Application of Resident Disease Screening Paradigm on Early Warning of Instability of Anaerobic Digestion of Food Waste

Early warning has been widely proven to be reliable in lowering the risk of instability for biological processes. However, it is very difficult for the warning systems used currently to achieve satisfactory accuracy, timeliness and universality simultaneously. This study developed a novel early warning system for instability in food waste anaerobic digestion (FWAD) by bioimitating the human disease screening paradigm. It consists of single, comprehensive and microbiological indicators. Findings showed that single-factor early warning systems resembled acute patient diagnosis, having high accuracy but low timeliness and poor universality. Each of the chosen single indicators showed distinct early warning performances and clear preferences for diverse inhibitions concerning the instabilities of high organic load rate, high ammonia, and high fat in FWAD. Then, a new comprehensive indicator was developed using the entropy weights of several indicators. Confirmatory tests revealed that the comprehensive indicator-based early warning system was analogue to the resident sub-health diagnostic regarding superior foresight and good operability but poor targeting. Therefore, an early warning system based on microbial changes was proposed for potential instability in FWAD by bioimitating human periodic physical examination. The sensitive bacteria were identified as norank_o_ norank_c_Dojkabacteria and Rikenellaceae_RC9_gut_group. Enlarged tests showed that the developed system could be used for emergent, indistinct and potential early warnings simultaneously while avoiding the shortcomings of existing systems. More preciously, this study provided a paradigm for developing early warning systems of FWAD, which is also suitable to be applied to the intelligent systems that rely on automated machine learning.