CAJ | 학술논문

把低价油掺入到高价油是食用油脂中的常见掺伪现象，芝麻油由于品质好价格高，市场上时有假冒伪劣产品，因此应用FTIR并结合化学计量学，建立了芝麻油的真伪和掺伪的快速分析方法。首先分析了芝麻油与大豆油、葵花籽油在4000～650cm-1范围的FTIR谱图，由于食用植物油都是不同脂肪酸甘油三酯的混合物，其谱图极为相似，很难发现芝麻油与其他油脂的明显差异。但是不同食用油的脂肪酸组成不同，其1800～650cm-1红外指纹特征区也有所不同，因此可以选择该区域，对红外光谱数据用化学计量学方法进行分类识别。通过建立主成分分析（PCA）和簇类独立软模式识别（SIMCA）模型，进行了芝麻油的真伪鉴别，该模型聚类效果较为理想，识别正确率达到了100％；采用标准正态化校正（SNV）和偏最小二乘法（PLS），经过PCA分析计算，芝麻油中掺入大豆油、葵花籽油的掺伪检测限均为10％；利用FTIR和PLS，建立了芝麻油掺的定量分析模型，该模型预测值与实际值有着良好的对应关系，预测相对误差为-6.87％～8.07％之间，说明定量模型可行。本方法能够实现芝麻油的快速真伪鉴别和掺伪定量分析，其优点是模型一旦建立，分析简便、快速，可以满足大量样品的日常监测。
파저개유참입도고개유시식용유지중적상견참위현상，지마유유우품질호개격고，시장상시유가모위렬산품，인차응용FTIR병결합화학계량학，건립료지마유적진위화참위적쾌속분석방법。수선분석료지마유여대두유、규화자유재4000～650cm-1범위적FTIR보도，유우식용식물유도시불동지방산감유삼지적혼합물，기보도겁위상사，흔난발현지마유여기타유지적명현차이。단시불동식용유적지방산조성불동，기1800～650cm-1홍외지문특정구야유소불동，인차가이선택해구역，대홍외광보수거용화학계량학방법진행분류식별。통과건립주성분분석（PCA）화족류독립연모식식별（SIMCA）모형，진행료지마유적진위감별，해모형취류효과교위이상，식별정학솔체도료100％；채용표준정태화교정（SNV）화편최소이승법（PLS），경과PCA분석계산，지마유중참입대두유、규화자유적참위검측한균위10％；이용FTIR화PLS，건립료지마유참적정량분석모형，해모형예측치여실제치유착량호적대응관계，예측상대오차위-6.87％～8.07％지간，설명정량모형가행。본방법능구실현지마유적쾌속진위감별화참위정량분석，기우점시모형일단건립，분석간편、쾌속，가이만족대량양품적일상감측。
It’s common in edible oil market that adulterating low price oils in high price oils .Sesame oil was often adulterated because of its high quality and price ,so the authentication and adulteration of sesame oil were qualitatively and quantitatively an-alyzed by Fourier transform infrared (FTIR) spectroscopy combined with chemometrics .Firstly ,FTIR spectra of sesame oil , soybean oil ,and sunflower seed oil in 4 000~650 cm-1 were analyzed .It was very difficult to detect the difference among the spectra of above edible oils ,because they are all mixtures of triglyceride fatty acids and have similar spectra .However ,the FTIR data of edible oils in the fingerprint region of 1 800~650 cm -1 differed slightly because their fatty acid compositions are differ-ent ,so the data could be classified and recognized by chemometric methods .The authenticity model of sesame oil was built by principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) .The recognition rate was 100% , and the built model was satisfactory .The classification limits of both soybean oil and sunflower seed oil adulterated in sesame oil were 10% ,with the chemometric treatments of standard normal variation (SNV) ,partial least square (PLS) and PCA .In addi-tion ,the FTIR data processed by PCA and PLS were used to establish an analysis model of binary system of sesame oil mixed with soybean oil or sunflower oil ,the prediction values had good corresponding relationship with true values ,and the relative er-rors of prediction were between -6.87% and 8.07% ,which means the quantitative model was practical .This method is very convenient and rapid after the models have been built ,and can be used for rapid detection of authenticity and adulteration of sesa-me oil .The method is also practical and suitable for the daily analysis of large amount of samples .