Electronic Nose Monitoring the Maillard Reaction Flavors of Sesame Oil from Different Production Processes

Su Dong-Yang,Li Jia,Zhu Li-Yun,Zhang Gao-Fan,Chen Ping,Zhang Yong-Jun,Zhang Yu

doi:10.19026/ajfst.6.132

Abstract

The objective in this study was to evaluate the capacity of electronic nose to monitoring the effect of different Maillard reaction processes on natural flavors of sesame oil, using a specific Electronic Nose device (PEN3). The flavors were prepared by Maillard reaction using chemical constituents from water extract of Lentinus and other precursors. The optimum conditions of reaction process was determined by using orthogonal test design, then an Electronic Nose (PEN3)was used to characterize and classify eight different flavors from different reaction process and sesame oil from market. This method firstly sampled aroma composition emanating from the flavors by PEN3 systems and then obtained response values of PEN3. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were used in order to investigate whether the electronic nose was able to distinguish among different Maillard Reaction Production (MRP). The loadings analysis was used to identify the sensors responsible for discrimination in the current pattern file. The results of this study showed that the basic components added with lysine, xylose and glycerin, heated in glycerine bath at 140C for 120 min, was a novel flavors with sesame oil flavor and taste. The electronic nose PEN 3 can discriminate successfully different MRPs using both PCA and LDA analysis. But, it was not able to detect a clear difference in the sample of similar aroma with sesame oil using PCA analysis. Some sensors have the highest influence in the current pattern file for electronic nose PEN 3. A subset of few sensors can be chosen to explain all the variance. This result could be used in further studies to optimize the number of sensors.

Highlights

The electronic noses (e-noses) are analytical instruments which are capable to recognize simple or complex mixtures of organic vapors after an appropriate training period
When the Linear Discriminant Analysis (LDA) analysis (Fig. 5), using the same data of nine groups (Maillard reaction process and the sesame oil date), the Maillard Reaction Production (MRP) were distinguishable from each group
Loading analysis: The loading analysis will help to identify the important of sensors responsible for discrimination in the current pattern file

Summary

INTRODUCTION

The electronic noses (e-noses) are analytical instruments which are capable to recognize simple or complex mixtures of organic vapors after an appropriate training period They are typically array of sensors used to detect and distinguish odors precisely in complex samples and at low cost (Peris et al, 2009). The Maillard reaction, a well-known nonenzymatic browning reaction involving a reducing sugar and an amino acid, may produce colored or colorless reaction products depending on the stage of the reaction as well as other factors such as pH, type of reactants, temperature, water activity, etc. Sesame oils have a mild odor and a pleasant taste and, as such, is a natural salad oil requiring little or no winterization It is used as a cooking oil, in shortening and margarine, as a soap fat, in pharmaceuticals and as a synergist for insecticides (Ampuero and Bosset, 2003). To identify each sensor responsible for discrimination in the current pattern file, using loading analysis

MATERIALS AND METHODS

RESULTS

Findings

CONCLUSION