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1. Digital platforms for boosting farmer knowledge: Two case studies in Kenya and UgandaApproximately 80% of all farms in Africa, or 33 million farms, are two hectares or less in size. Many of these smallholder farmers do not have access to resources, including extension services, to improve their farms. Lack of knowledge of Good Agronomic Practices (GAPs) causes farmers to fail to reach their full yield potential. Extension workers responsible to provide these GAPs to farmers are spread thin. For example, as of March of 2019, there was one extension worker for every 1,800 coffee... E. Bakirdjian, T. Harigaya, M. Osia, J. Zhu, J. Abuli |
2. Mapping spatial variability of soil nutrient deficiencies in smallholder villages – a prerequisite for improved crop production in AfricaSmallholder farming is the dominating type of agricultural production in many parts of Africa. If cultivation practices can be adapted to match the specific needs of individual smallholder plots, this can certainly be regarded as a form of precision agriculture (PA), considering their limited size. A fundamental prerequisite for successful application of PA is the availability of basic information on soil properties at a detailed enough level. To fill yield gaps, site specific information must... M. Söderström, K. Piikki, J. Kihara, J. Mutua, J. Wetterlind |
3. Decision Support System for Precision Agriculture management Case study : El Salihiya –east Nile delta, Egypt.Soil is a complex mixture of living organisms and organic material, along with soil minerals. the main objective of this work is develop a new methods to improve the agricultural management .The current study relies on developing a decision-making model for agricultural operations to manage potato crops in the El Salihiya area using field data,laboratory analysis and field sensor measurements. The precision agriculture decision support system entitled (EGYPADS) was designed and developed... A. Belal , S. abd el-kader, B. Mamdouh , M. A el-shirbeny, M. abdellatif1, M. Jalhoum , M. Zahran, E.S. Mohamed |
4. Sequencing integrated soil fertility management options for improved crop productivity and nutrient use efficiency on sandy soilsMaintaining high use efficiency of nutrient resources available to farmers is key to sustainable intensification of African smallholder farms. Multi-locational on-farm experiments were conducted on degraded sandy soils (< 10 % clay) in eastern Zimbabwe over 4 cropping seasons to evaluate different manure-, fertilizer- and legume-based integrated soil fertility management (ISFM) options with respect to maize productivity and, fertilizer nitrogen (N) and phosphorus (P) use efficiency.... H. Nezomba |
5. Keynote 3 - Setting the Record Straight on Precision Agriculture AdoptionAdoption of precision agriculture (PA) around the world has been uneven. Some PA technologies have been the most rapidly adopted agricultural technologies in history and others have lagged. Among the disappointments is variable rate fertilizer, which was among the first PA technologies, but has become standard practice only for some farming niches. PA is a tool box – Farmers take the tools that they need and leave the rest. For example, in countries with mechanized... J. Lowenberg-deboer |
6. Maximisation De L’efficience D’utilisation Des Nutriments : Recommandation De Fertilisation à La Carte Pour Le Maïs Sur Les Ferralsols Du Sud-togoL'amélioration de la nutrition des plantes à travers l'agriculture de précision devient incontournable pour l'optimisation de l'entreprise agricole et la protection de l'environnement. Nous avons conduit pendant la grande saison culturelle de 2019 et 2020, sous culture de maïs (Zea mays L.), des essais soustractifs à base de l'azote (N), du phosphore (P) et du potassium (K) à la station d'expérimentations agronomiques (SEAL)... J. Sogbedji, L. William, M. Lare, A. Sekaya, K. Sika , E. Tagba |
7. The Future of Farming: Bringing Biophotonics and Machine Learning to Revolutionize AgricultureThe future of farming is set to be revolutionized by biophotonics and machine learning. Biophotonics is the study of the interaction of light and living matter, and machine learning is a form of artificial intelligence that allows computers to learn from data. Together, these two technologies will allow for more precise and efficient farming, as well as greater yields and less wastage. Biophotonics will allow for more precise targeting of crops with pesticides and herbicides, as well as more efficient... S. Ndlovu |