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1. An Open Source Multispectral Camera for Crop MonitoringPrecision agriculture is one of the most important economic issues of the 21st century because it will make it possible to respond to the new challenges of agriculture, which are population growth, global warming, global epidemics, and inflation, to name a few. Remote sensing makes it possible to monitor the plantation from a distance and makes it possible to know the level of growth and the state of health and hydration of the plants. This paper outlines an affordable and open-source multisp... H. Nardjes, M. Yagoubi |
2. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat LeavesThe assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium conte... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris |
3. 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 sens... M. Söderström, K. Persson |
4. Leveraging Precision Agriculture Education for Resilient and Sustainable Agriculture in Sub-saharan AfricaImproved agricultural productivity and access to safe and nutritious food is critical to meeting south Saharan Africa (SSA)’s growing food demand and for improving incomes for smallholders in the region. This has to be done in ways that do not compromise natural capital but secure ecosystem functions and services. With almost 60 percent of the region’s population under the age of 25, Precision Agriculture (PA) education for SSA youth is crucial. PA offers the potential to transfor... K.A. Frimpong |
5. Performance of Remote Sensing Data and Machine Learning for Wheat Disease DetectionThe use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main re... Y. Lebrini, A. Ayerdi-gotor |
6. Unmanned Aerial Vehicles (UAVs) for Phenotypic Traits Estimation & Yellow Rust Disease Severity Assessment in Small-scale Wheat Breeding Trials in EthiopiaRemote Sensing (RS) platforms; like the Unmanned Aerial Vehicles (UAVs) are recently gaining traction in agricultural data collection systems and used for various phenotyping of breeding field trials and capturing different biophysical, biochemical and sanitary traits which can be used to predict and explain the resulting yield and selecting better verities. Compared to the conventional phenotyping usually done by visual scoring and manual measurements which is time consuming/back breakings, ... T. Anberbir, G. Mamo , A. Dabi |
7. Photogrammetrically Assessed Smallholder Pineapple Fields in Ghana Using Small Unmanned Aircraft SystemsUltra-high-resolution imagery taken by small unmanned aircraft systems (sUAS, drones) has been proven beneficial for the monitoring of agricultural crops in conventional farming especially in the context of precision farming. For smallholder pineapple cultivation, the use of sUAS imagery is still sparsely evaluated. However, technical developments in low cost sUAS-sensor combinations make assessments of agricultural areas by service providers more and more affordable for Africa. In this study... M. Hobart, E. Anin-adjei, E. Hanyabui, G. Badu-marfo, M. Schirrmann, N. Schiller |
8. Recommandation De Formules De Fertilisation Site-spécifique Pour La Production Du Maïs Dans La Région Des Savanes Du TogoDans le contexte actuel de la dégradation des terres agricoles et des difficultés de disponibilité et d'accès aux intrants agricoles en particulier les engrais, la maximisation de l'efficience d'utilisation des nutriments en nutrition des plantes devient plus que jamais une nécessité. Nous avons conduit en 2020 sous culture de maïs (Zea mays L.), des essais soustractifs à base de l'azote (N), du phosphore (P) et du potassiu... M. Lare, J. Sogbedji, K. Lotsi, K. Amouzou, A. Ale gonh-goh, A. Agneroh |
9. 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 ... J. Sogbedji, L. William, M. Lare, A. Sekaya, K. Sika , E. Tagba |
10. Application of Remote Sensing Technologies for Monitoring within Field Soil and Crop Growth Variability... N. Majozi |
11. A Comparative Estimation of Maize Leaf Moisture Content on Smallholder Farming Systems Using Unmanned Aerial Vehicle (UAV) Based Proximal Remote SensingUnderstanding maize moisture conditions is necessary for crop monitoring and developing early warning systems to optimise agricultural production in smallholder farms. Therefore, this study evaluated the utility of UAV derived multispectral imagery and machine learning techniques in estimating maize leaf moisture indicators; equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables ... S. Ndlovu |
12. Comparative Assessment of Landuse Landcover Changes on Water Quality of River Kaduna from 2012-2020 at Wuya, Niger State, NigeriaThe study investigates the effects of land use land cover changes on water quality of River Kaduna from 2012-2020 at Wuya, Niger state, Nigeria using Landsat 7 imagery. Five classes of LULC types where selected and used as basis for classification. Also five (5) sampling stations selected on the water body for water quality analysis which were collected once monthly for a period of six months from February 2020 to July 2020. The results of LULC classification depicts an increase in water body... I. Saratu usman, F. Yusufu |
13. Factors Influencing Farmers’ Decisions on Timing and Application Rates of Irrigation Water in Semi-Arid Regions: A Case-Study of Mwala, Machakos County, KenyaThis study investigates the factors influencing farmers’ decisions on water application in arid and semi-arid regions, where water shortages are prevalent due to low and unreliable rainfall. The research involved interviewing 41 farmers registered under the Equity Group Foundation extension scheme, focusing on their irrigation scheduling techniques, timing, application rates, and other factors such as plant and soil conditions. The study also involved laboratory analysis of soil samples... D. Mongína, C.K. Gachene, G. Kironchi |
14. Evaluating the Impact of Seasonal Weather Variability on Soil Moisture Conservation Under Mulching Systems for Date Palm Production in OasesSoil moisture is an essential parameter that governs crop production and soil health. Therefore, the critical role of soil moisture cannot be overstated in sustaining agriculture, especially in arid and semi-arid regions. Date palm production not only plays a vital role in economic and nutritional purposes in many arid areas but also plays important roles in creating favorable microclimates for agriculture and protecting lands from desertification. This study proposes an innovative appr... U. Safi, O. Abdallah , A. Sabri |
15. An Ensemble-Based Deep Learning Approach for Early and Accurate Wheat Disease DetectionCrop diseases are the primarily cause for yield loss and a factor for food security issue around the globe. Crop diseases caused by pathogens pose a significant threat to global food security, the challenge become worst particularly in developing countries like Ethiopia. Rapid population growth and accurate disease identification is crucial for timely intervention and minimizing crop losses. However, traditional methods often rely on expert analysis, which can be time-consuming and resource-i... T. Aboneh, P. Rorissa |
16. Rainwater Harvesting and Nutrient Intensification in Maize-Legume Farming Systems in Semi-Arid ZimbabweAgricultural productivity in Zimbabwe is declining mainly due to climate change and inherently poor soil fertility. The situation is worsened by the high cost of fertilizers beyond the reach of many smallholder farmers. In response to these challenges, most smallholder farmers are implementing either rainwater harvesting (RWH) or integrated soil fertility management (ISFM). This study sought to investigate the role of integrating the tied-contour RWH (TC-RWH) technique and ISFM on soil moistu... E. Mutsamba-magwaza, D. Nyamayevu, G. Nyamadzawo, R. Mandumbu, I. Nyagumbo |
17. Multivariate Regional Deep Learning Prediction of Soil Properties from Near-Infrared, Mid-Infrared and Their Combined SpectraArtificial neural network (ANN) models have been successfully used in infrared spectroscopy research for the prediction of soil properties. They often show better performance than conventional methods such as partial least squares regression (PLSR). In this study we develop and evaluate a multivariate extension of ANN for predicting correlated soil properties: total carbon (C), total nitrogen (N), clay, silt, and sand contents, using visible near-infrared (vis-NIR), mid-infrared (MIR) or comb... R. Nyawasha |
18. Upland Rice Yield Response to Soil Moisture Variability with Depth Across Ferralsols and Gleysols in Western UgandaSoil moisture is a vital factor in boosting rice productivity by influencing the growth of healthy plants. In mid-western districts like Kikuube where rainfall is unpredictable, maintaining optimal soil moisture differs between a bountiful harvest and crop failure. Effective soil moisture management leads to improved water use efficiency, allowing crops to withstand periods of drought. This study assessed upland yield response to soil moisture variations with soil depth in Ferralsols and Gley... T. Matila, P. Tamale |
19. Real-Time Moisture Control in Irrigation Systems for Water Use Efficiency and Climate Change Resilience. A ReviewDue to the increasing water scarcity and uncertainties of climate change, improving crop water use efficiency and productivity, at the same time minimizing detrimental effects on the environment to meet the world's rising food demand. Thus, is necessary to adopt innovative irrigation strategies, such as drip irrigation. Smart irrigation has a potential of improving water use efficiency in precision agriculture. Conventionally, irrigation systems rely on heuristic methods in order to sched... D. Kindikiza |
20. Design and Development of a LoRa Communication System for Scalable Smart Irrigation SystemsSmart irrigation is a promising tool to optimize irrigation water use but is still faced with challenges related to usability and applicability attributed to several constraints such as high initial costs, complex user interface, poor connectivity, limited farm coverage, etc. This study aimed to solve some of these issues through the development and testing of a LoRa communication system using a Raspberry Pi 4, LoRa HAT concentrator, and Strega smart valve at the Makerere University Agricultu... J. Wanyama , J. Ikabat, I. Kabenge, P. Hess, P. Nakawuka, E. Bwambale , J. Muyonga, S. Felicioni, A. Bühlmann, T. Anken |
21. Investigating the Interaction Between Soil Moisture and Clay Content for Enhanced Soil Moisture Prediction: A Lab-Based Approach with Implications for African Agriculture... Y. Atyosi |