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Hatami, Shahnaz, Hatami Badrbani, Mohammad, Kahrizi, Danial. (1403). Data Mining Approach in the Agricultural Industry, Medicinal Plants (case study) A Review. سامانه مدیریت نشریات علمی, 13(2), 247-256. doi: 10.22034/jmpb.2024.364419.1636
Shahnaz Hatami; Mohammad Hatami Badrbani; Danial Kahrizi. "Data Mining Approach in the Agricultural Industry, Medicinal Plants (case study) A Review". سامانه مدیریت نشریات علمی, 13, 2, 1403, 247-256. doi: 10.22034/jmpb.2024.364419.1636
Hatami, Shahnaz, Hatami Badrbani, Mohammad, Kahrizi, Danial. (1403). 'Data Mining Approach in the Agricultural Industry, Medicinal Plants (case study) A Review', سامانه مدیریت نشریات علمی, 13(2), pp. 247-256. doi: 10.22034/jmpb.2024.364419.1636
Hatami, Shahnaz, Hatami Badrbani, Mohammad, Kahrizi, Danial. Data Mining Approach in the Agricultural Industry, Medicinal Plants (case study) A Review. سامانه مدیریت نشریات علمی, 1403; 13(2): 247-256. doi: 10.22034/jmpb.2024.364419.1636

Data Mining Approach in the Agricultural Industry, Medicinal Plants (case study) A Review

Journal of Medicinal Plants and By-products
مقاله 1، دوره 13، شماره 2، شهریور 2024، صفحه 247-256    اصل مقاله (960.01 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22034/jmpb.2024.364419.1636
نویسندگان
Shahnaz Hatami* 1؛ Mohammad Hatami Badrbani2؛ Danial Kahrizi3
1Department of Industrial Engineering, Faculty of Industrial Engineering, System Management and Productivity, Arak Branch, Islamic Azad University, Arak, Iran
2Animal Science Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Alborz, Iran
3Agricultural Biotechnology Department, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
چکیده
In the realm of agriculture and natural resources, medicinal plants stand out as a valuable resource. In recent years, faced with challenges such as predicting climate changes, soil classification, land use, and identifying patterns, there is a growing need for optimal techniques with higher efficiency, particularly in the cultivation of medicinal plants. Therefore, this article introduces the application of data mining to analyze available data in the agriculture and natural resources areas, focusing specifically on the medicinal plant industry. The primary objective is to explore data mining techniques that can enhance various aspects of medicinal plant cultivation, addressing challenges related to climate predictions, soil classification, and optimizing production. The article concludes by presenting the most effective data analysis methods in this domain, accompanied by their corresponding algorithms. Additionally, the aforementioned research is a guide for those intending to investigate the applications of data mining methods are highlighted for increased productivity, encompassing areas such as predicting crop yield, forecasting weather conditions, rainfall patterns, seed and plant conditions, soil quality, and medicinal plant production. The summarization and analysis of the outcome indicated that implementing AI could improve the design and process engineering strategies in bioprocessing fields.
کلیدواژه‌ها
Data mining؛ Medicinal plants؛ Classification؛ Clustering
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