Application of Machine Learning in Horticulture

The development of machine learning (ML) technologies in recent years has opened new opportunities for the horticulture sector, enabling more precise, efficient and sustainable crop management. The aim of this publication is to review the applications of machine learning techniques in horticulture, with particular emphasis on image analysis, decision support systems, yield prediction and resource management. The most commonly used algorithms are described and their potential and challenges related to implementation in the horticultural context are discussed. The work also indicates areas requiring further research that can contribute to increasing productivity and minimizing the impact of agriculture on the environment.