Predictive Analytics in Smart Agriculture 1st Edition

Capture the future of farming with Predictive Analytics in Smart Agriculture (1st Edition) — a practical, forward-looking guide that turns data into decisions. Whether you manage a family farm in the Midwest, lead an agritech startup in Europe, or advise smallholders in Asia and Africa, this book shows how predictive models and IoT transform crop performance, resource use, and profitability.

Dive into clear explanations of machine learning techniques, time-series forecasting for yield prediction, remote sensing and drone imagery analysis, soil and weather sensor integration, and real-world case studies across temperate, tropical, and arid regions. Technical enough for data scientists and accessible for agronomists, the text balances algorithms, deployment strategies, and on-the-ground implications for precision farming and sustainable agriculture.

Discover actionable workflows for building predictive pipelines, improving irrigation scheduling, detecting pests early, and optimizing fertilizer application to cut costs and environmental impact. Each chapter links analytical methods to measurable outcomes — higher yields, lower input waste, and smarter risk management — making it indispensable for farmers, extension officers, researchers, and policymakers.

Packed with practical insights and regional relevance, Predictive Analytics in Smart Agriculture empowers readers to implement scalable solutions across diverse agricultural systems. Elevate your farm management, research, or consultancy with the tools to predict tomorrow’s conditions today. Order now to start turning data into reliable agricultural advantage.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.