Monitoring The Vinegar Aging Of Organic Acids, Antioxidant Capacity And Based On Electronicnose Detection

In this paper, five kinds of aging period of four kinds of commercial vinegars as theresearch object. To develop an analytical method for the determination of seven organic acidsin vinegars by cleaning up using an C18solid phase extraction cartridge and high-performanceliquid chromatography(HPLC), and to analysis of the dynamic changes in the aging processof organic acid.Also established four kinds of commercial vinegars in the monitoring of5months the antioxidant activity of aging period, trend analysis of vinegars in the aging processof antioxidant capacity;Finally, the German PEN3electronic nose was used to detect the odorof4kinds of commodities vinegars during the aging process, and combined with the analysisof Fisher linear discriminant and multilayer perceptron neural network, to establish effectivemethods of electronic nose monitoring vinegar aging period.The results are presented in thefollowings:(1) Qualitative and quantitative analysis of seven kinds of organic acid in different agingperiod vinegars. The results showed that acetic acid and lactic acid was found to be thepredominant organic acid in the vinegars, and as the aging time increases, the content of lacticacid increased, the content of acetic acid decreased. The change tendency of Oxalic acid,tartaric acid, malic, acid and citric acid are not obvious, probably because the content isless.So the vinegar in the aging process is mainly through the content of non-volatile acid(especially lactic acid) to make vinegars sour taste more mellow, harmony.(2) In different aging period of vinegar antioxidant were measured. The results showedthat DPPH· scavenging ability, Fe3+reducing power, total phenolic content, total flavonoidcontent, total acid content and total antioxidant capacity of vinegars in the aging process wereincreased, and the increasing trend of each month is not significant, was significantlyincreased only in two months or three months later, so vinegars antioxidant in the overallaging process is increasing, but slow.Correlation between the content of vinegar in the aging process of total phenolics andflavonoids, the variation trend is the same, one adds another also increased; In the agingprocess of increased DPPH·scavenging ability may be due to the increase of the content oftotal flavonoids and total acid content increased; The Fe3+reducing capacity may be due to the increased total phenolic content and total acid content;(3) An electronic nose was used to detect the vinegars in different aging period, testresults showed that vinegar flavor improvement is mainly because the oxides of nitrogen,methane and hydrogen sulfide type some unpleasant volatile component is gradually reducedin the aging process of vinegars.(4) The distinction of vinegars during the different aging period based on PCA(principalcomponent analysis) and LDA (linear discrimination analysis) showed that LDA is better thanPCA, and volatile components of vinegar in aging period have obvious trend through theLDA. As the aging time increases, the volatile composition changes of the increasing,consistent variation and total acid, so electronic nose can be distincted vinegar of differentaging time by the differences in the volatile composition of different aging time.(5) FDA (fisher linear discrimination analysis) were employed to predict the aging timeof the samples. The results showed that the FDA prediction rate of Feng Xiang, Long Xian,Jin Tai, Wei Bin vinegars samples were100%,100%,98%and100%respectively. In order toverify the feasibility of electronic nose combined with FDA apply to detecting the aging timeof vinegars. MLPNN (multilayer perceptron neural network) were employed to predict theaging time of the samples. The results showed that the MLPN prediction rate of Feng Xiang,Long Xian, Jin Tai, Wei Bin vinegars samples were100%、100%、96.92%和100%respectively.Thus verified can achieve rapid monitoring of vinegar ageing time of theelectronic nose with multilayer perceptron neural network. The prediction rate by Anelectronic nose combined with FDA was better than MLPNN.