{
  "abstract": "Generative and foundation-model artificial intelligence can strengthen food analysis, but computational performance does not establish decision readiness. This systematic review examines applications and validation requirements in food safety, authenticity, and quality control. A Scopus search on 13 June 2026 identified 438 records; 65 publications were retained, including 41 direct analytical reports and 24 supporting publications. Independent dual screening and coding supported thematic synthesis and descriptive evidence mapping. The direct core comprised 18 safety-related, 4 authenticity, 9 quality-related, and 10 adjacent-domain reports. Of these, 23 reported experimental or reference-method validation, 13 dataset/model evaluation, and 5 human, sensory, or expert assessment. None of the 41 direct reports documented prospective evaluation in a real industrial setting. This finding remained unchanged in narrower-scope analyses, although the balance among experimental, dataset/model, and human-assessment validation changed. The generated food-evidence transfer gap integrates established transfer problems with food-specific decision requirements. Five cumulative gates organize provenance, technical validity, food-science validity, human calibration, and deployment governance. The framework connects generative-AI evidence requirements to established analytical standards rather than replacing them. Decision readiness requires risk-proportionate evidence for a specified use, including applicable reference-method and regulatory requirements. These findings characterize the captured literature, not the complete industrial deployment landscape.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Industrial Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates.",
    "CESI LINEACT, 15C Avenue Albert Einstein, 69100 Villeurbanne, France."
  ],
  "article_type": "review article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zied Bahroun",
      "orcid": "0000-0003-2832-3672"
    },
    {
      "affs": [
        1
      ],
      "name": "Mohamed Amine Abdeljaouad"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e48s32sdqqxvj.bib",
  "cited_by": 0,
  "doi": "10.3390/foods15193420",
  "fulltext_url": "https://europepmc.org/articles/PMC13664196",
  "id": "e48s32sdqqxvj",
  "issns": [
    "2304-8158"
  ],
  "landing_url": "https://europepmc.org/article/MED/42883527",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1602|Spectroscopy and Chemometric Analyses"
    ]
  ],
  "openalex": "W7214175989",
  "pdf_url": "https://europepmc.org/articles/PMC13664196?pdf=render",
  "pmcid": "PMC13664196",
  "pmid": "42883527",
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/e48s32sdqqxvj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:16Z",
      "native_id": "MED:42883527",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42883527"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1602|Spectroscopy and Chemometric Analyses",
      "subfield": "analytical"
    }
  ],
  "title": "Generative and Foundation-Model Artificial Intelligence in Food Safety Analysis, Authenticity Identification, and Quality Control: A Systematic Review of Validation and Decision Readiness.",
  "title_text": "Generative and Foundation-Model Artificial Intelligence in Food Safety Analysis, Authenticity Identification, and Quality Control: A Systematic Review of Validation and Decision Readiness.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:16Z",
  "url": "https://research.draconitic.com/paper/e48s32sdqqxvj",
  "venue": "Foods (Basel, Switzerland)",
  "versions": []
}