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1. Excellence in Agronomy 2030: A new CGIAR-wide initiative to deliver agronomy solutions at scaleRequired increases in crop production and productivity in sub-Saharan Africa (SSA) will not happen without the increased use of appropriate agronomic practices. While several thousand new varieties of nearly all key crops have been produced in the past decade, recent increases in yields in specific countries have only happened when such varieties received the right agro-inputs and management. That said, agronomy is often highlighted as an area that has not delivered impact at scale in SSA, or... B. Vanlauwe, T. Amede, F. Baudron, P. Chivenge, M. Devare, K. Saito, J. Kihara, V. Nangia, P. Pypers, K. Shepherd, E. Vandamme |
2. SIMULATION OF CASSAVA YIELD UNDER DIFFERENT CLIMATIC SCENARIOS IN KILEMBWE, SOUTH-KIVU PROVINCE EASTERN DR CONGOClimate variability and change are projected to significantly impact agricultural production across Africa. This study assessed the effects of climate variability and change on cassava yield in Kilembwe, South-Kivu province Eastern DR Congo. The assessment relies on the DSSAT crop model simulation of cassava under current and future climate. The period 1980–2010 was used to represent the baseline, while future projection covers three periods including the near future (2010–2039), mid-century... A.B. Yamungu, A. Egeru, M.J. Majaliwa, B.M. Dossa |
3. Spectral assessment of chickpea morpho-physiological traits from space, air and groundChickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The current... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg |
4. MAPPING AND ASSESSING AFRICAN SOILS FERTILITY USING HIGH-RESOLUTION REMOTE SENSING AND MACHINE LEARNING APPROACHES: STATE-OF-THE-ART AND PERSPECTIVESAfrica is far from exploiting its true agricultural potential. United Nations Food and Agriculture Organization (FAO) indicates that the continent has 60% of non-cultivated lands worldwide. While soil fertility is well highlighted as one of the major limiting factors, only limited information is available on soil nutrient contents and nutrient availability in the African soils. Soil fertility of agricultural fields is related to many physical and chemical properties, such as texture, organic matter... M. Hmimou, A. Laamrani, F. Sehbaoui, A. Chehbouni, S. Khabba, D. Dhiba |
5. A precision irrigation app for smart water management by farmersIn a context of climate change and water scarcity which is globally recognized, Morocco is one of the countries that are facing already insufficient water supply for irrigation in order to sustain productivity and food security. Therefore, there is a strong need for adapting agricultural practices and developing new technologies for efficient and smart irrigation management to make best use of available water and maximize productivity per unit of consumed water. Recent studies have shown that... A. Abouabdillah , R. Bouabid |
6. QUANTIFICATION OF OPTIMAL FERTILIZERS DEMAND IN WHEAT AND CORN FIELDS IN MOROCCO USING VERY HIGH-RESOLUTION REMOTE SENSED IMAGERY AND HYBRID COMPUTATIONAL APPROACHESAbstract. Demand on agricultural products is increasing as population continues to grow. Data driven management of macronutrients (i.e., nitrogen (N), phosphorus (P) and potassium (K)) and crops are of critical prominence to get the most out of soil in terms of crop yield while preserving environment. This study aims to establish a quantitative framework for macronutrient (i.e., nitrogen, phosphorus, and potassium) status (i.e., excess, deficiency) for winter wheat (Triticum aestivum... K. Misbah, A. Laamrani, A. Chehbouni , D. Dhiba , J. Ezzahar, K. Khechba |
7. Performance agronomique et économique de différentes stratégies de gestion de la fertilité du sol sous culture de soja (Glycine max L. Merril) dans la zone littorale du Togo.Ce travail a pour objectif de valoriser les émondes de deux légumineuses arbustives et quelques fertilisants organiques pour améliorer la production du soja. Afin de parvenir à cet objectif, les paramètres comme la masse de mille graines, les rendements en gousses, en graines, en fanes du soja et autres ont été déterminés. L’étude a eu lieu à la Station d’Expérimentation Agronomique de Lomé (SEAL)... K.M. Amouzouvi, K.E. Ozou, L. Kolani, K.A. Amouzouvi, J.M. Sogbedji |
8. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture ApplicationsCurrently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto |
9. Monitoring irrigation water use at large scale irrigated areas using remote sensing in water scarce environmentIncreasing pressure on available water resources in semi-arid region will affect the availability of water for irrigated agriculture. In this context, adoption of innovative and cost-effective tools for water management and analysis of water use patterns in irrigated areas is required for an efficient and sustainable use of water resources. This study aims to evaluate a remote sensing-based approach which allows estimation of the temporal and spatial distribution of crop evapotranspiration... M. Kharrou, V. Simonneaux, M. Le page, S. Er-raki, G. Boulet, J. Ezzahar, S. Khabba, A. Chehbouni |
10. Mapping of micronutrients status in soils under multivarietal Citrus sinensis production for precision agricultureCitrus production in Nigeria is below the world average; and this is caused among other things by poor soil management. The situation is further acerbated by blanket fertilizer application and low application of precision in soil fertility management. A study was carried out on a 34 year old multi varietal citrus orchard under sweet orange (Citrus sinensis) to determine the current soil fertility status and variability of micronutrients. Soil samples were collected at a sampling depth... B.N. Okafor, B.N. Okafor, V. Aduaramigba, O. Denton |
11. Predicting in-Season Sorghum yield potential using Remote Sensing Approach: a case study of Kano in Sudan Savannah agro- ecological zone, NigeriaThe preliminary estimation of expected yields and the accuracy of this evaluation provide information for decision-making related to the harvest. Estimating crop yield using remote sensing techniques has proven to be successful, having the ability to provide yield estimates prior to harvest. This study was conducted to examine the applicability of Sentinel-2B for estimating sorghum yield during the 2018 rainy season in Bebeji, Dawakin-Kudu and Rano Local Government Areas Kano State, in the Sudan... A. Tukur, H.A. Ajeigbe, F.M. Akinseye, I.B. Mohammed, M.M. Badamasi |
12. The status of precision agriculture and its adoption in MoroccoPrecision agriculture (PA), as an integrated crop management system that uses various tools and technologies for assessing and monitoring soil and crop spatial variability and for implementing site-specific (variable rate) applications, is a concept that becomes nowadays in many developed countries a common practice rather than an innovation. On the contrary, in most developing countries, agriculture is still struggling with the basics of farming and is constrained by many factors, such as land... R. Bouabid |
13. Comparison of soil testing and scanning methods for spatial variability assessment of soil fertility: implications for precision agricultureUnderstanding spatial variability of soil fertility is a key to variable rate nutrient applications for precision fertilization. The objective of this study was to assess field spatial variability of soil fertility using two approaches, a gridded soil testing and a scanner-based technique. Measurements were performed on a quarter pivot silage corn field of 13 ha. For the first approach, soil samples were taken on a geopositioned grid and were analyzed for the main physicochemical and nutrient... R. Bouabid |
14. Spatial variability of soil and tree nutrient status in relation to bitter pit incidence in apple orchards in the Sais plateau, MoroccoDiscreet spatial variability of soil fertility affects crop productivity and quality. In general, nutrient deficiencies are the most incriminated. However, excess or unbalanced nutrient can also impact seriously both yield and quality, especially in fruit tree crops. Bitter-pit, a nutrient disorder related to K-Ca-Mg unbalance in apple orchards can cause major loss of apple quality in field, as well as on post-harvest following periods of cold storage. Conventional composite sampling for soil... R. Bouabid |
15. Climate Smart Agriculture: Constraints, Challenges and Opportunities to Promote the System in EthiopiaAgriculture is vital to the economy of Ethiopia and its development has significant implications for food security and poverty reduction. An increase in agricultural production over the past decades has been due to land area expansion, with a modest change in production techniques and improvement in yields. Yet, the substantial reliance of the sector on rain-fed systems has made it particularly vulnerable to variability in rainfall and temperature and climate change. Climate change may decrease... G. Agegnehu, T. Amede |
16. From Drone to Satellite – Does It Work?Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sensors.... M. Söderström, K. Persson |
17. Engaging Stakeholders in Precision Agriculture Toolbox Conception: Case of Cowpea Atlas Platform Establishment in Benin RepublicCowpea [(Vigna Unguiculata (L.) Walpers] is among the most preferred and consumed legumes in West Africa and grown by many smallholder farmers. The crop has huge potential, is easy to grow and constitute a source of income of many actors involved in different value chains. Unfortunately, despite many interventions which aimed at promoting the crop in West Africa mainly Benin, areas under cowpea crop decrease over the years along with the loss of cowpea-based products. Such problem is... N.V. Fassinou hotegni, Y.L. Godonou, L.M. Gnanglè, O.N. Coulibaly, E.G. Achigan-dako |
18. Modelling Fertigation and Micro-Climate Parameters for Greenhouse Tomato (Solanum Lycopersicum L.)Amidst the hiking price of fertilizer and projected water scarcity across the world, it is imperative to explore the interaction between fertilizer, irrigation and genotype notwithstanding the micro-climate parameters so as to maximize yield while protecting the environment. The Decision Support System for Agrotechnology Transfer (DSSAT) is a model which employs all these input factors to help predict yield and thereby make an informed decision. The study sort to calibrate and validate the... Y.K. Agbemabiese, P. Abubakari, P.K. Dzomeku, I. Shaibu |
19. Evolving Potentials for Precision Climate-smart Agriculture in Sub-saharan African CountriesProgressively, there is increasing awareness on the significance of agriculture in both adaptation and mitigation to climate change. While adaptation has been typically highlighted in the most vulnerable countries, especially in Africa where the failure to adapt have been noted to exacerbate the dangers of food insecurity, there is limited effort at emphasizing mitigation as the ultimate resolution of the debacle. Climate-smart agriculture (CSA) is critical to achieving development irrespective... M.G. Ogunnaike, O.D. Onafeso |
20. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear RegressionTraditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud |
21. Use of Earth Observation Imagery, Advanced Modelling Algorithms and Other Monitoring Systems to Produce Operational Agricultural Annual Crop Inventories for Morocco.African farmers are facing the challenges of a changing climate, increased temperatures, changes in rainfall patterns, more frequent extreme weather events and reductions in water availability. The digital transformation of the agricultural sector is one of the opportunities that can promote good practices of the African agricultural through the sharing of information and tools for decision-making, thereby, boost economic growth of our African country. The shift to digital technologies is... M. Choukri, A. Laamrani , V. simonneaux , B. Gerard , S. Belaqziz, A. Chehbouni, K. Misbah, H. Mcnairn |
22. Together, Let's Make Africa the Epicenter of a Sustainable Transformation of Food Systems... P. Bwire |
23. Agricultural Data Market to Empower African FarmersBy transforming the agricultural data into agronomic advices by using AI model, farmer can get a strong tool to help them making the right decision in the right time. Decision about the quantity and the quality of fertilizer to apply, the quantity and the timing of the irrigation,… Also he can get valuable information about yield prediction, phytosanitary risk. All of this information can help famers reducing its operational cost by up to 30%. To develop robust AI model,... F. Sehbaoui |
24. Implementing Field-Based High Throughput Plant Phenotyping: The Open Source Way... Y. Kassim |
25. The Use of Unmanned Aerial Vehicle (UAV) Remotely Sensed Data and Biophysical Variables to Predict Maize Above-Ground Biomass (AGB) in Small-Scale Farming SystemsConsidering the current and projected increase in human population, approaches to optimize crop productivity to meet the rising demand are paramount. Timely and accurate maize Above Ground Biomass (AGB) measurements allow for development of models that can precisely predict yield prior to harvesting, useful for food production management and sustenance. The development of Unmanned Aerial Vehicles (UAVs) as a new generation of robust remote sensing platforms, mounted with high-resolution sensors... C. Dlamini, J. Odindi, O. Mutanga, T. Matongera |
26. Enhancing the Estimation of Equivalent Water Thickness in Neglected and Underutilized Taro Crops Using UAV Acquired Multispectral Thermal Image Data and Index-Based Image SegmentationDue to the impact of climate variability and change, smallholder farmers are increasingly faced with the challenge of sustaining crop production. Taro, recognized as a future smart neglected and underutilized crop due to its resilience to abiotic stresses, has emerged as valuable for diversifying crop farming systems and sustaining local livelihoods. Nonetheless, a significant research gap exists in spatially explicit information on the water status of taro, contributing to the paradox of its... S. Ndlovu, J. Odindi, M. Sibanda, O. Mutanga |