Literature DB >> 33383770

Classifying the Biological Status of Honeybee Workers Using Gas Sensors.

Jakub T Wilk1, Beata Bąk1, Piotr Artiemjew2, Jerzy Wilde1, Maciej Siuda1.   

Abstract

Honeybee workers have a specific smell depending on the age of workers and the biological status of the colony. Laboratory tests were carried out at the Department of Apiculture at UWM Olsztyn, using gas sensors installed in two twin prototype multi-sensor detectors. The study aimed to compare the responses of sensors to the odor of old worker bees (3-6 weeks old), young ones (0-1 days old), and those from long-term queenless colonies. From the experimental colonies, 10 samples of 100 workers were taken for each group and placed successively in the research chambers for the duration of the study. Old workers came from outer nest combs, young workers from hatching out brood in an incubator, and laying worker bees from long-term queenless colonies from brood combs (with laying worker bee's eggs, humped brood, and drones). Each probe was measured for 10 min, and then immediately for another 10 min ambient air was given to regenerate sensors. The results were analyzed using 10 different classifiers. Research has shown that the devices can distinguish between the biological status of bees. The effectiveness of distinguishing between classes, determined by the parameters of accuracy balanced and true positive rate, of 0.763 and 0.742 in the case of the best euclidean.1nn classifier, may be satisfactory in the context of practical beekeeping. Depending on the environment accompanying the tested objects (a type of insert in the test chamber), the introduction of other classifiers as well as baseline correction methods may be considered, while the selection of the appropriate classifier for the task may be of great importance for the effectiveness of the classification.

Entities:  

Keywords:  classification; decision systems; electronic nose; gas sensor; honey bee

Mesh:

Year:  2020        PMID: 33383770      PMCID: PMC7795461          DOI: 10.3390/s21010166

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  4 in total

1.  The cuticular hydrocarbon profiles of honey bee workers develop via a socially-modulated innate process.

Authors:  Cassondra L Vernier; Joshua J Krupp; Katelyn Marcus; Abraham Hefetz; Joel D Levine; Yehuda Ben-Shahar
Journal:  Elife       Date:  2019-02-05       Impact factor: 8.140

2.  The effect of queen pheromones on worker honey bee ovary development.

Authors:  Shelley E R Hoover; Christopher I Keeling; Mark L Winston; Keith N Slessor
Journal:  Naturwissenschaften       Date:  2003-09-18

3.  Gas Sensor Array and Classifiers as a Means of Varroosis Detection.

Authors:  Andrzej Szczurek; Monika Maciejewska; Beata Bąk; Jakub Wilk; Jerzy Wilde; Maciej Siuda
Journal:  Sensors (Basel)       Date:  2019-12-23       Impact factor: 3.576

4.  Application of an electronic nose instrument to fast classification of Polish honey types.

Authors:  Tomasz Dymerski; Jacek Gębicki; Waldemar Wardencki; Jacek Namieśnik
Journal:  Sensors (Basel)       Date:  2014-06-18       Impact factor: 3.576

  4 in total
  1 in total

1.  In-Field Detection of American Foulbrood (AFB) by Electric Nose Using Classical Classification Techniques and Sequential Neural Networks.

Authors:  Beata Bąk; Jarosław Szkoła; Jakub Wilk; Piotr Artiemjew; Jerzy Wilde
Journal:  Sensors (Basel)       Date:  2022-02-02       Impact factor: 3.576

  1 in total

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