Publication Type

Journal Article

Publication Date (Issue Year)

2024

Journal Name

MDPI-Agriculture

Abstract

This study presents PlanteSaine, a novel mobile application powered by Artificial Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina Faso. Agriculture in Burkina Faso, like many developing nations, faces substantial challenges from plant pests and diseases, posing threats to both food security and economic stability. PlanteSaine addresses these challenges by offering a comprehensive solution that provides farmers with real-time identification of pests and diseases. Farmers capture images of affected plants with their smartphones, and PlanteSaine’s AI system analyzes these images to provide accurate diagnoses. The application’s offline functionality ensures accessibility even in remote areas with limited Internet connectivity, while its messaging feature facilitates communication with agricultural authorities for guidance and support. Additionally, PlanteSaine includes an emergency alert mechanism to notify farmers about pest and disease outbreaks, enhancing their preparedness to deal with these threats. An AI-driven framework, featuring an image feature extraction phase with EfficientNetB3 and an artificial neural network (ANN) classifier, was developed and integrated into PlanteSaine. The evaluation of PlanteSaine demonstrates its superior performance compared to baseline models, showcasing its effectiveness in accurately detecting diseases and pests across maize, tomato, and onion crops. Overall, this study highlights the potential of PlanteSaine to revolutionize agricultural technology in Burkina Faso and beyond. Leveraging AI and mobile computing, PlanteSaine provides farmers with accessible and reliable pest and disease management tools, ultimately contributing to sustainable farming practices and enhancing food security. The success of PlanteSaine underscores the importance of interdisciplinary approaches in addressing pressing challenges in global agriculture

Keywords

artificial intelligence in agriculture, pest and disease detection, mobile application for farmers, Burkina Faso agriculture, real-time plant diagnosis, sustainable farming practices

Grantee Name(s)

Obed Appiah

Type of Grant

Grant – AGRiDI

Thematic Area

ICTs Including Big Data and Artificial Intelligence

Funding Statement

This work benefited from the support of other experts and institutions. Notable among them are the extension officers (particularly those from the Centre-Ouest, Centre-Sud, and Plateau Centrale regions) and experts of the General Directorate of Plant Production (DGPV) under the Ministry of Agriculture. Special thanks also go to the staff of WASCAL including Jesse Naab, Momo Bebe, Ivan Bessin, Audrey Codjia, Kisito Gandji, and Melika Vodounhessi who contributed in different ways.

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