Honeybees pollinate over 75% of the total food resources produced annually, and they produce valuable hive products, such as bee pollen, propolis, and royal jelly. However, species such as the Asian hornet (Vespa velutina) feed on more than 85% of honeybees, causing a decline in their population and considerable damage to beekeepers in Korea. To prevent damage to honeybees, a portable real-time monitoring system was developed that detects V. velutina individuals and notifies users of their presence. This system was designed with a focus on portability and ease of installation, as V. velutina can be found in various areas of apiary sites. To detect V. velutina, an improved convolutional neural network YOLOv5s was trained on 1960 high-resolution ($3840\times 2160$) image data. At the confidence threshold of ≥0.600 and intersection over the union of ≥0.500, the performance of the system in terms of detection accuracy, precision, recall, F1 score, and mean average precision was high. A distance-based performance comparison showed that the system was able to detect V. velutina individuals while monitoring three beehives. During a field test of monitoring three beehives, the system could detect 83.3% of V. velutina during their hunting activities and send alarms to registered mobile application users.

Vespa velutina is an ecosystem disruptor that causes annual damage worth KRW 170 billion (USD 137 million) to the South Korean beekeeping industry. Due to its strong fertility and high-lying habitat, it is difficult to control. This study aimed to develop a system for the control of V. velutina nests using drones for detection and tracking the real-time location of the nests. Vespa velutina nest image data were acquired in Buan-gun and Wanju-gun (Jeollabuk-do), and artificial intelligence learning was conducted using YOLO-v5. Drone image resolutions of 640, 1280, 1920, and 3840 pixels were compared and analyzed. The 3840-pixel resolution model was selected, as it had no false detections for the verification image and showed the best detection performance, with a precision of 100%, recall of 92.5%, accuracy of 99.7%, and an F1 score of 96.1%. A computer (Jetson Xavier), real-time kinematics module, long-term evolution modem, and camera were installed on the drone to acquire real-time location data and images. Vespa velutina nest detection and location data were delivered to the user via artificial intelligence analysis. Utilizing a drone flight speed of 1 m/s and maintaining an altitude of 25 m, flight experiments were conducted near Gyeongcheon-myeon, Wanju-gun, Jeollabuk-do. A total of four V. velutina nests were successfully located. Further research is needed on the detection accuracy of artificial intelligence in relation to objects that require altitude-dependent variations in drone-assisted exploration. Moreover, the potential applicability of these research findings to diverse domains is of interest.

The honey bee, a crucial organism that provides ecological and economic value to humans, is currently facing threats from various environmental factors including pesticides. Numerous studies have been conducted to demonstrate the risks associated with neonicotinoid pesticides, but research on their occurrence in actual field conditions has not been identified. Therefore, in this study, we observed changes in honey bee (Apis mellifera) colonies located near rice cultivation areas as they progressed beyond the rice pesticide application period. Furthermore, we collected honey bees exposed to the clothianidin and analyzed their stress-related gene expression. The results showed that the foraging behavior of honey bee colonies located near rice cultivation areas did not exhibit significant differences between the treatment sites (Cheongyang and Gimje) and the control site (Wanju) during the experimental period. However, it was observed that the expression levels of stress-related genes in honey bees collected from the treatment group were significantly higher than those in the control. Most of the stress-related genes were associated with detoxification processes in response to pesticides. As a result, pesticide treatment in proximity to rice cultivation areas did not cause direct damage to honey bees but had an indirect impact, suggesting the potential for ongoing chronic damage.

Honey bee reproductive behavior involves a complicated mating system that embodies a number of factors, including environmental and human-induced factors. Controlled breeding in isolated mating stations is a prerequisite to maintain the genetic resources of honey bees through natural mating. The concept of controlled mating is a challenge in most beekeeping operations due to its low mating success rate. Therefore, a detailed investigation into the suitability of isolated mating stations is of interest. Thus, we bred two subspecies of honey bees (Apis cerana koreana and Apis mellifera L.) in isolated mating stations (island) from 2021 to 2023 and in an open breeding station in 2023. Our results demonstrate that the highest percentage of the mating success rate in isolated mating stations was recorded in the Wido Island, which had the highest percentage of bare land, coniferous forests, deciduous forests, fields, and mixed forests. The mating success rate was higher in the summer and spring for A. cerana and A. mellifera, respectively. The mating success rate was higher in open mating compared to controlled mating (Island) and did not vary between pure-breeding and cross-breeding lines. Our findings suggested that mating stations with mixed forest and fields are potential sites for the successful breeding of honey bees.

Honey bees (Apis mellifera L.) express complex behavioral patterns (aggressiveness) in defensive mechanisms for their survival. Their phenotypic expression of defensive behavior is influenced by internal and external stimuli. Knowledge of this behavior has recently become increasingly important, though beekeepers are still faced with the challenges of selecting defensive and less-defensive bred lines. Field evaluation of defensive behavior among bred lines of honey bees is required to overcome the challenges. Chemical cues (alarm pheromone and isopentyl acetate mixed with paraffin oil) and physical and visual stimuli (dark leather suede, colony marbling, and suede jiggling) were used to evaluate defensiveness and orientation among five bred lines of honeybee colonies. Our results showed that both chemical assays recruited bees, but the time of recruitment was significantly faster for alarm pheromone. Honeybees’ response to both assays culminated in stings that differed among bred lines for alarm pheromone and paraffin when colonies were marbled. Honeybee orientation defensiveness varied among bred lines and was higher in more defensive bred lines compared to less-defensive bred lines. Our findings suggest that it is crucial to repeatedly evaluate orientation defensiveness at the colony level and among bred lines when selecting breeding colonies.

The ectoparasitic mite Varroa destructor is well known for transmitting a number of viruses that can contribute to the collapse of honeybee colonies. To date, the many control measures put in place to limit the spread of V. destructor have yielded no satisfactory results. This is challenging because the effect of the parasite on honeybee colonies is becoming notorious. This has weakened the beekeeping industry and reduced pollination services, which may contribute to global food insecurity in the future. Therefore, it is necessary to put in place possible control measures and outline sustainable approaches to mitigate research efforts against the Varroa destructor. Extensive research to elaborate on the best possible solution has revealed that the selective breeding of naturally occurring V. destructor immune-related traits of honeybee strains is sustainable. Since the Integrated Pest Management approach was introduced, while still being very unreliable, there are open questions as to what control strategy could be considered effective. After cross-examination of existing strategies, a more practical way could be the adoption of an integrated approach. This approach should involve the association of selective breeding of honeybee colonies with V. destructor immune-related traits and the application of soft chemical treatment.