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ORIGINAL RESEARCH article

Front. Nutr.

Sec. Nutrition and Food Science Technology

Volume 12 - 2025 | doi: 10.3389/fnut.2025.1658452

This article is part of the Research TopicAI-Driven Advances in Personalized Nutrition through Optimization in Food ManufacturingView all 4 articles

AI-Guided Optimization of Traditional Bulgur Pilafs: Enhancing Sensory and Bioactive Properties through RSM-PSO Modeling

Provisionally accepted
  • 1Namik Kemal University, Tekirdağ, Türkiye
  • 2Pamukkale University, Pamukkale, Türkiye
  • 3Halic Universitesi, Beyoğlu, Türkiye
  • 4Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
  • 5North Dakota State University, Fargo, United States
  • 6Istanbul Saglik ve Teknoloji Universitesi, Istanbul, Türkiye
  • 7King Saud University, Riyadh, Saudi Arabia

The final, formatted version of the article will be published soon.

This study aimed to enhance the sensory and bioactive properties of pilafs prepared from three geographically indicated bulgur varieties—Siyez, Firik, and Karakilçik—through an AI-guided optimization approach combining Response Surface Methodology (RSM) and Particle Swarm Optimization (PSO). Different bulgur (130–150 g) and water (350–450 mL) ratios were tested to determine optimal formulations. Sensory evaluation revealed that Firik bulgur pilaf achieved the highest overall acceptability (8.49), while Karakilçik bulgur pilaf scored highest in color (7.68) and aroma (8.58), and Siyez bulgur pilaf received the highest taste score (7.50). In terms of bioactive properties, Karakilçik bulgur pilaf showed the highest antioxidant capacity (75.57% DPPH radical scavenging activity), whereas Firik bulgur pilaf had the highest total phenolic (842.39 mg GAE/kg) and flavonoid contents (6.38 mg CE/g). Color analysis indicated that Siyez bulgur pilaf had the lightest color (L=52.18), while Firik pilaf exhibited the most intense red hue (a=8.12) and Karakilçik pilaf the darkest appearance (L=35.42). PSO-based validation confirmed the accuracy of RSM models by reaching global optima within 40 iterations and minimal deviation from experimental values. This is the first study to apply an integrated RSM–PSO modeling approach to traditional bulgur pilafs, enabling the prediction and optimization of their sensory and bioactive characteristics. The results provide a novel framework for enhancing the nutritional value and consumer appeal of heritage cereal-based foods and support the development of standardized, functional bulgur products for the food industry.

Keywords: particle swarm optimization (PSO), Bulgur pilaf, Sensory analysis, GeographicalIndication, personalized nutrition

Received: 02 Jul 2025; Accepted: 09 Oct 2025.

Copyright: © 2025 Yıkmış, Türk Aslan, Türkol, Şimşek, Aljobair, Karrar, Tokatlı and Mohamed Ahmed. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Seydi Yıkmış, syikmis@nku.edu.tr
Moneera Aljobair, moaljobair@pnu.edu.sa
Isam A. Mohamed Ahmed, iali@ksu.edu.sa

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