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—In this paper, we analyze the periodic cycle of honeybees when they have between 7 and 9 days of age. The circadian clock of the bees present very erratic behavior that it is a challenge to detect cycles. In signal processing, there are several methods to detect periodic patterns. In here, we will use a well-known test, named periodogram, to evaluate rhythmicity and estimate the period. Besides, to determine whether or no rhythmicity exists, we estimate the time when the bees behavior starts to be rhythmic. Also, it can occur that the bees behavior never gets rhythmic. The test of rhythmicity is applied consecutively until find out periodicity, if this exists. Furthermore, we carry out the periodicity test for the time series obtained from the actogram. We find out that for bees which time series is visually periodic, our method detects correctly the starting time. However, for bees which time series does not show a cyclic pattern our method fails due to a very erratic time series and that the consecutive test results also will show this erratic behavior. Finally, we classify the bees according to theirs beginning of a periodic cycle, using functional data analysis.
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Clustering Honeybees by Its Daily Activity [Clustering Honeybees by Its Daily Activity]
In this work, we analyze the activity of bees starting at 6 days old. The data was collected at the INRA (France) during 2014 and 2016. The activity is counted according to whether the bees enter or leave the hive. After data wrangling, we decided to analyze data corresponding to a period of 10 days. We use clustering method to determine bees with similar activity and to estimate the time during the day when the bees are most active. To achieve our objective, the data was analyzed in three different time periods in a day. One considering the daily activity during in two periods: morning and afternoon, then looking at activities in periods of 3 hours from 8:00am to 8:00pm and, finally looking at the activities hourly from 8:00am to 8:00pm. Our study found two clusters of bees and in one of them clearly the bees activity increased at the day 5. The smaller cluster included the most active bees representing about 24 percent of the total bees under study. Also, the highest activity of the bees was registered between 2:00pm until 3:00pm. A Chi-square test shows that there is a combined effect Treatment× Colony on the clusters formation.
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- PAR ID:
- 10095828
- Date Published:
- Journal Name:
- Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
- Volume:
- 1
- Page Range / eLocation ID:
- 598 to 604
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5220/0007387505980604
