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AfPCA Proceedings 2024

Proceedings

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Soumaya, A
Awosiyan, O.E
Amin, M.E
Arafat, S.M
Abinadaw, T
Gobezie, T.B
Adolwa, I
Asante, B
Amujoyegbe, B
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Authors
AbdelRahman, M.A
Saleh, A.M
El Sharkawy, M.M
Farg, E
Arafat, S.M
Gobezie, T.B
Biswas, A
Teye, E
Abinadaw, T
Atiah, K
Amuah, C
Awosiyan, O.E
Mary, I.K
Adesina, F.A
Amao, P.A
Amujoyegbe, B
Oyedele, D
Amin, M.E
Abdelfattah, M.A
Mohamed, E.S
Belal, A.A
Nabil, M
Mahmoud, A.G
Adolwa, I
Asante, B
Boughattas, N
Marwa, K
Mohamed, Z
Sawsen, A
Soumaya, A
Hafedh, H
Imen, H
Youssef, T
Topics
Mapping and Geostatistics
Policy Support Innovations
Adoption of Precision Agriculture
Precision Agriculture for Field and Plantation Crops
Precision Planting/Harvesting
Plenary Session
Precision Water Management
Precision Nutrient Management
Type
Oral
Poster
Year
2020
2022
2024
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Authors

Filter results9 paper(s) found.

1. Spatial Interpolation for Mapping Hydraulic Soil Properties in GIS Environment

Soil 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. Just a moment; the need for streamlining precision agriculture data in Africa

Precision agriculture (PA) data sources in the era of digital agriculture are diverse in terms of the range of technology options and the types of data they generate. These include proximal sensors, unmanned aerial vehicle (UAV), satellites, farm machinery mounted sensors and robotics to generate static data or real time information (e.g., yield monitoring). Government institutions, scientists and private sectors take the lion’s share in generating PA data at innovation, validation and dissemination... T.B. Gobezie, A. Biswas

3. Feasibility studies on developing farmer friendly rapid in-situ evaluation technique for soil quality in cocoa planation based on pocket-sized near-infrared spectroscopy and chemometrics

Rapid and in-situ determination of soil quality holds a brighter potential for improving food security, food quality and minimizing waste of excessive application of soil amendments with its effect of pollution. In this study a pocket-sized NIR spectroscopy (740 -1070 nm) and chemometrics coupled with mobile phone was used to predict nitrogen (N), phosphorus (P), potassium (K), pH and calcium (Ca2+) in cocoa plantation soils in Ghana. Different partial least square algorithms (Full...

4. DIGITAL MAPPING OF EXCHANGEABLE CATIONS IN SOILS OF SOUTHWESTERN NIGERIA

Soil acidity and low exchangeable cation are the major soil fertility challenges resulting in low crop productivity in Southwest Nigeria. Digital soil mapping is an effective way to achieve precision agriculture. However, most of the research work on soil exchangeable cations as soil information was not geo-referenced, The study created geo-database and developed a digitized map of soil exchangeable cations Indicating the spatial distribution in soils of southwestern Nigeria. Secondary data... O.E. Awosiyan, I.K. Mary, F.A. Adesina

5. Fertilizer Micro-dosing on Growth and Vegetative Yield of Fluted Pumpkin (Telfairia occidentalis Hook. f)

The study evaluated growth and vegetative response of fluted pumpkin (Telfairia occidentalis Hook. f) to levels and time of micro-dosing Urea fertilizer. The experiment was conducted in two growing seasons of late and early cropping seasons of 2017 and 2018 respectively at the Teaching and Research Farm of Obafemi Awolowo University. The experiment was a factorial laid out in a Randomized Complete Block Design (RCBD) with four replications involving seasons, levels of fertilizer (0, 20,... P.A. Amao, B. Amujoyegbe, D. Oyedele

6. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear Regression

Traditional 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

7. Post-Harvest Assessments of On-Farm Maize Experimentation

The completion of the most recent maize-growing seasons in northern Cote d’Ivoire and Kenya (western and eastern regions) provided a first opportunity for farmers to share assessments from their participation in a new on-farm research initiative for sub-Saharan Africa called NUTCAT - meaning Nutrient-Catalyzed Agricultural Transformation. ... I. Adolwa

8. Spatial-Temporal Assessment of Drought in the Northern Region, Ghana

... B. Asante

9. Optimizing Durum Wheat Nitrogen Nutrition Index (NNI) Prediction Through Sentinel-2 Vegetation Index Integration

Nitrogen is crucial for durum wheat growth and productivity, but excess or insufficient levels can harm both the environment and farmers' finances. Remote sensing offers rapid, cost-effective, and nondestructive ways to assess crop nutrition, with vegetation indices (VIs) indicating plant health. This study aims to enhance the accuracy of durum wheat nitrogen status prediction by investigating modified formulations of Nitrogen Nutrition Index (NNI) coupled with various vegetation indices (VIs),... N. Boughattas, K. Marwa, Z. Mohamed, A. Sawsen, A. Soumaya, H. Hafedh, H. Imen, T. Youssef