Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/58990
Title: Bayesian Multi-Targets Strategy to Track Apis mellifera Movements at Colony Level
Keywords: Crowded image processing
Living system
Entropy
Kernel density estimations
Probability distribution functions; bee contamination
Issue Date: 9-Feb-2022
Publisher: MDPI
Citation: OLIVEIRA, Jordão N.; SANTOS, Jônatas C.; JUMBO, Luis O. Viteri; ALMEIDA, Carlos H. S.; TOLEDO, Pedro F. S.; REZENDE, Sarah M.; HADDI, Khalid; SANTANA, Weyder C.; BESSANI, Michel; ACHCAR, Jorge A.; OLIVEIRA, Eugenio E.; MACIEL, Carlos D. Bayesian multi-targets strategy to track apis mellifera movements at colony level. Insects, v. 13, n. 2, p. 1-12,Feb. 2022. DOI: https://doi.org/10.3390/insects13020181.
Abstract: Interactive movements of bees facilitate the division and organization of collective tasks, notably when they need to face internal or external environmental challenges. Here, we present a Bayesian and computational approach to track the movement of several honey bee, Apis mellifera, workers at colony level. We applied algorithms that combined tracking and Kernel Density Estimation (KDE), allowing measurements of entropy and Probability Distribution Function (PDF) of the motion of tracked organisms. We placed approximately 200 recently emerged and labeled bees inside an experimental colony, which consists of a mated queen, approximately 1000 bees, and a naturally occurring beehive background. Before release, labeled bees were fed for one hour with uncontaminated diets or diets containing a commercial mixture of synthetic fungicides (thiophanate-methyl and chlorothalonil). The colonies were filmed (12 min) at the 1st hour, 5th and 10th days after the bees’ release. Our results revealed that the algorithm tracked the labeled bees with great accuracy. Pesticide-contaminated colonies showed anticipated collective activities in peripheral hive areas, far from the brood area, and exhibited reduced swarm entropy and energy values when compared to uncontaminated colonies. Collectively, our approach opens novel possibilities to quantify and predict potential alterations mediated by pollutants (e.g., pesticides) at the bee colony-level.
URI: https://www.mdpi.com/2075-4450/13/2/181
http://repositorio.ufla.br/jspui/handle/1/58990
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