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dc.citation.startPage 109691 -
dc.citation.title INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY -
dc.citation.volume 372 -
dc.contributor.author Sharma, Poonam -
dc.contributor.author Vimal, Archana -
dc.contributor.author Vishvakarma, Reena -
dc.contributor.author Kumar, Pradeep -
dc.contributor.author Vandenberghe, Luciana porto de Souza -
dc.contributor.author Gaur, Vivek Kumar -
dc.contributor.author Varjani, Sunita -
dc.date.accessioned 2023-12-21T14:06:54Z -
dc.date.available 2023-12-21T14:06:54Z -
dc.date.created 2022-06-29 -
dc.date.issued 2022-07 -
dc.description.abstract It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the world. Inception of modern techniques like omics (metagenomics, proteomics, transcriptomics, wasteomics, diseaseomics etc), enzymatic treatments, and artificial intelligence in food waste reduction and management can bring a sustainable solution for food loss management, starvation and environmental challenges. Acceptance of modern techniques while policies formulation by government bodies can substantially strengthen the idea of waste reduction, food security and can easily save the life of around 25,000 children and adults dying of starvation every day. Artificial Intelligence (AI) can bestead current agriculture and food supply chain system to overcome the challenges of nutrition demand, resource depletion, climate change, population growth, and pollution. This communication provides a thorough examination of the concept of food waste management with omics approaches linkages. In addition, the notion of artificial intelligence in food waste transformation and mitigation, as well as present challenges and future prospects have been covered. Overall, this communication would assist decision-makers in identifying economically and environmentally appropriate biorefinery solutions ahead of time. -
dc.identifier.bibliographicCitation INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, v.372, pp.109691 -
dc.identifier.doi 10.1016/j.ijfoodmicro.2022.109691 -
dc.identifier.issn 0168-1605 -
dc.identifier.scopusid 2-s2.0-85129684192 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/58976 -
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S0168160522001635?via%3Dihub -
dc.identifier.wosid 000803813800006 -
dc.language 영어 -
dc.publisher ELSEVIER -
dc.title Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Food Science & Technology; Microbiology -
dc.relation.journalResearchArea Food Science & Technology; Microbiology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Metagenomics -
dc.subject.keywordAuthor Omics approaches -
dc.subject.keywordAuthor Artificial intelligence -
dc.subject.keywordAuthor Food security -
dc.subject.keywordAuthor Valorization -
dc.subject.keywordPlus SUSTAINABLE MANAGEMENT -
dc.subject.keywordPlus PROCESSING WASTE -
dc.subject.keywordPlus KITCHEN WASTE -
dc.subject.keywordPlus POLICY -
dc.subject.keywordPlus INDUSTRIAL -
dc.subject.keywordPlus CHITINASE -
dc.subject.keywordPlus PRODUCTS -
dc.subject.keywordPlus EFFLUENT -
dc.subject.keywordPlus ETHANOL -

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