MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees

We present a one-year-long Multi-Sensor dataset with Phenotypic trait measurements from honey Bees (MSPB). Data were continuously collected between April-2020 and April-2021 from 53 hives located at two apiaries in Québec, Canada. The sensor data included audio features, temperature, and relative humidity. The phenotypic measurements contained beehive population, number of brood cells (eggs, larva and pupa), Varroa destructor infestation levels, defensive and hygienic behaviors, honey yield, and winter mortality. Our study is amongst the first to provide a wide variety of phenotypic trait measurements annotated by apicultural science experts, which facilitate a broader scope of analysis on honey bees, such as bee acoustics analysis, multi-modal hive monitoring, queen presence detection, Varroa infection detection, hive population estimation, biological analysis of bees, etc.

Related Info

The data collection process, feature pre-processing, preliminary data analysis, and usage notes can be found in our paper https://arxiv.org/abs/2311.10876

Check the project webpage (https://zhu00121.github.io/MSPB-webpage/) and Github repo (https://github.com/MuSAELab/MSPB) for more information.

Citation

Kindly cite the following paper:

@misc{zhu2023mspb,

     title={MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees},  

     author={Yi Zhu and Mahsa Abdollahi and Ségolène Maucourt and Nico Coallier and Heitor R. Guimarães and Pierre Giovenazzo and Tiago H. Falk},

     year={2023},

     eprint={2311.10876},

     archivePrefix={arXiv},

     primaryClass={eess.AS}

}

Contact

You can contact us at [e-mail], if you encounter any questions accessing the data.