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AfPCA Proceedings 2024

Proceedings

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Magalhães, D.V
Nasrallah, A
KPEMOUA, K
Emam, M
AYERDI-GOTOR, A
ITO, T
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Authors
Belal, A
Elsayed , M
Jalhoum, M.E
Abdelatif , M
Hendawy , E
Emam, M
Zahran , M
Ganyo, K.K
ABLEDE , K.A
KOUDJEGA, K
ANI, S
AFAWOUBO, K
ANOUMOU, D.A
MENSAH, A.T
ASSIH-FARAM, E
TCHALLA-KPONDJI, M
KPEMOUA, K
LOMBO, Y
MORIMOTO, E
ARAI, Y
NONAMI, K
ITO, T
Aboelkhier, H
Nasrallah, A
Shaddad, S
Buttafuoco, G
Higuti, V.A
Velasquez, A.E
Gasparino, M.V
Magalhães, D.V
Becker, M
Milori, D.M
Aroca, R.V
LEBRINI, Y
AYERDI-GOTOR, A
Topics
Adoption of Precision Agriculture
Precision Nutrient Management
Robotics, Automation, and Small Farm Mechanization
Proximal and Remote Sensing
Type
Oral
Poster
Year
2020
2022
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Authors

Filter results6 paper(s) found.

1. Precision Farming Technology to Increase Soil and Crop Productivity in Egypt Using Remote Sensing and GIS

Precision farming or site-specific land management is a new approach for development the agriculture processes to increase the soil and crop productivity with saving efforts and costs. Precision farming includes many techniques such as Global Position Systems (GPS), Geographic Information Systems (GIS), Remote Sensing (RS), Yield Monitors, Internet of Things (IOT), Variable Rate Application (VRA), Yield Mapping, Site-Specific Management Zones (SSMZ) and Crop Modeling. SSMZ delineation can be improved... A. Belal, M. Elsayed , M.E. Jalhoum, M. abdelatif , E. Hendawy , M. Emam, M. Zahran

2. Soil fertility mapping of Dry savannah zone of Togo

Increasing 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. Development of Lodging Direction Determination System Using Image Processing

In this study, image processing system was developed for application on rice plants to determine lodging condition, which was contributing factor to declining harvester efficiency by using combine harvester. Therefore, We developed a system for determination of the lodging direction by algorithm based on convolutional neural network (CNN). As for deep learning framework, Pytorch1.1.0 were used to train and test the judging direction. GoogLeNet was used as a pre-trained CNN model. Lodging... E. Morimoto, Y. Arai, K. Nonami, T. Ito

4. A geostatistical approach to define a soil fertility index based on the main soil macronutrients

Soil fertility is greatly affected by main soil macronutrients such as nitrogen (N), phosphorus (P), and potassium (K). These macronutrients can be used to define a synthetic fertility index to support soil fertilization. The study was aimed to propose a geostatistical approach to define a synthetic fertility index based on factorial cokriging. It consists in quantifying and reducing the spatial variability of multivariate data to only a few factors, related to different spatial scales. Such factors... H. Aboelkhier, A. Nasrallah, S. Shaddad, G. Buttafuoco

5. LiDAR-based soybean crop segmentation for autonomous navigation

The technological advances in the last few decades have greatly changed agricultural operations. In order to became safer, more profitable, efficient, and sustainable, modern farms have adopted the use of sophisticated technologies, such as robots, sensors, aerial images, and GNSS (Global Navigation Satellite System). These technologies not only increase the crop productivity, but also reduce the wide use of water, fertilisers, and pesticides. Due to this, they reduce costs and negative environmental... V.A. Higuti, A.E. Velasquez, M.V. Gasparino, D.V. Magalhães, M. Becker, D.M. Milori, R.V. Aroca

6. Performance of Remote Sensing Data and Machine Learning for Wheat Disease Detection

The 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 reason... Y. Lebrini, A. Ayerdi-gotor