Maturity Level: 3
Compost from Millet and Fonio Crop Residues
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This innovation involves producing compost using millet and fonio crop residues combined with organic activators. It provides a low-cost alternative to mineral fertilizers, improving soil fertility, increasing fonio yields by up to 46%, and supporting sustainable agriculture practices in Mali. The method enhances degraded soils while boosting productivity and farmer income, especially for women producers.…
Co-composting of Organic Waste with Human Urine and Excreta
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This document describes an agroecological innovation that transforms pre- and post-consumption organic waste combined with human urine and excreta into high-quality compost. It addresses soil infertility, high fertilizer costs, and poor waste management in Sahelian regions, offering a low-cost, sustainable solution that improves soil fertility, boosts crop yields, and reduces environmental pollution. Organisation: Université Boubakar Bâ…
Fonio Production Technology in Mali
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This technical sheet presents fonio (Digitaria exilis) as a resilient crop suitable for poor and degraded soils, contributing to food security and income diversification in dry areas. Improved varieties such as Peazo show strong performance with yields exceeding 1 ton per hectare and revenues around 700,000 FCFA/ha. The document outlines production steps, challenges, and impacts…
Phospho-Compost Technology for Soil Fertility Improvement
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This document presents a composting technique enriched with natural phosphate to improve soil fertility and crop nutrition in phosphorus-poor Sahelian soils. Developed under the CATHI-GAO project, it uses locally available biomass and Tahoua phosphate to enhance millet yields sustainably. The method includes detailed composting steps and demonstrates significant yield improvements. Organisation: CATHI-GAO Project / INRAN Author: Zounon…
Food diversification: potential of mungbean
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This document presents the potential of mungbean (Vigna radiata) as a crop for food diversification in semi-arid regions, particularly in Burkina Faso. It highlights its nutritional value, drought tolerance, and short growth cycle, along with agronomic practices and yield comparisons with other legumes. It also discusses farmer perceptions, including constraints such as labor-intensive harvesting and…
AgroGaskiyAI Crop Yield Prediction Model
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AgroGaskiyAI is a hybrid artificial intelligence model designed to predict agricultural yields, analyze production variability factors, and support strategic decision-making. It integrates biophysical data and farmer knowledge into a unified, explainable system, helping anticipate production deficits and optimize resource allocation in climate-vulnerable farming systems. Organisation: FUMA Gaskiya Author: Mahaman Lawali Inoussa Garba; Naroua Harouna; Chaibou Kadri; Maman…

