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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. Modeling of the Optimal Parameters, Improvement and Performance Evaluation of Marc Engine Driven Common Bean (Phaseolus Vulgaris L.) Thresher in EthiopiaThis executive summary provides an overview of the research study conducted on modeling the optimal parameters, improvement, and performance evaluation of the engine-driven bean thresher developed by the Melkassa Agricultural Research Center (MARC) in Ethiopia. The study aimed to enhance the efficiency and productivity of the bean thresher, contribute to sustainable agricultural practices, promote technology adoption, and support the economic development of the agricultural sector. The re... B. Zewdie gebrekidan |
6. Assessing of Soil Nutrients Using Laboratory and Remote Sensing Methods in Northern Guinea SavannahIntroduction Soil nutrients are essential for plant growth and development, making their assessment crucial for sustainable agriculture and environmental management. The northern Guinea savannah region, known for its agricultural potential, requires periodic monitoring of soil nutrient status to ensure optimal crop yields and maintain soil fertility. This study aims to evaluate the effectiveness of laboratory and remote sensing techniques in assessing soil nutrients in this region.... A. Rabiu garba |
7. Toward Precision Agriculture by Assessing FAO Soil Data Accuracy with Localised Soil Mapping in Mid-Western UgandaProper soil mapping remains a major input for efforts that aim at developing context specific soil and crop management. Soil maps often enable policy makers and other agricultural extension programs to establish the suitability of land for various production systems. Currently, most soil maps have been developed basing in the FAO soil data bases at a scale of 1:50,000 yet farmers and other local land users require fine scales to guide decision in the use of fertilizers and selection of ... P. Musinguzi, E. Ojambo |