were analyzed according to the Chinese national standard method. Near infrared （NIR） transmission spectra of these samples were recorded and preprocessed, and a quantitative analysis model was developed using partial least square regression （PLSR） method and validated. In the selected spectra ranges of 4 963--4 616, 5 222-5 037 and 5 688-5 499 cm-1, after spectral preprocessing by first derivative and Savitzky-Golay （7,5） smoothing, the correlation coefficient （R） for the calibration set and the root mean square error of calibration （RMSEC） were determined to be 0.996 5 and 1.84%, respectively, and the R value for the validation set and the root mean square error of validation （RMSEV） were 0.993 6 and 1.92%, respectively, suggesting the accuracy and reliability of the predictive model. Therefore, it is feasible to apply NIR to quantitatively analyze polar components of frying oil.

关 键 词：煎炸油 近红外透射光谱 极性组分 定量分析模型 

分 类 号：TS227[轻工技术与工程—粮食、油脂及植物蛋白工程]