摘要
选择97个标称纯油茶籽油样品经过皂化、甲酯化后,先经气相色谱分析得到脂肪酸组成相对含量,然后利用透反射模式采集所有样品的近红外光谱,采用偏最小二乘法(partial least squares analysis,PLS)建立油茶籽油的饱和脂肪酸(C16:0+C18:0)、油酸(C18:1)和亚油酸(C18:2)相对含量的校正模型,并将模型用于预测,并对光谱预处理方法进行优化。结果表明:C16:0+C18:0、C18:1和C18:2的交叉验证均方根误差(root mean square error in cross-vali-dation of prediction,REMSECV)分别为0.143、0.448、0.392,预测均方根误差值(root-mean-square error value,RMSEP)分别为0.180、0.598和0.269,上述3种成分预测集相关系数(Rp2)依次分别为0.996、0.999和0.999。近红外光谱法可作为一种快速、无损和准确的方法用于测定油茶籽油的脂肪酸组成,从而鉴别纯油茶籽油的真伪。
In the present work,after being saponified and methyl esterified,the fatty acid composition of 97 camellia oil samples was analyzed by gas chromatography.Meanwhile,the near-infrared spectra of all samples were acquired in the transreflection mode.Calibration models for the relative contents of saturated fatty acids（C16：0 ＋ C18：0）,oleic acid（C18：1） and linoleic acid（C18：2） were established by partial least-squares regression method were applied.Additionally,the pretreatment of spectra was optimized.The results showed that the root mean square errors of cross-validation（RMSECV） for C16：0 ＋ C18：0,C18：1 and C18：2 were 0.180,0.598 and 0.269,respectively.The root-mean-square errors of prediction（RMSEP） for C18：0,C18：1 and C18：2 were 0.180,0.598 and 0.269,respectively.The correlations of determination（Rp2） of the three components were 0.996,0.999 and 0.999,respectively.These findings indicate that near-infrared spectroscopy can be used to identify the authenticity of camellia oil as a simple,rapid,nondestructive and reliable method for analyzing fatty acid profile.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2011年第18期205-208,共4页
Food Science
基金
湖南省农业科学院科技创新项目(2009hnnkycx29)
