Predicting the Kinetics and energy efficiency of drying the medicinal plant Lemon verbena (Lippia citriodora Kunth) using artificial neural networks | ||
| فناوری و گیاهان دارویی ایران | ||
| Volume 7, Issue 1 - Serial Number 12, July 2024, Pages 151-138 PDF (1.72 M) | ||
| Document Type: Original Article | ||
| DOI: 10.22092/mpt.2025.370955.1204 | ||
| Authors | ||
| Hamid Khafajeh* 1; Mohammad Zarien2; Mohammad Younesi Alamouti3 | ||
| 1Biosystems Engineering Department, Jahrom University, Jahrom, Iran | ||
| 2Biosystems Engineering Department, Tarbiat Modares University, Tehran, Iran | ||
| 3Imam Khomeini Higher Education Center, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| Abstract | ||
| Medicinal plants are one of the most important primary resources used in the food and pharmaceutical industries. Drying is one of the oldest methods of preserving medicinal plants. In this study, the effect of different microwave powers (25%, 50%, 75% and 100% power) and product thicknesses of 3 and 6 mm on drying behavior, effective diffusion coefficient, best mathematical model of drying, activation energy values and energy consumption in medicinal plant (Lippia citriodora Kunth) was investigated. The results showed that the lowest effective diffusion coefficient was 1.329×10-6 m2/s at 3 mm thickness and 25% power and the highest value was 2.486×10-5 m2/s at 6 mm thickness and 100 power. Also, in this research, different drying parameters and different topologies of MLP artificial neural network were investigated and evaluated to determine the best network for lemon plant with microwave dryer. The obtained results showed that the best training model was obtained with 3-15-3 MLP network with 15 neurons in the hidden layer with the highest coefficient of determination (0.952) and the lowest root mean square error (0.154). | ||
| Keywords | ||
| Lemon verbena; dryer; kinetics; microwave; neural network | ||
| References | ||
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