| Abstrakt: |
Environmental hurdles, in the form of climatic crises, have taken a toll on prevalence of medicinal plants, which served as the foundation for traditional medicine from time immemorial. Drying preserves medicinal plants, and analyzing drying kinetics enhances resource efficiency, including energy and time utilization. This study is the first to examine the drying kinetics of insulin plant leaves. In this study, insulin plant leaves were dried at different temperatures ("40 °C," "50 °C," and "60 °C") to determine optimal drying temperature and assess its mass transfer characteristics. Higher temperatures led to shorter drying times: 530 min at 40 °C, 290 min at 50 °C, and 155 min at 60 °C. Both mathematical models and artificial neural networks (ANN) were used to model drying characteristics, with the logarithmic model showing superior predictive performance among the mathematical models. ANN with the "Levenberg-Marquardt algorithm" and "TANSIGMOID transfer function" gave the best model with better prediction. Comparative analysis confirmed that ANN exhibited superior predictive capabilities. Effective moisture diffusivity followed an upward trend with temperature and 60 °C revealed a diffusivity of 2.4352 × 10−7 m2/s. Activation energy, at 42.124 kJ/mol, underscored utilization of a moderate level of energy to enhance moisture diffusivity within the sample. Color and microstructural analysis also revealed that 60 °C had better color attributes and agglomerative structures. Drying leaves at 60 °C expedited the drying process, enhanced mass transfer, and improved color characteristics. These results provided vital insights for utilizing dried insulin plant leaves in various nutraceutical products. [ABSTRACT FROM AUTHOR] |
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