Influence of Processing Parameters and PYTHON Based Image Analysis for Quantification of Carcinogenic Acrylamide in Potato Chips

Abstract

Acrylamide (AA), a toxic compound and potential carcinogen, which forms at elevated heating of starchy food stuffs through the Maillard reaction. Thus, the identification and quantification of AA in the fried starchy food stuffs is of great importance in order to prevent cancer causing possibilities. The primary objective of this research was to investigate the effect of frying conditions and utilize PYTHON programming language to quantify the AA content on the Potato Chips (PCs). The PCs were prepared by frying at different time intervals and duration. The digital images of PCs were captured and used to extract significant browning parameter. Here, we employed image processing technique with PYTHON module to quantify the AA content on the PCs. In addition, we studied the influence of frying conditions concerning to the formation of AA, by varying the temperature and duration. As-prepared PC samples’ water content decreased and ash content increased with respect to the enhancement of frying temperature and duration. For image processing, the captured PCs images were subjected to pre-processing in terms of object segmentation, region of interest and feature extraction to quantify the AA content, precisely. The lowest AA content was observed as 0.26 µg/g, and the highest AA content was observed as 4.75 µg/g on the PCs. The results of this study showed that the small/large scale fried starchy food stuffs companies can utilize this cost-effective technique to quantify the AA content in their products.