Classification of beekeeping provinces in Türkiye using data mining methods and research into production trends. Technical note

Abstract

Beekeeping holds significant importance both in human nutrition and economically worldwide. The objective of this study is to classify provinces in Türkiye based on beekeeping production indicators using K–Means clustering method. Furthermore, by utilizing national data related to production indicators, ascending and descending trends were identified. Five production indicators (number of enterprises, number of colonies, total honey production, beeswax production, and honey yield per colony) from the years 1991 to 2022 were analyzed. For an objective and accurate classification of the provinces, the K–Means clustering method, as a data mining technique, was employed. To identify trends, the Sen Trend and Modified Mann–Kendall test were used. As a result of the K–Means clustering method, a structure with three clusters, comprising 4, 11, and 66 provinces, was obtained. Ordu, Muğla, Adana, and Sivas were grouped in cluster 1, which is the top cluster with the highest productivity (P<0.001). These provinces stand out with their different aspects. In Adana, which is categorised in cluster 1 in the Mediterranean Region, colony production continues in the winter months also. In Ordu, the most active city in the Black Sea region, the implementation of modern training programs plays a significant role in achieving high honey yield per colony. On the other hand, the Sen trend analysis results revealed a negative trend in honey yield per colony but positive trends in the remaining indicators (all P<0.001). In conclusion, it was determined that implementing practices aimed at supporting beekeeping productivity in provinces within Cluster 2 and 3 is essential. Accordingly, by ensuring ascending trends in all production indicators, a contribution to global beekeeping activities can be achieved.