Artificial Intelligence for Agroforestry: A Review
Sameer Daniel
*
Department of Silviculture and Agroforestry, College of Forestry, SHUATS, Prayagraj-211 007 (U.P.), India.
*Author to whom correspondence should be addressed.
Abstract
This review explores about use of artificial intelligence techniques for agroforestry. Agroforestry is an intensive and interactive land usage strategy that maximises biotic and abiotic resources by deliberately combining trees and/or shrubs with crops and/or animals in temporal and spatial patterns on the same plot of land. Agroforestry is a self-sustaining, green and smart technology that will transform the future of Indian agriculture. AI-powered agroforestry plays a critical role in data collecting, processing, assessment, interpretation, knowledge acquisition, and solution provision to improve overall production and efficiency. It is very essential to understand the complexity of Agroforestry system, cropping patterns, succession, stratification, productivity and biodiversity on the land. However, a larger workforce is required to increase the farm productivity which also enables with employment opportunity and smart work in a reconnection with nature. Thus, AI-enabled solutions are extremely valuable in crop cultivation, risk management, crop management, crop protection, crop advice, soil and crop health monitoring and management, crop feeding, automated irrigation, autonomous crop harvesting, crop grading, and even marketing. It will transform contemporary agroforestry methods by enhancing efficiency through accurate real-time monitoring and projections of increased food yields. Thus, the combination of AI, robotics, machine learning, and ancestral knowledge is the path to a transformational technological period that will renew agriculture and agroforestry throughout the world by encompassing varied crops and livestock species. This is also known as Smart Farming, Green Farming, Modern Farming, or Technical Farming. AI systems should be developed and deployed with consideration for local communities, indigenous knowledge, and historically marginalized groups. Finally, we believe that a sound theoretical framework is a useful basis for guiding the development of specific technical applications of artificial intelligence.
Keywords: Agroforestry, artificial intelligence, robots, transforming, smart farming, green farming