New article in Current Research in Food Science: Balancing Nutrition and Antioxidant Capacity in Extruded Foods

Xu Zhou, Keer Ni, Pranav Gupta, and Prof. Ilias Tagkopoulos published Computational optimization of food formulation and extrusion conditions for nutritional quality and antioxidant capacity in Current Research in Food Science on 7/22/2026.

About this work: How can food processing be optimized to preserve nutrition while enhancing beneficial bioactive compounds? This work introduces a computational framework that combines an ingredient-level nutrient and phytochemical database, mechanistic kinetic models, machine learning, and global optimization, using extrusion processing as a case study. The authors curated 503 ingredient records from 2,000 peer-reviewed papers and commercial supplier data and evaluated 20 food formulations. At a simulated reference extrusion condition of 140 °C for 30 seconds, the model predicted that nutritional quality, measured by the NRF9.3 score, decreased by an average of 10.7%, while predicted antioxidant capacity increased by an average of 25%. Ingredient sourcing was also a major source of uncertainty, typically contributing 3 to 11 times more variation in nutritional quality than processing itself. By tailoring extrusion temperature and residence time to each formulation, the framework predicted an average 10% improvement in the combined nutrition–antioxidant score over the reference condition, with improvements reaching up to 44%. The results highlight how ingredient selection, sourcing, and processing conditions can be considered together to systematically design food-processing strategies, while the authors note that the computational predictions still require experimental validation.

Reference: Zhou, Xu, Keer Ni, Pranav Gupta, and Ilias Tagkopoulos. “Computational optimization of food formulation and extrusion conditions for nutritional quality and antioxidant capacity.” Current Research in Food Science 13 (2026): 101509. doi: 10.1016/j.crfs.2026.101509.