Quantitative Analysis Of Oat Flour In Oat-wheat Mixed Powders Based On Fatty Acids

Oats is known as ―Natural full nutritional food‖ and is widely used in food industry in virtue of its high value in medical treatment, health protection and cosmetology. Simultaneously, food adulteration and fraud issues on the market have also spread to oat materials and products whereas there is no established standard quality testing method. Therefore, this paper was devoted to solving these problems and the main contents included the following aspects:Multiple oat samples of different habitats and varieties were collected and then contents of three characteristic ingredients including avenacosides, β-glucan and oil of them were determined. The results indicated that contents variation coefficients about the three ingredients of the whole samples were very large, which were 12.13%、20.79%、22.46% respectively. And it was the same with samples of each habitats. Therefore, the three indicators could not represent the information of all the oat samples, so they were not suitable for adulteration discrimination and quantitative analysis of oat raw materials and products.Based on results of study on the compositions of oats at home and abroad, fatty acids was preliminarily selected to be the discriminant indicator for adulteration discrimination and quantitative analysis of oat raw materials and products. Principal component analyses were carried out on fatty acids in oats and wheat samples, and 11 characteristic fatty acids in 46 naked oat samples and 12 characteristic fatty acids in 36 wheat samples were identified by total pattern method combined with cluster analysis. Then the fatty acids standard fingerprints of naked oats flour and wheat flour were constructed, and the similarities of both oats and wheat samples were above 0.99. RSD of precision, reproducibility and stability experiments were all less than 5%, which were in line with fingerprint testing requirements. According to the owned similarities of unknown oats or wheat samples after comparing with the standard fingerprints, authenticity and purity of the unknown samples can be determined qualitatively.Based on comparative analysis, it could be concluded that oats and wheat flours are both rich in fatty acids. Furthermore, contents of palm acid, oleic acid and linoleic acid took up more than 90% of the total fatty acids, and they all had small variation coefficients which were 5.90%、6.13%、5.33% in oats and 5.46%、8.16%、1.97% in wheat respectively. But there existed great differences between contents of the three fatty acids of the two crops, the average contents of them were 15.86%、39.17%、37.74% in naked oats and 16.21%、15.81%、59.81% in wheat. Therefore, the said three main fatty acids were considered as ideal characteristic indicators for quantitative discriminant of oat flour in oat-wheat mixed products on account of similarities and differences of fatty acids in oats and wheat.On the basis of the studies above, the information and distribution regulars in the three dimensional figure of fatty acids in oat-wheat mixed powders were determined, the mixed powders were acquired by an balanced incomplete randomized block design which aimed at including the significant variations that may be encountered in future samples. Then quantitative discriminant analyses were conducted through fisher discriminant analysis, SVM support vector machine and BP neural network. Results showed that classification discriminant of the mixed powder samples with different oat flour additions could be performed successfully through the three chemometric methods when using contents of palm acid, oleic acid and linoleic acid or ratios of oleic acid/linoleic acid, palm acid/oleic acid and palm acid/linoleic acid as variables. And high classification accuracy ranging from 86.0% to 93.7% of the three methods were obtained, which indicated the feasibility and scientific of the chosen indicators.It was proved that the fitting equation with oat flour addition as independent variable and ratio of oleic acid/linoleic acid as dependent variable had the largest R Square when conducted comparative analysis using the 315 groups of fatty acids data of the 105 experiment samples. And it was the most suitable for detecting oat flour addition in unknown mixed powder samples, the equation was Y=0.0125X+0.2680,R2=0.9725. To explore the application of the established quantitative model in oat noodles, fatty acids of mixed powders and noodles were detected, and the results showed that the contents of palm acid, oleic acid and linoleic acid in noodles are 1.08, 1.03 and 0.96 times as those in mixed powder samples. So for noodles with unknown oat addition levels, it can be quantified by using the change factors of each fatty acid for conversion, and then the found distribution regulars in the three dimensional figure of fatty acids and the built discriminant model for classification.