Toward intelligent crop production management decision support system through data fusion

Abu Bakar B., . and Mohd Noh A., . and Baharom S.N.A., . and Ahmad M.T., . and Ten, S.T and Muhd Bookeri M.A., . and Zakaria N.K., . and Ahmad Sayuti A.F., . and Zubir M.N., . (2023) Toward intelligent crop production management decision support system through data fusion. International Journal of Agriculture, Forestry and Plantation (Malaysia), 13. pp. 58-63. ISSN 2462-1757

Integration of data from various sources provide farmers with useful information and recommendations for managing their crops. Data fusion techniques can be used to combine data from different sources such as weather forecasts, satellite imagery, soil sensors, and crop growth models to create a holistic view of the crop's growing conditions. An intelligent system can use this information to provide farmers with real-time recommendations on things like irrigation, fertilization, pest control, and harvest timing. By using data fusion, the system can improve the accuracy of its predictions and recommendations, resulting in better crop yields and reduced costs for farmers. The data can also be analyzed by agronomists and researchers to improve crop management practices and develop new crop varieties. Toward this end, a system is being developed to fuse data from multiple sensors and multiple sites for two crops, namely pineapple in the open field and leafy vegetables planted indoors. It is hoped that the developed system can help farmers to make more informed decisions, improve crop yields, and increase their profits while helping to conserve resources such as water and fertilizer.

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Abstract

Integration of data from various sources provide farmers with useful information and recommendations for managing their crops. Data fusion techniques can be used to combine data from different sources such as weather forecasts, satellite imagery, soil sensors, and crop growth models to create a holistic view of the crop's growing conditions. An intelligent system can use this information to provide farmers with real-time recommendations on things like irrigation, fertilization, pest control, and harvest timing. By using data fusion, the system can improve the accuracy of its predictions and recommendations, resulting in better crop yields and reduced costs for farmers. The data can also be analyzed by agronomists and researchers to improve crop management practices and develop new crop varieties. Toward this end, a system is being developed to fuse data from multiple sensors and multiple sites for two crops, namely pineapple in the open field and leafy vegetables planted indoors. It is hoped that the developed system can help farmers to make more informed decisions, improve crop yields, and increase their profits while helping to conserve resources such as water and fertilizer.

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Item Type:	Article
AGROVOC Term:	pineapples
AGROVOC Term:	crop production
AGROVOC Term:	decision support
AGROVOC Term:	irrigation
AGROVOC Term:	fertilization
AGROVOC Term:	pest control
AGROVOC Term:	harvesting
AGROVOC Term:	precision agriculture
AGROVOC Term:	farm management
AGROVOC Term:	agronomy
Geographical Term:	Malaysia
Depositing User:	Mr. Khoirul Asrimi Md Nor
Date Deposited:	04 Jun 2026 06:47
Last Modified:	04 Jun 2026 06:47
URI:	http://webagris.upm.edu.my/id/eprint/3963

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