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| Filter results6 paper(s) found. |
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1. Spatial Interpolation for Mapping Hydraulic Soil Properties in GIS EnvironmentSoil water information is an essential input for environmental, hydrological or land surface models. There is a need for reliable soil water information with current coverage in the area. A number of 60 soil profiles data were evaluated for the performance of estimates inverse distance weighting to map some of the soil quality properties. soil profiles were used for the application of geostatistics. Maps with the investigated coverage were produced with the soil information available about soil... M.A. Abdelrahman, A.M. Saleh, M.M. El sharkawy, E. Farg, S.M. Arafat |
2. Soil fertility mapping of Dry savannah zone of TogoIncreasing agricultural productivity and therefore the production requires a good knowledge of the soil fertility status and a sustainable nutrients management. The objective of this study is to map spatial distribution of some selected soil fertility parameters in the dry savannah agro-ecological zone that covers the regions of Savanes and Kara in Togo. Soil fertility parameters such as pH, available phosphorus (P), exchangeable potassium (K) and organic matter were determined in soil samples... K.K. Ganyo, K.A. Ablede , K. Koudjega, S. Ani, K. Afawoubo, D.A. Anoumou, A.T. Mensah, E. Assih-faram, M. Tchalla-kpondji, K. Kpemoua, Y. Lombo |
3. 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 |
4. 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 |
5. Precision Maize Nutrition: Evidences from On-farm Experimentation of Quefts Estimated Nutrient Requirement for Variable Densities in Smallholder Farmers in EthiopiaQuantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model is an important tool for estimating optimal nutrient requirement of crops. The study was conducted to evaluate QUEFTS estimated (QE) nutrient requirement of maize in two pant densities (32,443 and 53,333 plants/ha in Central Rift Valley (CRV); 27724 and 62,000 plants/ha in Jimma) on fields of three farmers wealth classes (poor, medium and wealth) in contrasting agro-ecologies of Ethiopia. QUEFTS follows a target oriented... W.B. Kenea, T.B. Tura, A.N. Woldekristos |
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 at... 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 |