Artificial intelligence in gastronomy: a bibliometric analysis of research foundations and emerging themes
Yazarlar (2)
Doç. Dr. Hasan Evrim ARICI Kastamonu Üniversitesi, Türkiye
Doç. Dr. Serkan ÇALIŞKAN Kastamonu Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | International Journal of Gastronomy and Food Science (Q2) | ||
| Dergi ISSN | 1878-450X Dergi Bilgileri (2026) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2026 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-06-2026 |
| Cilt / Sayı / Sayfa | 44 / 1 / – | DOI | 10.1016/j.ijgfs.2026.101530 |
| Makale Linki | https://doi.org/10.1016/j.ijgfs.2026.101530 | ||
| UAK Araştırma Alanları |
Otel İşletmeciliği
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| Özet |
| The integration of artificial intelligence (AI), machine learning (ML), deep learning (DL), and robotics is increasingly transforming gastronomy through applications such as AI-assisted flavour profiling, recipe generation, intelligent food safety monitoring, and robotic service delivery, with implications for operational efficiency, creativity, sustainability, and consumer experience. Despite a growing body of literature, research in this area remains fragmented and lacks a comprehensive field-level synthesis. Addressing this gap, the present study conducts a systematic bibliometric analysis of AI-related research in gastronomy. Using a PRISMA-guided approach, 112 SSCI-indexed journal articles retrieved from the Web of Science Core Collection were analysed through co-citation and bibliographic coupling techniques with VOSviewer. The findings reveal established intellectual foundations alongside emerging research … |
| Anahtar Kelimeler |
| Artificial intelligence | Bibliometric analysis | Deep learning | Gastronomy | Machine learning |
Science Direct
Artificial intelligence in gastronomy: a bibliometric analysis of research foundations and emerging themes
BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 2 |