Digital Agriculture

The world population is increasing while arable land is decreasing at an alarming rate. About one-quarter of arable land is degraded and needs significant restoration before it can sustain crops again. By 2030, the water supply will fall 40% short of meeting global demand. Moreover, looming climate change poses additional challenge to increasing food production to feed 10 billion people by 2050. Current major agricultural systems are on a largely unsustainable trajectory because of their contributions to greenhouse gas emissions, water pollution, and biodiversity loss.
For these reasons, innovative technologies are being introduced in modern agriculture to sustain food production.  They include digital and geospatial technologies to manage soil, climate and plant genetic resources. With the development of tools and sensors integrated into the internet of things (IoT) environment, physically collected information is converted into computer-readable language. Digital innovations thus allow real-time analysis, machine learning, and artificial intelligence (AI) that manage massive amount of data, also known as big data. Accordingly, digital agriculture affords greater potential for sustainable farming and economic benefits.

This book summarizes the latest advances in AI-integration of agriculture practices. Specific focus includes but not limited to, big data, yield mapping, pests management, and optimal fertigation. As such, it presents a forward-looking approach to meet multiple UN Sustainable Development Goals, specifically, SDG 2, 6, 13 and 15.