Evidence map›Paper›PMID 40779082›Full record

ArticleJournal of chemical ecology2025

Arduino-Based Volatile Delivery System for Evaluating Honeybee Learning.

Guillermo Bragunde, Gabriel González, Carmen Rossini

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of chemical ecology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Guillermo BragundeLaboratorio de Ecología Química, Facultad de Química, Universidad de la República, Gral. Flores 2124, Montevideo, CP 11800, Uruguay.ORCID http://orcid.org/0000-0002-3489-6154
Gabriel GonzálezTaller de Instrumentos, Facultad de Química, Universidad de la República, Gral. Flores 2124, Montevideo, CP 11800, Uruguay.
Carmen RossiniLaboratorio de Ecología Química, Facultad de Química, Universidad de la República, Gral. Flores 2124, Montevideo, CP 11800, Uruguay. crossini@fq.edu.uy.ORCID http://orcid.org/0000-0003-1222-5381

Funding

ANII (Agencia Nacional de Innovación e Investigación-Uruguay) FSA_1_2018_1_152862ANII (Agencia Nacional de Innovación e Investigación-Uruguay) POS_FSA_2019_2_1009134Comisión Académica de Posgrados, Universidad de la República Doctoral fellowshipCSIC (Comisión Sectorial de Investigación Científica, Universidad de la República CSIC-Grupos 2022
6 · The paper itself

Abstract

The proboscis extension reflex (PER) conditioning protocol is a widely used paradigm for studying learning and memory in honeybees. Accurate and consistent delivery of odor stimuli is essential for ensuring reproducible conditioning results, yet many existing systems require complex and expensive equipment. Here, we present a low-cost, fully documented Arduino-based system for automated volatile delivery during PER conditioning assays. The system integrates solenoid and servo valves, allowing controlled airflow between clean air and odorant channels, with stimulus timing managed by easily modifiable open-source code. Using this setup, we successfully conditioned Apis mellifera workers to associate 1-hexanol with a sucrose reward, achieving response rates comparable to those reported in previous studies. After three conditioning trials, 90% of honeybees exhibited conditioned responses, and 75% retained the association after five trials. This accessible and flexible system provides a reliable tool for researchers and educators aiming to implement classical conditioning protocols without requiring specialized technical expertise or infrastructure.

Indexed as

LearningAnimalsBeesConditioning, ClassicalHexanolsOdorantsSucroseHexanolsSucroseApis melliferaArduinoPERProboscis extension response

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.