Akademik Veri Yönetim Sistemi
Computers and Electronics in Agriculture, cilt.241, 2026 (SCI-Expanded, Scopus)
Learning is an adaptive behavior that improves the performance of bees in foraging, dance communication, predator avoidance, and other tasks. Any deficiencies in learning could be detrimental to the long-term survival of the bee colony. The passive avoidance task is a fundamental procedure for investigating learning. We introduce Api-TRACE, a computer vision-aided system for analyzing avoidance assays. Api-TRACE tracks individual bees from the video footage of the assay and detects the moments when they are exposed to a stimulus. The algorithm provides the stimulus exposure duration and learning profiles of each individual bee, enabling fast and detailed analysis of the results. The electric shock avoidance assay (ESAA) is one of the most common experimental methods for assessing learning. We designed an apparatus for the ESAA using readily available hardware and 3D-printed components. Honey bee behavioral analyses are easily performed and automated with Api-TRACE and our easy-to-build apparatus. Our system enables large-scale studies on how environmental factors, chemicals, and other agricultural inputs affect bee learning, providing data to help protect bee health and, therefore, agricultural productivity. We used Api-TRACE and an experimental apparatus to investigate the effect of lithium on bee learning success in passive avoidance and reversal learning paradigms through an ESAA. Lithium is a potential chemical for combating Varroa, a bee (Apis) parasite, and a well-known medication for treating bipolar disorder. It is known that lithium alters learning in humans and other animals. Before the experiment, we treated the bees with a sucrose solution with 0, 5, 25, and 125 mM LiCl ad libitum. Our results indicated a decrease in learning performance with increasing lithium doses in the reversal phase but not in the acquisition phase of the ESAA.