Design and Validation of Automated Sensor-Based Artificial Ripening System Combined with Ultrasound Pretreatment for Date Fruits

Climate change affects fruit crops’ growth and development by delaying ripening, reducing color development, lowering quality yield. The irregular date palm ripening in the past few years is assumed to be related climatic change. current study aimed design validate an automated sensor-based artificial system (S-BARS) combined with ultrasound pretreatment for fruits cv. Khalas. A control was constructed allow continuous real-time recording over process variables. impact of processing variables, i.e., temperature (ART-temp) relative humidity (ART-RH) using designed S-BARS time (USP-Time) (USP-Temp) on required (RT), percentage ripened (PORF), damaged (PODF), electrical energy consumption (EEC) were investigated. quadratic predictive models developed Box–Behnken Design (B-BD) predict RT, PORF, PODF, EEC experimentally via Response Surface Methodology(RSM). Expert software (Version 13) used modeling graphically analyzing acquired data. parameter values determined solving regression equations 3D response surface plots. All parameters simultaneously optimized RSM desirability function. Mean Absolute Percentage Error (MAPE) Root Square (RMSE) between predicted actual experimental evaluate models. physicochemical properties assessed under optimization criteria. results indicated that pretreated unripe 40 kHz frequency, 110 W power, USP-Temp 32.49 °C 32.03 min USP-Time 60 ART-Temp 59.98% ART-RH achieved best results. precisely controlled at target setpoints. improved density artificially fruits, decreased RT EEC, increased PORF without negatively affecting studied attributes. could effectively EEC. efficient approach high-quality fruits.