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Sammanfattning

Plant-pollinator interactions are fundamental to the functioning of natural ecosystems and the enhancement of agricultural productivity. An effective support of pollinator communities necessitates a comprehensive understanding of the mechanisms underlying pollinator attraction and nutritional preferences. Pollinators depend on olfactory, visual, gustatory and tactile signals to locate and select floral resources. Investigating olfactory and gustatory preferences in flying insects, however, presents notable challenges due to the lack of standardised experimental frameworks, the labour-intensive nature of current methodologies and the limitations inherent in existing experimental systems, particularly their inadequacy in simultaneously delivering and measuring olfactory and gustatory cues. These constraints hinder the detailed understanding of how insects integrate multiple sensory modalities during foraging. In this study, we introduce a binary-choice flight arena and assay specifically designed for the investigation of scent and taste preferences in flying insects. To facilitate robust and unbiased behavioural data analysis, we developed a computer-vision-based tool capable of quantifying insect preferences from video recordings. The system's effectiveness was validated through a series of experimental trials, utilising definitive and quantifiable metrics, including (i) the number of visits at each feeding tube, (ii) the total number of insects interacting, (iii) the cumulative time spent by insects at each stimulus source per hour and (iv) the volume of reward solution consumed. Our findings demonstrate that the experimental framework, detection algorithm and arena design collectively facilitate balanced visitation rates under controlled conditions, yielding consistent and reliable quantifications. Our results also indicate that the setup is highly suitable for and will facilitate exploring the influence of olfactory and gustatory compounds on insect visitation patterns and feeding behaviours.

Nyckelord

bioinformatics; community ecology; computer vision; evolutionary biology; molecular evolution; monitoring (population ecology); population ecology; species interactions

Publicerad i

Methods in Ecology and Evolution
2026
Utgivare: WILEY

SLU författare

UKÄ forskningsämne

Ekologi

Publikationens identifierare

  • DOI: https://doi.org/10.1111/2041-210x.70276

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/146474