Process Optimization and Uncertainty Analysis of IoT‐Integrated Cyclic Microwave‐Assisted Extraction (CMAE) for Vanillin Recovery
Year: 2026
Type: article
Abstract: Vanillin, the principal flavor compound in vanilla, is a high‐value natural product whose conventional extraction is often limited by low efficiency and high energy consumption. Although microwave‐assisted extraction (MAE) has improved extraction efficiency, most systems rely on continuous operation with limited real‐time process monitoring. To address this limitation, an IoT‐integrated cyclic microwave‐assisted extraction (CMAE) system was developed for vanillin recovery from Vanilla planifolia . The system incorporated an infrared temperature sensor, a solid‐state relay, an ESP32 microcontroller, and a Node‐RED interface to enable real‐time temperature monitoring and programmable cyclic microwave operation. Response surface methodology identified optimal conditions of 436 W microwave power, 16.93 min extraction time, 3.45 g sample mass on a dry‐weight basis, and 75% ethanol, with a predicted vanillin content of 3.13% DW, equivalent to a yield of 31.29 mg/g DW. Monte Carlo simulation yielded a 95% uncertainty interval of 29.41–33.16 mg/g DW (2.94%–3.32% DW), whereas sensitivity analysis identified microwave power and ethanol concentration as the most influential variables. Experimental validation under approximately energy‐equivalent conditions of 380 W for 19.44 min and 500 W for 14.78 min yielded 30.43 and 30.98 mg/g DW, respectively, with deviations from the predicted value below 3%. Assuming equivalent vanillin recovery, cyclic operation reduced the calculated nominal microwave energy input and specific energy consumption (SEC) by 16.7% relative to a calculated continuous‐operation baseline. The developed CMAE system provides a data‐driven extraction platform integrating IoT‐based monitoring, programmable cyclic operation, process optimization, and uncertainty analysis, with potential application in energy‐conscious phytochemical extraction.
DOI: 10.1155/ijfo/4384246
Language: English
Subfield: Biotechnology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $860
Funder: Chiang Rai Rajabhat University
Award: G9000498735
OpenAlex ID: W7214725977
