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| Filter results7 paper(s) found. |
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1. Self-developed Small Robot for Tomato Plants DetectionA mobile (robot) measuring station for tomato plant detection has been developed, equipped with different sensors and a self-developed hardware and software background. The development aims are the applications in precision crop production: artificial intelligence- based detection, imaging, data collection, automation, and remote sensing. The robot is fault- free in field conditions and is therefore a key development tool for precision farming and digital agriculture. The measurement system d... B. Ambrus, G. Teschner, M. Neményi, A. Nyéki |
2. Potentials of Unmanned Aerial Vehicles (UAVs) for the Nigerian AgricultureThe continuous development of technology is driving the invention of new machineries such as the Unmanned Aerial Vehicles (UAVs), also known as “drones”. The UAVs have become much more popular within the last decade for its significant roles in agriculture among other industries, yet their applications in Nigeria are yet to be appreciated. Therefore, the present study reviewed the characteristics and multiple uses of UAVs in agriculture and their potentials for the Niger... M. Kabir, S. Ekici |
3. Detecting the Impact of Hail Damage on Maize Crops in Smallholder Farms Using Unmanned Aerial Vehicles Derived Multispectral DataNatural disasters such as hailstorms are now frequent and negatively impact smallholder farmers' livelihoods. In these events, there is a need for robust and innovative techniques for monitoring the extent of their damage in smallholder croplands to optimise production. In this regard, this study sought to evaluate the utility of drone-derived multispectral data in estimating crop health elements (i.e., equivalent water thickness (EWT), chlorophyll content, and leaf area index (LAI) of ma... M. Sibanda |
4. 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 ... S. Ndlovu |
5. Predicting the Distribution of Groundnut Phytopathogens Under Current and Future Climatic Scenarios in ZimbabweGroundnut (Arachis hypogaea L.) is an important oil crop with immense nutritional and economic benefits, but its productivity in sub-Saharan Africa (SSA) is threatened by a plethora of phytopathogens such as groundnut rosette virus, Alternaria leafspots, early leafspots and peanut rust. In Zimbabwe, ecological niches and epidemiology of these pathogenic microbial strains, particularly under the current and predicted climate change scenarios, are still poorly understood. Yet, this inf... H. Chinwa, C.N. Kamutando |
6. Capacity Building of African Young Scientists in Precision Agriculture Through Cross Regional Academic MobilityClimate change is one of the main problems affecting food and nutrition globally, particularly in sub-Saharan Africa. Adapting to and/or mitigating climate change in the agri-food sector requires merging information technologies, genetic innovations, and sustainable farming practices to empower the agricultural youth sector to create effective and locally adapted solutions. Precision Agriculture applied to crops (PAAC), has been advocated as a strategic solution to mitigate/adapt agriculture ... K. Frimpong, V. Fassinou hotegni, A. Karangwa, A. Manyatsi, M. Amri, D. Cammarano, C. Lesueur, J. Taylor, S. Phillips, E.G. Achigan-dako, G. Houessou, O. Linkpon, D. Tchokponhoué, C. Houdegbe, C. Adje |
7. Inter-Country Cooperation Can Transform Precision Agriculture Education and Research in AfricaThere is a significant potential to transform the productivity and profitability of African agricultural systems through integration of precision agriculture technologies and practices. Implementing smart agriculture solutions in Africa, both in terms of policies and program design, implementation and monitoring and evaluation requires cooperation among the African nations. Inter-country cooperation will enable leveraging the available good and diverse capacities for develop... K. Frimpong, V. Aduramigba-modupe, V. Fassinou hotegni, M. Mechri |
