Based On The Characteristic Fatty Acid Of The Near Infrared Of The Identification Of Adulterated Sesame Oil

Edible oils plays an important role in people’s life. Different types of edible oilwhich has different fatty acid composition and nutritional value, the quality hasimportant influence for the grease. In recent years, cooking oils adulterationphenomenon has became increasingly serious, especially the price is relativelyexpensive sesame oil. Sesame oil has a high nutritional value, due to its adulterationphenomenon has always existed, it needs for a rapid determination of the mainingredients of vegetable oil analysis techniques. Near-infrared spectroscopytechnology for its rapid, nondestructive, and the advantages of convenient, has beenwidely used in the food industry, petrochemical industry, pharmaceutical industry andother fields, including research of grease nutrition. Chemometrics is the integrated useof statistics, mathematics, computer science. Near-infrared spectroscopy andchemometrics which is the basis for solving the problem of detecting adulterationplays an important role in the qualitative and quantitative analysis. This paper mainlyto the main fatty acids changes in the adulterated sesame oil fatty acid for detectingtarget, launched the research of near infrared spectroscopy quantitative analysis,establishing the conditions for selection to eliminate from the main parameter selection,abnormal samples and near infrared analysis model are discussed.1. The detection method of fatty acids in edible vegetable oil were analyzed, thedetection principle chromatography, infrared spectroscopy were discussed, thedetection methods of each index in this paper were determined.2. Studied the incorporation of sesame oil, soybean oil, peanut oil, cottonseed oilsamples using near-infrared spectroscopy to establish a method for the determinationof four fatty acid content. By correcting the model spectra pretreatment methods wereoptimized for the best spectral wavenumber, the optimal combined with partial leastsquares (PLS) analysis of the quantitative calibration models were established, and thegas chromatography method for the determination of fatty acid content as the chemical value, calibration set samples number is122, test samples number is38, the test resultsshowed that:(1) linolenic acid(C18:3), arachidonic acid(C20:0), tetracosanoic acid(C24:0) andmyristic acid(C14:0) are specific near-infrared absorption of mixed oil sample.(2) The optimum condition of mathematics model of four components werestudied, including the sample set selection，chemical value analysis，the detectionmethods and condition. The correlation between the reference value of the calibrationsample and the near infrared predictive value were R2(C14:0)=0.996, R2(C18:3)=0.989,R2(C20:0)=0.995, R2(C24:0)=0.993, respectively. And the correlation between thereference value of the testing sample and the near infrared predictive value were0.981,0.984,0.949,0.956respectively.(3) The results of the test show that the model can better detect mixed oil fattyacid content, the average relative error of prediction of four kinds of fatty acid contentwas7.7%,6.2%,4.9%,6.8%.3. The configuration with the sesame oil four element system of soybean oil,peanut oil and cottonseed oil, and the adulteration content was quantitativelydetermined, established the PLS model of soybean oil, peanut oil and cottonseed oilcontent, the correlation coefficients of models were0.951、0.960、0.933, theRMSECV were0.401、0.379、0.564, respectively. The correlation is poor, whichrevealed that the method couldn’t get an accurate quantitation analyzed result.