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AfPCA Proceedings 2024

Proceedings

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Aboneh, T
Aidoudi, Z
AYERDI-GOTOR, A
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Authors
Rudiger, U
Aidoudi, Z
Frija, A
Rekik, M
Zaiem, A
Cheikh, H
LEBRINI, Y
AYERDI-GOTOR, A
Aboneh, T
Rorissa, P
Topics
Robotics, Automation, and Small Farm Mechanization
Proximal and Remote Sensing
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2020
2022
2024
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Authors

Filter results3 paper(s) found.

1. Small Machinery for Sustainable Intensification of Crop-Livestock System under Biomass Shortage

Small crop-livestock systems in Low- and Middle-Income Countries (LMIC) such as North African ones are characterized by low mechanization levels, thus undermining their productivity and sustainability. Machinery being promoted in local markets are made and imported mostly from industrial countries where farm systems are larger in terms of size. Prices of these machines are not affordable for small to medium sized land-holding farmers who remain incapable of upgrading and modernizing their farming... U. Rudiger, Z. Aidoudi, A. Frija, M. Rekik, A. Zaiem, H. Cheikh

2. 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

3. An Ensemble-Based Deep Learning Approach for Early and Accurate Wheat Disease Detection

Crop diseases are the primarily cause for yield loss and a factor for food security issue around the globe. Crop diseases caused by pathogens pose a significant threat to global food security, the challenge become worst particularly in developing countries like Ethiopia. Rapid population growth and accurate disease identification is crucial for timely intervention and minimizing crop losses. However, traditional methods often rely on expert analysis, which can be time-consuming and resource-intensive.... T. Aboneh, P. Rorissa