Browsing by Author "Musa, A."

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    An Exploratory Data Analysis of Growth, Pest Infestation and Treatment Dataset Towards Improved Prediction of Cowpea Yield
    (FUOYE Journal of Pure and Applied Sciences, 2025-04-10) Babatunde, R. S; Musa, A.; Ajao, J. F.; Isiaka, R. M.; Ojo, J. A.; Abdulrahman, L. O; Mohammend, A. K.
    The rising need for food security requires creative agricultural methods, especially in the farming of essential crops such as cowpea (Vigna unguiculata). This research introduces an improved automated forecasting system for cowpea production utilizing machine learning methods, drawing on an extensive dataset comprising factors like plant growth metrics, pest presence, and treatment methods. Utilizing regression models and sophisticated algorithms, the system examines past growth data to determine significant factors affecting yield results. Preliminary findings indicate a strong relationship between growth indicators like plant height at different developmental phases and the overall yield. The predictive model will not only enable prompt actions in crop management but also assists farmers in making refined choices to enhance production. Ultimately, this study aids in crafting precision agriculture techniques that improve cowpea production while tackling issues arising from pests and environmental factors. This automated method indicates a way to enhance agricultural output and sustainability in areas dependent on cowpea as an essential food source.