https://ph04.tci-thaijo.org/index.php/abe/issue/feed 2025-04-12T21:22:44+07:00 Somchai Chuan-Udom abe@kku.ac.th Open Journal Systems <div> <p><strong>Agricultural and Biological Engineering (ABE)</strong> is a peer-reviewed open-access journal. The journal aims to publish high quality research in <strong>engineering</strong> and the physical sciences that represent advances in <strong>agriculture</strong> and<strong> biological systems</strong>. </p> </div> <table border="0"> <tbody> <tr> <td><strong>Journal Abbreviation:</strong> Agr Biol Eng</td> </tr> <tr> <td><strong>ISSN:</strong> 3056-932X (Online)</td> </tr> <tr> <td><strong>Start year:</strong> 2024</td> </tr> <tr> <td><span style="font-weight: bolder;">Language:</span> English</td> </tr> <tr> <td><span style="font-weight: bolder;">Publication fee:</span> free of charge</td> </tr> <tr> <td> <span style="font-weight: bolder;">Issues per year:</span> 4 Issues</td> </tr> <tr> <td> </td> </tr> <tr> <td> </td> </tr> </tbody> </table> <p> <strong>Focus and Scope</strong></p> <p><strong>Agricultural and Biological Engineering (ABE)</strong> publishes research in <strong>engineering</strong> and <strong>the physical sciences</strong> that represent advances in <strong>agriculture</strong> and<strong> biological systems</strong> for sustainable developments in soil and water, land use, bioproduction processes and processing, machines and mechanization system, equipment and buildings, and logistics. Papers may report the results of experiments, theoretical analyses, development, design, innovations, analytical techniques, and instrumentation.</p> <p> </p> <p><a href="https://ph04.tci-thaijo.org/index.php/abe/issue/view/84">Download ABE Template</a></p> https://ph04.tci-thaijo.org/index.php/abe/article/view/8798 2025-02-28T12:50:19+07:00 Jarinee Jongpluempiti Jarinee.jo@rmuti.ac.th Metinan Kulanad jarinee.jo@rmuti.ac.th Nattida Nuankhamsing jarinee.jo@rmuti.ac.th Bunleab Chea jarinee.jo@rmuti.ac.th Ponthep Vengsungnle Ponthep.ve@rmuti.ac.th

<p>This research focuses on the development of an agricultural drying house with multi-zone airflow management using Computational Fluid Dynamics (CFD) combined with Genetic Algorithm (GA) to enhance drying efficiency. The experiment compared the results of a conventional drying house with the improved version by analyzing drying time, energy consumption, average product moisture content, and drying uniformity. The results demonstrated that the drying house utilizing CFD and GA techniques reduced drying time by an average of 30.0 ± 2.6%, decreased energy consumption by 25.0 ± 2.0%, reduced the average product moisture content from 15.5 ± 1.0% to 10.5 ± 0.6%, and increased drying uniformity from 70.0 ± 3.5% to 90.1 ± 2.4%, all with statistical significance. These findings reflect the capability of CFD and GA technologies to improve efficiency, reduce production costs, and enhance the quality of products sustainably. This technology holds significant potential for advancing drying processes in agriculture and the food industry in the future.</p>

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