Precision irrigation management using automatic scheduling techniques under environmental drought stress conditions in Egypt: a review

Document Type : Review Articles

Authors

1 Water Relations and Field Irrigation Department, Agricultural and Biological Research Institute, National Research Centre

2 Water Relations and Field Irrigation Department, Agricultural and Biological Institute, National Research Centre

3 Water Relations and Field Irrigation Department, Agricultural and Biological Institute, National Research Centre; 33 EL Bohouth St., Dokki, Giza, Egypt.

Abstract

Water resources are, therefore, a limiting factor for the country’s agricultural production, and saving water becomes clearly a necessary prerequisite. In this logic, irrigation technologies appear to play a major role in supporting Egypt's agro-economy. However, using such modern means of irrigation control can help in scheduling both irrigation and fertigation processes very accurately, providing different cultivated crops with their exact requirements of water and fertilizers at the correct time for the plant. Moreover, it will consume the minimum water, fertilizers energy, and labor as well. Also, it will render the plant avoid any stress of water deficiency. This review article aims to present some automated scheduling techniques for accurate irrigation management in Egypt, as one of the solutions to overcome the impact of climate change. This can be done through several methods such as irrigation scheduling using the data required for irrigation scheduling or by using irrigation scheduling programs and models. As well as the use of automatic irrigation, whether by means of ground humidity or controlling the time and amount of water. Precision agriculture using the Internet of Things (IoT), is a broad class of related technologies that will maintain precise control over farm decisions. This method of planting decisions is intended for specific crops and not for an entire region. Precision farming combines agricultural machinery and efficient agricultural operations to meet the specific needs of farmers. For example, making the best decision to manage irrigation systems by automatically scheduling irrigation, and knowing the plants' need for water in actual amounts and in real-time.

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