Research Area: Artificial Intelligence
The current world population is 7.8 billion and is projected to reach 9.8 billion by 2050. The limited land area and strong need to produce more crop to feed the ever-increasing population is a major challenge today, especially for developing countries. The strong need to produce more crop from lesser land has led to several challenges in the field of agriculture. Reduction in agriculture yield due to climate change and global warming due to farming has become a vicious circle. Excessive use of chemicals in farms to increase soil fertility and reduce weeds and pests have adversely affected the environment and the human health. There is limited availability of natural resources like phosphorous and energy required in agriculture. Water scarcity and increase in plant diseases are other major concerns. Artificial intelligence (AI) has emerged as a promising technology in digital agriculture. Digital agriculture relates to using digital technologies for collecting, storing, and further analyzing the electronic agricultural data for better reasoning and decision-making using AI techniques. Precision agriculture is one such technique that monitors soil moisture and composition, temperature, and humidity and determines optimized fertilizer and water requirements for a specific crop and different areas of a farm.
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Author(s) Name: Parvinder Singh, Amandeep Kaur
Journal name: Deep Learning for Sustainable Agriculture
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Publisher name: ELSEVIER
DOI: https://doi.org/10.1016/B978-0-323-85214-2.00011-2
Volume Information: 2022, Pages 57-80
