Artificial Intelligence in Horticulture: Fundamentals Concepts, Applications and Case Studies presents a comprehensive examination of the emerging role of artificial intelligence in modern horticultural science and production. The book brings together fundamental concepts, advanced methodologies, practical applications, and emerging research directions in AI-enabled horticulture. It covers machine learning, deep learning, computer vision, remote sensing, IoT, precision irrigation, crop-yield prediction, plant disease detection, pest identification, post-harvest quality assessment, cold-chain optimization, AI-powered drones, smart greenhouse automation, and climate-smart horticulture.

The chapters also examine emerging technologies such as digital twins, foundation models, large language models, vision transformers, graph neural networks, federated learning, explainable AI, robotics, and multimodal AI. Particular emphasis is placed on data-driven decision-making, sustainable resource management, automation, crop health monitoring, and intelligent horticultural systems.

Designed for students, researchers, academicians, agricultural professionals, horticulturists, and technology practitioners, the book provides an interdisciplinary perspective on how AI can contribute to productive, efficient, resilient, and sustainable horticultural systems.