Investigates optimal ultrasound conditions to maintain quality in pomegranate arils, suggesting effective preservation methods.
• Non-thermal ultrasound preserves quality and nutritional value of pomegranate arils. • Multi-objective modeling enabled the optimization of qualitative properties. • Controlled ultrasound duration protects bioactive compounds in pomegranate arils. • Storage duration is the main factor affecting physicochemical quality indicators. • Optimal ultrasound at 14 min and 9.7-day storage preserves product quality. In order to enhance the quality preservation of pomegranate arils and to develop an effective non-thermal technology, the present study investigated and optimized ultrasound treatment using modeling and multi-objective optimization. The scientific significance and industrial applicability of this research lie in its potential to reduce postharvest losses and to preserve the qualitative and physicochemical attributes of the product. The objective of the study was to determine the optimal ultrasound and storage conditions for maintaining quality indices, including total soluble solids (TSS), color parameters (a* and b*), overall acceptability (OA), and fungal decay (FD). The ranges of the independent variables were considered as ultrasound time (4–14 min) and storage duration (0–16 days). The optimization analysis using the response surface methodology (RSM) demonstrated that ultrasound treatment significantly enhanced the preservation of key physicochemical attributes compared to untreated samples, while storage duration remained the primary factor influencing overall quality degradation. The predicted values of the quality indices under optimal conditions were TSS = 16.3°Brix, a = 22.7, b = 1.64, OA = 4.6, and FD = 5.01%. The findings demonstrated high model accuracy, satisfactory predictive capability, and the positive effect of ultrasound treatment on maintaining organoleptic and biochemical characteristics. This non-thermal technology enables improvement of product quality, reduction of losses, effective postharvest management, and development of advanced storage systems, and it can be applied as a scientific and practical strategy within the cold chain of sensitive products.
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Isa Hazbawi (2026) studied this question.
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