Application of machine learning in optimizing irrigation management practices: A systematic literature review and bibliometric analysis

The emergence of machine learning (ML) approaches to irrigation management systems is transforming how resources derived from nature are handled. To better understand the subject, we used 127 Scopus-indexed publications from 2013 to 2024 (till April 24) to investigate theme progression and future research prospects. We conducted a comprehensive literature review and bibliometric analysis with the R studio bibliometrix package and the VOS viewer software. We discovered that issues relevant to ML for managing irrigation practices have grown considerably since 2013. India ranks highest with 33 documents and 1497 citations. The findings reveal that data mining, crop production and empirical analysis are the emerging themes and machine learning, irrigation and soil moisture exhibit the motor themes.