Document Type
Article
Author ORCID Identifier
Vladimir A. Kulyukin https://orcid.org/0000-0002-8778-5175
Aleksey V. Kulyukin https://orcid.org/0009-0009-4396-9878
William G. Meikle https://orcid.org/0000-0002-1759-6950
Journal/Book Title/Conference
Sensors
Volume
25
Issue
14
Publisher
MDPI AG
Publication Date
7-10-2025
Journal Article Version
Version of Record
First Page
1
Last Page
27
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Abstract
We explored the stationarity, trend, and seasonality of the hive weight and in-hive temperature of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, Arizona, USA. The hives were monitored with electronic scales and in-hive temperature sensors from June to October 2022. The weight and temperature were recorded every five minutes around the clock. The collected data were curated into 2160 timestamped weight and 2160 timestamped temperature observations. We performed a systematic autoregressive integrated moving average (ARIMA) time series analysis to answer three fundamental questions: (a) Does seasonality matter in the ARIMA forecasting of hive weight and in-hive temperature? (b) To what extent do the best forecasters of one hive generalize to other hives? and (c) Which time series type (i.e., hive weight or in-hive temperature) is better predictable? Our principal findings were as follows: (1) The hive weight and in-hive temperature series were not white noise, were not normally distributed, and, for most hives, were not difference- or trend-stationary; (2) Seasonality matters, in that seasonal ARIMA (SARIMA) forecasters outperformed their ARIMA counterparts on the curated dataset; (3) The best hive weight and in-hive temperature forecasters of the ten monitored colonies appeared to be colony-specific; (4) The accuracy of the hive weight forecasts was consistently higher than that of the in-hive temperature forecasts; (5) The weight and temperature forecasts exhibited common qualitative patterns.
Recommended Citation
Kulyukin, V.A.; Kulyukin, A.V.; Meikle, W.G. Discrete Time Series Forecasting in Non-Invasive Monitoring of Managed Honey Bee Colonies: Part II: Are Hive Weight and In-Hive Temperature Seasonal and Colony-Specific? Sensors 2025, 25, 4319. https://doi.org/10.3390/s25144319