Development of Imaging-Based Honeybee Traffic Measurement System and Its Application to Crop Pollination

Abstract

Bee traffic can be used as an indicator of the health of bee colonies, age, production of honeybee products, and crop pollination. To study bee pollination processes, we developed an algorithm that can automatically measure bee traffic through an image processing system. The match rate between the bee traffic observed through the system and the traffic that was visually observed was 93.6%. However, the higher the bee traffic, the lower the match rate. We applied the system in a strawberry cultivation greenhouse containing two colonies (one with 12500 bees and one with 10000 bees), and there was a significant difference in bee traffic between the two colonies. In addition, bee traffic depends on the climatic conditions inside the greenhouse (air temperature, relative humidity, illumination, and UV radiation), and there was a significant correlation between these indicators and the level of bee traffic observed. There was also a strong correlation (R>0.8) between bee traffic and foraging activity (which is correlated with pollination), and the foraging activity could be estimated with a high probability (R²=0.74). Therefore, the bee traffic measurement system developed in this study can be used to study the effect of pollination on crops, and is expected to be applied as a major model for producing high-quality agricultural products in smart beekeeping and crop smart farms.