Research Article

Food styling and food photography with generative AI

Volume: 6 Number: 2 January 7, 2025
EN

Food styling and food photography with generative AI

Abstract

The objective of this study is to evaluate the aesthetic suitability of generative AI food images and to examine the potential role of AI in food styling and photography, including its strengths, weaknesses, opportunities, and threats. In this research, eight dishes from Turkish cuisine, Imambayıldı and Zeytinyağlı enginar (artichoke with extra virgin olive oil) for the olive oil theme, Adana kebab and Hünkâr beğendi for the main course theme, fırında sütlaç (baked rice pudding) and pumpkin dessert for the dessert theme, çay (Turkish tea) and Turkish coffee for the beverage theme, were produced separately using Adobe Firefly 3 and DALL-E 3 Artificial Intelligence (AI) applications. Real food photographs were also included for comparison. Thirty-one professional food stylists and photographers volunteered and participated in the study. Consequently, a total of 24 food images were created and evaluated by professionals according to six aesthetic criteria: lighting, color, composition, presentation, appropriateness of the props and background, and the creation of a mouth-watering sensation. The findings reveal no significant difference between the food photographs produced using the AI 1 application and real food photographs. Half of the images created by the AI 2 application also showed no significant differences compared to real images. However, significant differences were observed in five images between the two AI applications. Participants highlighted low costs, fast production, and flexibility as strengths of AI applications in food styling and photography. Conversely, weaknesses included the production of surreal images and aesthetic concerns. Opportunities were identified in fostering innovation, creativity, and new perspectives, while potential threats involved ethical and copyright concerns, overdependence on AI tools, and potential job displacement.

Keywords

Aesthetic, AI, Artificial Intelligence, Food Styling

Ethical Statement

Ethical approval was given by the Ankara Hacı Bayram Veli University Ethics Commission on 17.07.2024, with the number 280014.

Thanks

This study was presented orally at the 8th UGTAK 2024 congress.

References

  1. Baştürk, S., & Taştepe, M. (2013). Evren ve Örneklem. (Ed. S.Baştürk). Bilimsel araştırma yöntemleri, Ankara:Vize Yayıncılık.
  2. Bhattacharjee, G. (2023). Art and photography in the age of artificial intelligence. In 12th International Photographic Conference of PAD, Kolkata.
  3. Brady, E., & Prior, J. (2020). Environmental aesthetics: A synthetic review. People and Nature, 2(2), pp. 254-266.
  4. Boddy, J.R. (2016). Sample size for qualitative research. Qualitative Market Research, 19(4), pp. 426-432. doi:10.1108/QMR-06-2016-0053.
  5. Burger, B., Kanbach, D. K., Kraus, S., Breier, M., & Corvello, V. (2023). On the use of AI-based tools like ChatGPT to support management research. European Journal of Innovation Management, 26(7), pp. 233-241.
  6. Cankul, D., Ari, O.P., & Okumus, B. (2021). The current practices of food and beverage photography and styling in food business. Journal of Hospitality and Tourism Technology, 12(2), pp. 287-306.
  7. Califano, G., Zhang, T., & Spence, C. (2024). Would you trust an AI chef? Examining what people think when AI becomes creative with food. International Journal of Gastronomy and Food Science, 100973. https://doi.org/10.1016/j.ijgfs.2024.100973.
  8. Califano, G., & Spence, C. (2024). Assessing the visual appeal of real/AI-generated food images. Food Quality and Preference, 116, 105149. https://doi.org/10.1016/j.foodqual.2024.105149.
  9. Conolly, O., & Haydar, B. (2003). Aesthetic principles. The British Journal of Aesthetics, 43(2), pp. 114-125.
  10. Custer, D. (2010). Food styling: The art of preparing food for the camera. John Wiley & Sons.
APA
Güleç, H., & Özkaya, F. (2025). Food styling and food photography with generative AI. Journal of Tourism Leisure and Hospitality, 6(2), 90-103. https://doi.org/10.48119/toleho.1573824
AMA
1.Güleç H, Özkaya F. Food styling and food photography with generative AI. TOLEHO. 2025;6(2):90-103. doi:10.48119/toleho.1573824
Chicago
Güleç, Hakan, and Fügen Özkaya. 2025. “Food Styling and Food Photography With Generative AI”. Journal of Tourism Leisure and Hospitality 6 (2): 90-103. https://doi.org/10.48119/toleho.1573824.
EndNote
Güleç H, Özkaya F (January 1, 2025) Food styling and food photography with generative AI. Journal of Tourism Leisure and Hospitality 6 2 90–103.
IEEE
[1]H. Güleç and F. Özkaya, “Food styling and food photography with generative AI”, TOLEHO, vol. 6, no. 2, pp. 90–103, Jan. 2025, doi: 10.48119/toleho.1573824.
ISNAD
Güleç, Hakan - Özkaya, Fügen. “Food Styling and Food Photography With Generative AI”. Journal of Tourism Leisure and Hospitality 6/2 (January 1, 2025): 90-103. https://doi.org/10.48119/toleho.1573824.
JAMA
1.Güleç H, Özkaya F. Food styling and food photography with generative AI. TOLEHO. 2025;6:90–103.
MLA
Güleç, Hakan, and Fügen Özkaya. “Food Styling and Food Photography With Generative AI”. Journal of Tourism Leisure and Hospitality, vol. 6, no. 2, Jan. 2025, pp. 90-103, doi:10.48119/toleho.1573824.
Vancouver
1.Hakan Güleç, Fügen Özkaya. Food styling and food photography with generative AI. TOLEHO. 2025 Jan. 1;6(2):90-103. doi:10.48119/toleho.1573824