# A Perspective on Emerging Inter-Disciplinary Solutions for the Sustainable Management of Food Waste
## 4 Food Waste Management, Regulations, and Biological Treatment Technologies
### Initiatives Supported by Omics and Bioengineering Disciplines  
Opportunities for the development of new high-throughput systems for efficiently identifying uncultivable microorganisms, unknown genes, and pathways involved in bio-gas production from a wide range of biomass resources have been greatly enhanced by recent advances in omics technologies such as metagenomics, transcriptomics, proteomics, and metabolomics [131]. Most of the microorganisms and genes involved in biogas generation from different forms of biomass remain unknown due to a lack of optimum anaerobic reactor conditions essential for optimal microbial growth, despite the staggering number of research articles dedicated to identifying them. On the other hand, meta-omics approaches are potent instruments for analyzing microbial communities' gene, metabolite, and protein expression patterns that might be used as possible indicators of process performance during anaerobic digestion. Several contributions [132; 133; 134; 126] were able to provide a comprehensive evaluation of various meta-omics approaches. However, these meta-omics methods continue to rely on basic techniques such as transcriptomic, proteomics, and metabolomics; despite all of these being relevant, an overreaching approach specifically applicable to food waste management is still needed. Elsewhere, [PERSON] et al. [136] used maize silage (feedstock) in combination with pig/cattle dung in an optimized continuously stirred tank reactor (CSTR) in which bio-gas was produced. The dominant species in the CSTR system was determined to be _Porphromondaceae_ bacterium using next-generation sequencing (NGS) technology, i.e.,  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Bioprocess Engineering Techniques** & **Nanotechnology Techniques** & **Omics Techniques** & **Artificial Intelligence** & **Treatment Method** & **Biogas Yield/\% Increase** & **References** \\ \hline
20\% \(\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\textIllumina MiSeq system, whereby the bacteria's entire genome sequence was established. Numerous researchers have also concentrated on transcriptomic-linked bioprocessing engineering systems used in biogas production. Transcriptomics studies an organism's whole transcriptome (RNA or mRNA). Transcriptomics analysis may be critical in identifying the essential microbes with the relevant genes and metabolites. In biogas generating systems, for instance, _Clostridia_ were shown to be the predominant class of hydrolytic organisms, playing a crucial role in the first stages of biomass degradation as evidenced by transcriptome analysis [137; 138; 139; 140]. It is evident from these explorations that the use of transcriptomic approaches in conjunction with other technologies may aid in the advancement of our understanding of anaerobic digestion. Proteomics often refers to the comprehensive analysis of an organism's protein components. In contrast, \"metaproteomics\" refers to the study of all the proteins expressed by complex microbial communities in a given environment and at a given time [133]. For instance, proteins extracted from anaerobic digesters may be isolated and sequenced using tandem mass spectrometry (MS/MS) [133; 139; 141]. Several authors [142; 143; 144; 145] have attempted to integrate proteomics during anaerobic digestion processes. Perhaps the most outstanding discoveries were made by [PERSON] et al. [127], who used tandem mass tag (TMT) proteomics to determine the amount of _Methanosarcina_ spp. proteins that were changed by carbon nanotubes (CNTs). Numerous genes involved in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were differentially expressed, indicating a direct involvement of carbon nanotubes in cell structure and function. These findings contributed to yet a greater understanding of the effect of conductive materials on the biomethane formation process, highlighting the need to incorporate proteomic techniques into studies of biomethane production.