McLean Callum J, Fisher David N
School of Biological Sciences, University of Aberdeen, King's College, Aberdeen, UK.
J Insect Sci. 2025 Jan 20;25(1). doi: 10.1093/jisesa/ieaf002.
Radio frequency identification (RFID) technology and marker recognition algorithms can offer an efficient and non-intrusive means of tracking animal positions. As such, they have become important tools for invertebrate behavioral research. Both approaches require fixing a tag or marker to the study organism, and so it is useful to quantify the effects such procedures have on behavior before proceeding with further research. However, frequently studies do not report doing such tests. Here, we demonstrate a time-efficient and accessible method for quantifying the impact of tagging on individual movement using open-source automated video tracking software. We tested the effect of RFID tags and tags suitable for marker recognition algorithms on the movement of Argentinian wood roaches (Blapicta dubia, Blattodea: Blaberidae) by filming tagged and untagged roaches in laboratory conditions. We employed DeepLabCut on the resultant videos to track cockroach movement and extract measures of behavioral traits. We found no statistically significant differences between RFID tagged and untagged groups in average speed over the trial period, the number of unique zones explored, and the number of discrete walks. However, groups that were tagged with labels for marker recognition had significantly higher values for all 3 metrics. We therefore support the use of RFID tags to monitor the behavior of B. dubia but note that the effect of using labels suitable for label recognition to identify individuals should be taken into consideration when measuring B.dubia behavior. We hope that this study can provide an accessible and viable roadmap for further work investigating the effects of tagging on insect behavior.
射频识别（RFID）技术和标记识别算法可以提供一种高效且非侵入性的动物位置跟踪方法。因此，它们已成为无脊椎动物行为研究的重要工具。这两种方法都需要在研究生物体上固定标签或标记，所以在进行进一步研究之前，量化这些操作对行为的影响是很有用的。然而，研究常常没有报告进行过此类测试。在这里，我们展示了一种使用开源自动视频跟踪软件来量化标记对个体运动影响的省时且易于操作的方法。我们通过在实验室条件下拍摄有标记和无标记的阿根廷木蠊（Blapicta dubia，蜚蠊目：硕蠊科），测试了RFID标签和适用于标记识别算法的标签对其运动的影响。我们在所得视频上使用DeepLabCut来跟踪蟑螂的运动并提取行为特征的测量值。我们发现在试验期间，RFID标记组和未标记组在平均速度、探索的独特区域数量以及离散行走次数方面没有统计学上的显著差异。然而，用适用于标记识别的标签标记的组在所有这三个指标上的值都显著更高。因此，我们支持使用RFID标签来监测阿根廷木蠊的行为，但请注意，在测量阿根廷木蠊行为时，应考虑使用适用于标记识别的标签来识别个体的影响。我们希望这项研究能够为进一步研究标记对昆虫行为的影响提供一条易于操作且可行的路线图。
