Cahiers Agricultures est une revue scientifique sur les agricultures du monde, leurs évolutions et leur place dans les sociétés

To assess producers’ exposure level to pesticides in vegetable production in Burkina Faso, a study was carried out in 2016 and 2017 among 30 tomato producers in the municipalities of Kouka and Toussiana. Eighteen (18) commercial formulations were identified, with more than 50% of pesticides destined for cotton production. Eleven active substances have been identified and the most frequently used are λ-cyhalothrin (35%), acetamiprid (22%) and profenofos (13%). The most commonly used chemical families are pyrethroids (28%) and organophosphates (18%). The study revealed a low level of training for producers, a high use of pesticides according to the Frequency Treatment Indicator, and a very low level of protection used by producers. The Health Risk Index shows that active substances such as methomyl, λ-cyhalothrin and profenofos present very high risk to operators’ health. Based on the UK-POEM model, the predictive exposure levels obtained varied from 0.0105 mg/kg body weight/day to 1.7855 mg/kg body weight/day, which is several times higher than the Acceptable Operator Exposure Level. However, the study also shows that exposure can be greatly reduced if the required Personal Protective Equipment is worn. Producers’ awareness and training on integrated pest management are necessary to reduce the risks linked to the pesticides use in Burkina Faso.

D. Son, S. Bonzi, I. Somda, T. Bawin, S. Boukraa, F. Verheggen, F. Francis, A. Legreve, and B. Schiffers (2017) First Record of Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae) in Burkina Faso. African Entomology: Vol. 25, No. 1, pp. 259-263. https://doi.org/10.4001/003.025.0259

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

Effect of plant diversification on pest abundance and tomato yields in two cropping systems in Burkina Faso: farmer practices and integrated pest management

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