Application of real-time image processing for monitoring bacterial cellulose growth in various nitrogen sources using soybean-boiled wastewater medium during fermentation

Abstract

One of the utilizations of liquid waste of soybean boiling was a combination medium of bacterial cellulose (BC) fermentation. Recent study was found the implementation of image processing approach on observation of BC growth. This work utilized the image processing approach with a soybean-boiled wastewater medium using ammonium sulphate and yeast extract as nitrogen source. This study aimed to find out the highest correlation between variables that affect the fermentation process and to examine the kinetic model of the BC thickness during fermentation stage using Real-Time Image Processing (RTIP) approach with the variation of nitrogen sources. The outcome demonstrates that the correlation between time and thickness was found as the highest correlation variable during fermentation on both mediums. The Gompertz model equation was followed in the kinetic observation of BC growth on both medium and showed that the first growth of BC on ammonium sulphate was earlier than on yeast extract as nitrogen source. Further studies are also needed to understand the ability of image processing approach to detect potential failures in BC growth.