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Flight patterns of Apis mellifera and Bombus terrestris near their hives for image deep learning
- 언어ENG
- URLhttps://db.koreascholar.com/Article/Detail/433421
Bee traffic at the hive entrance can be used as an important indicator of foraging activity. We investigated patterns of honeybees and bumblebees near their hives as a basis for calculating bee traffic using the image deep learning. The flight pattern near the hive differed significantly according to bee at entering and leaving the hive. Honeybees mainly showed flight that changed flight direction more than once (69.5%), whereas bumblebees mainly performed straight flight (48.7%) or had a single turn (36.5%) in flight. When bees entered the hive, honeybees primarily showed one-turn or two-turn flight patterns(88.5%), and bumblebees showed a one-turn flight pattern (48.0%). In contrast, when leaving the hive, honeybees primarily showed a straight flight pattern (63.0%), and bumblebees primarily showed a straight or one-turn pattern (90.5%). There was a significant difference in flight speed according to the flight pattern. The speed of straight flight (0.89±0.47 m/s) was 1.5 to 2.1 times faster than flight where direction changed. Therefore, our results can help determine the capturing and recognizing the flying image of bees when calculating bee traffic by image deep learning.
