Automated computer-based detection of encounter behaviours in groups of honeybees

Automated computer-based detection of encounter behaviours in groups of honeybees
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DOI:
10.1038/s41598-017-17863-4
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发表时间:
2017-12-15
期刊:
影响因子:
4.6
通讯作者:
Beye, Martin
Beye, Martin
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Blut, Christina;Crespi, Alessandro;Beye, Martin

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蜜蜂形成了一个社会,在这个社会中,成千上万的成员将他们的行为整合为一个单一的功能单位。我们对协作功能如何受工蜂活动的调控知之甚少,因为我们缺乏能够收集每只工蜂同时和连续行为信息的方法。在这项研究中,我们介绍了蜜蜂行为注释系统(BBA),它能够在小型观察蜂箱中自动检测蜜蜂的行为。在一个小型观察蜂箱中,通过用2D条形码标记工蜂,获得了关于位置和方向的连续信息。我们从跟踪信息中计算行为和社会特征,以使用基于机器学习的系统来训练行为分类器,以识别遭遇行为(工作人员通过天线进行交互)。该分类器正确地检测了一群蜜蜂中93%的相遇行为,而错误分类的行为中有13%与相遇行为无关。建立自动注释行为的准确分类器的可能性可能允许在小型观察蜂箱的社会环境中检查工蜂的个体行为。我们预计,BBA将是一个强大的工具,用于检测实验性操纵社会属性的影响和杀虫剂对行为的亚致命影响。
Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable collection of simultaneous and continuous behavioural information for each worker bee. In this study, we introduce the Bee Behavioral Annotation System (BBAS), which enables the automated detection of bees' behaviours in small observation hives. Continuous information on position and orientation were obtained by marking worker bees with 2D barcodes in a small observation hive. We computed behavioural and social features from the tracking information to train a behaviour classifier for encounter behaviours (interaction of workers via antennation) using a machine learning-based system. The classifier correctly detected 93% of the encounter behaviours in a group of bees, whereas 13% of the falsely classified behaviours were unrelated to encounter behaviours. The possibility of building accurate classifiers for automatically annotating behaviours may allow for the examination of individual behaviours of worker bees in the social environments of small observation hives. We envisage that BBAS will be a powerful tool for detecting the effects of experimental manipulation of social attributes and sub-lethal effects of pesticides on behaviour.