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However, the industrial conversion of this heterogeneous biomass into standardized functional food ingredients is currently impeded by significant techno\u2010economic barriers, primarily structural recalcitrance, compositional inconsistency, and the presence of toxic fermentation inhibitors. This review provides a comprehensive analysis of the synergistic application of microbial engineering and artificial intelligence (AI) to resolve these bioprocessing bottlenecks within a food\u2010to\u2010food closed\u2010loop framework (as shown in the graphical abstract). We evaluate recent advances in engineering food\u2010grade microbial chassis (e.g.,\n                    <jats:italic>Saccharomyces cerevisiae<\/jats:italic>\n                    and\n                    <jats:italic>Escherichia coli<\/jats:italic>\n                    ) to enhance lignocellulose degradation and stress tolerance. Concurrently, we examine the integration of AI across the entire value chain, covering deep learning\u2010based rational enzyme design, genome\u2010scale metabolic modeling, and intelligent process control for precision fermentation. Current evidence demonstrates that the hardware\u2013software coupling of engineered strains and AI algorithms significantly enhances conversion efficiency and process robustness. Key findings highlight that AI\u2010driven Design\u2013Build\u2013Test\u2013Learn cycles facilitate the de novo creation of enzymes with superior kinetics and strains with adaptive stress response capabilities against toxins. Moreover, dynamic digital twin models effectively mitigate the impact of substrate variability, ensuring the batch\u2010to\u2010batch consistency required for food applications. We conclude that this data\u2010driven synergistic paradigm is pivotal for establishing a resilient circular bioeconomy, enabling the reliable bioconversion of waste into high\u2010value single\u2010cell proteins, natural flavor additives, and sustainable packaging materials.\n                  <\/jats:p>","DOI":"10.1111\/1541-4337.70611","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T02:59:06Z","timestamp":1788231546000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence"],"prefix":"10.1111","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-6087-9823","authenticated-orcid":false,"given":"Jiajin","family":"Sun","sequence":"first","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongbo","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingwei","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chongpeng","family":"Bi","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianping","family":"Li","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anshan","family":"Shan","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology Northeast Agricultural University  Harbin 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