Optimization of lard compound analysis using portable electronic nose based upon response surface methodology

Abstract

Portable Electronic Nose (E-Nose) is a device that mimics human olfactory system and can be carried around for an “on-line” detection of lard in food. The objectives of this study wass to optimize process parameters for the determination of lard detection quantitatively. This study was important to increase the performance of the device in an efficient manner. The optimum conditions for the detection of lard were determined using Historical Data Design in Response Surface Methodology (RSM). This design was used to investigate the effects of the analytical conditions, namely weight (g), temperature (°C) and time (min). These parameters were found to give a positive effect on the sensor response, which plays an important role in the increment of the sensor response. While Analysis of Variance (ANOVA) shows that the selected quadratic model was significant with Fisher value of 40.77, as it adequately represented the data obtained. Moreover, regression analysis showed that 96% of the total variation was successfully explained by the models. Optimum process parameters generated by Design Expert 7.1.5 shown that 0.2g of lard is the minimum weight can be detected at 50°C for 3 minutes. Hence, this study had successfully optimized the process parameters using RSM for the presence of lard adulteration in food. © 2018, Malaysian Consumer and Family Economics Association. All rights reserved