Artificial intelligence in sustainable horticultural production: a systematic review

Abstract Artificial intelligence (AI) is playing a key role in making horticultural production more efficient, sustainable, and precise. This review focuses on recent advances in AI technologies such as machine learning (ML), deep learning (DL), and the Internet of Things (IoT) and their applications in horticulture. AI tools like sensors, drones, and robots help monitor crops in real time, automate tasks, and support better decision-making. In addition, case studies show how AI can reduce resource use, improve productivity, and address challenges like climate change and post-harvest losses. Moreover, AI applications in various areas, including pest and disease management, prediction of crop yield and quality, harvesting, postharvest handling, processing, and losses of horticultural crops, cultivar classification and weed detection, retail marketing of horticultural crops, prediction and detection of crop loss brought on by natural calamities, soil health monitoring , irrigation management , floriculture and landscaping, and other applications for sustainable horticultural production, are covered in the review. Practical challenges in the adoption of AI technologies in horticulture and future directions are also discussed for achieving sustainable horticultural production.