Water Optimization in Digital Farming

Pascal Faye, Jeanne Faye, Mariane Senghor

2024

Abstract

In Senegal, agriculture is subsistence and highly dependent on soil, climate, and raining season. Food crops take up to 46% of the total land and make up 15% of the Gross Domestic Product (GDP), ensuring between 70% and 75% employment. In this work, we propose methods to understand through a sensor network, the effects of the required irrigation system on six soil types (ferruginous tropical - sandy - loamy - clay - humus-bearing - clay and loamy) depending to crop production like : - the time interval for infiltration or evaporation of the irrigation water according to the type of soil - the speed of spreading of water in both directions (lateral and depth) - the set up of four soil’s amendments (peanut shells, livestock manure, poultry manure and plant mixture) methods for optimized water in crop production. We, also, propose an agricultural calendar for a good distribution of the farms’ activities over time after finding the relationship between eighteen crop production and soil amendments. Our results show the effectiveness of our solution to help water optimization in agriculture. This means that, taking into account these data, it is possible to understand crop dependencies, anticipate agro-ecological phenomena and crop water stress that affect the yield of crops.

Paper Citation

in Harvard Style

Faye P., Faye J. and Senghor M. (2024). Water Optimization in Digital Farming. In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 472-479. DOI: 10.5220/0013057400003822

in Bibtex Style

@conference{icinco24,
author={Pascal Faye and Jeanne Faye and Mariane Senghor},
title={Water Optimization in Digital Farming},
booktitle={Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2024},
pages={472-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013057400003822},
isbn={978-989-758-717-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Water Optimization in Digital Farming
SN - 978-989-758-717-7
AU - Faye P.
AU - Faye J.
AU - Senghor M.
PY - 2024
SP - 472
EP - 479
DO - 10.5220/0013057400003822
PB - SciTePress