摘要
为建立快速检测油茶籽油中脂肪酸组成的方法,利用傅里叶红外光谱仪扫描86个油茶籽油样品,红外光谱数据分别通过Savitzky-Golay平滑(SG)、多元散射校正(MSC)、标准正态变换(SNV)、一阶导数(FD)和二阶导数(SD)等5种方法进行降噪处理,然后以气相色谱测定的脂肪酸组成作为标准值,采用全波长偏最小二乘法(PLS)、区间偏最小二乘法(iPLS)和联合区间偏最小二乘法(siPLS)分别构建油茶籽油中主要脂肪酸(油酸、棕榈酸、亚油酸)的定量回归模型。结果表明:油酸、棕榈酸、亚油酸的红外光谱数据预处理分别以SG、SNV、SD较好;siPLS通过有效波段的选择可去掉更多的噪声,比PLS和iPLS建立的模型精确度高,油酸、棕榈酸、亚油酸的校正集和预测集的相关系数(R)分别为0.9479和0.8539、0.9008和0.9101、0.9793和0.9505。红外光谱结合siPLS更适用于油茶籽油脂肪酸组成的快速测定。
In order to establish a method for rapid determination of fatty acid composition in oil-tea camellia seed oil,86 oil-tea camellia seed oil samples were scanned by Fourier transform infrared spectrometer,and the infrared spectrum data were denoised by Savitzky-Golay(SG)smoothing,multiple scattering correction(MSC),standard normal transformation(SNV),first derivative(FD)and second derivative(SD),respectively.Then the quantitative regression model of main fatty acids(oleic acid,palmitic acid and linoleic acid)in oil-tea camellia seed oil was established by full-wavelength partial least square(PLS),interval partial least square(iPLS)and synergy interval partial least square(siPLS),respectively with fatty acid composition determined by gas chromatography was as the standrad value.The results showed that SG,SNV and SD were the best pretreatment methods for infrared spectral data of oleic acid,palmitic acid and linoleic acid,respectively,and siPLS could remove more noise through the selection of effective bands,which was more accurate than the models established by PLS and iPLS.The correlation coefficients(R)of the correction set and prediction set of oleic acid,palmitic acid and linoleic acid were 0.9479 and 0.8539,0.9008 and 0.9101,0.9793 and 0.9505,respectively.Infrared spectroscopy combined with synergy interval partial least square method is more feasible for the rapid determination of the fatty acid composition of oil-tea camellia seed oil.
作者
陈品杰
吴雪辉
CHEN Pinjie;WU Xuehui(College of Food Science,South China Agricultural University,Guangzhou 510642,China;Guangdong Engineering Research Center for Oil-Tea Camellia,Guangzhou 510642,China)
出处
《中国油脂》
CAS
CSCD
北大核心
2022年第12期112-118,共7页
China Oils and Fats
基金
广东省林业科技计划项目(2019-02)
河源市科技计划(河科2021007)。
关键词
油茶籽油
脂肪酸组成
红外光谱
数据预处理方法
偏最小二乘法
oil-tea camellia seed oil
fatty acid composition
infrared spectrum
data preprocessing method
partial least square
作者简介
陈品杰(2001),男,在读本科,研究方向为粮油食品加工(E⁃mail)835636165@qq.com;通信作者:吴雪辉,教授,博士(E⁃mail)xuehwu@scau.edu.cn。
