Integration of smart irrigation with AI-based disease detection: A field-based agro-technical evaluation for tomato (Solanum lycopersicum L.)
Paper Details
Integration of smart irrigation with AI-based disease detection: A field-based agro-technical evaluation for tomato (Solanum lycopersicum L.)
Abstract
This study, conducted in the Centre Region of Cameroon, evaluated the agronomic and economic effectiveness of an integrated production system for tomato cultivation (Solanum lycopersicum L.). The experimental design, a complete randomized block design, compared five treatments combining different irrigation methods (traditional manual vs. smart sensor-driven SynField) and phytosanitary control strategies (traditional preventive/curative vs. smart via the Agrix Maladies application). The aim was to address the sector’s major constraints: empirical water management, high disease pressure (late blight, early blight), and low profitability. The results demonstrated the systematic and synergistic superiority of the fully integrated treatment (IICI: Intelligent Irrigation + Intelligent Control). This treatment optimized plant physiology, leading to the best performance in height, number of leaves, and number of flowers. It produced the highest yield (20.06 t/ha), a record water use efficiency (WUE) of 85.6 kg/m³, and exceptional disease control (25% incidence for late blight and 0% for early blight). Economically, despite a higher total cost due to technology depreciation, the IICI system generated the largest gross margin (6,996,500 FCFA/ha), thanks to optimized input use and maximum production value. This research validates that a systemic approach, combining precision irrigation and targeted crop protection, is the most powerful lever for tomato production that is simultaneously productive, resource-efficient, sustainable, and profitable in Cameroon.
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Mvondo Nganti Dorothée*, Nchange Kouotou Adamou, Mefire Nchouwat Youssouf, Nana Modeste, Lombeko Tomo Obe Victorine, Manga Essouma François, 2026. Integration of smart irrigation with AI-based disease detection: A field-based agro-technical evaluation for tomato (Solanum lycopersicum L.). Int. J. Agron. Agric. Res., 28(2), 12-22.
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