PlanteSaine: An Artificial Intelligent Empowered Mobile Application for Pests and Disease Management for Maize, Tomato, and Onion Farmers in Burkina Faso

Obed Appiah (), Kwame Oppong Hackman, Belko Abdoul Aziz Diallo, Kehinde O. Ogunjobi, Son Diakalia, Ouedraogo Valentin, Damoue Abdoul-Karim and Gaston Dabire
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Obed Appiah: Competence Centre, West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Blvd Mouammar Kadafi, Patte d’oie, Ouagadougou 06 BP 9507, Burkina Faso
Kwame Oppong Hackman: Competence Centre, West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Blvd Mouammar Kadafi, Patte d’oie, Ouagadougou 06 BP 9507, Burkina Faso
Belko Abdoul Aziz Diallo: Competence Centre, West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Blvd Mouammar Kadafi, Patte d’oie, Ouagadougou 06 BP 9507, Burkina Faso
Kehinde O. Ogunjobi: Competence Centre, West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Blvd Mouammar Kadafi, Patte d’oie, Ouagadougou 06 BP 9507, Burkina Faso
Son Diakalia: Directorate of Plant Protection and Packaging (DPVC), Ministry of Agriculture, Animal Resources and Fisheries (MARAH), Ouagadougou 03 BP 7005, Burkina Faso
Ouedraogo Valentin: Competence Centre, West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Blvd Mouammar Kadafi, Patte d’oie, Ouagadougou 06 BP 9507, Burkina Faso
Damoue Abdoul-Karim: Afrique Géosciences, S/C 11 BP 178 Ouaga CMS 11, Ouagadougou, Burkina Faso
Gaston Dabire: Gaoua University Center, Nazi BONI University, Bobo-Dioulasso 01 BP 1091, Burkina Faso

Agriculture, 2024, vol. 14, issue 8, 1-23

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 (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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