AI-Predicted Development of Compact Chocolate Bars for Crisis Scenarios: Physicochemical and Sensory Analyses

Background: AI has become an effective tool for optimizing new food formulations and has been applied in the development of several products. Objective: This study explored the role of Artificial Intelligence (AI) in predicting optimal formulations for Compact Chocolate Bars (CCBs), focusing on sensory and physicochemical analyses to meet nutritional needs during crisis scenarios, such as natural disasters and military operations. Methods: My Chef AI was used to formulate four different treatments incorporating apricots, black raisins, dates, and cranberries. The sensory evaluation was performed on the four treatments, and physicochemical analysis was performed for the best-scoring treatment. Results: The treatment incorporating black raisins has the highest sensorial score across age and gender groups. Furthermore, the newly developed CCBs met the RDA for energy, Protein, Carbohydrates, Fat, and iron content, but fell short of the RDA for sodium, calcium, and magnesium. Discussion: The AI-predicted formulation of CCBs has demonstrated promising results in terms of sensory evaluation, raw material selection, and product optimization. However, a larger population study to assess sensorial analysis and mineral micronutrient adjustments should be further investigated. Conclusion: Formulations incorporating a blend of dried fruits not only enhanced the nutritional profile but also improved sensory acceptance. Furthermore, physicochemical analysis demonstrated the stability of selected formulations under varying environmental conditions and their relatively small size, making them suitable for emergency food supplies. This research highlights the potential of AI-driven approaches in food technology to develop innovative CCBs that effectively meet dietary needs in crisis situations.