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DeepWings: a machine learning tool for identification of honey bee subspecies

dc.contributor.authorAriel Yadró, Carlos
dc.contributor.authorRodrigues, Pedro João
dc.contributor.authorAdam, Tofilski
dc.contributor.authorElen, Dylan
dc.contributor.authorMcCormack, Grace P.
dc.contributor.authorHenriques, Dora
dc.contributor.authorPinto, M. Alice
dc.date.accessioned2022-10-17T10:49:32Z
dc.date.available2022-10-17T10:49:32Z
dc.date.issued2022
dc.description.abstractDeepWings© is a software that uses Machine Learning for fully automated identification of Apis mellifera subspecies based on wing geometric morphometrics (WGM). Here, we examined the performance of DeepWings© under realistic conditions by processing 14,782 wing images with varying quality and produced by different operators. These images represented 2,593 colonies covering the native ranges of A. m. iberiensis (Portugal, Spain and historical introduction in the Azores), A. m. mellifera (Belgium, France, Ireland, Poland, Russia, Sweden, Switzerland, UK) and A. m. carnica (Croatia, Hungary, Romania). The classification probability obtained for the colonies was contrasted with the endemic subspecies distribution. Additionally, the association between WGM classification and that inferred from microsatellites and SNPs was evaluated for 1,214 colonies. As much as 94.4% of the wings were accepted and classified by DeepWings©. In the Iberian honey bee native range, 92,6% of the colonies were classified as A. m. iberiensis with a median probability of 91.88 (IQR = 22.52). In the Azores, 85.7% of colonies were classified as A. m. iberiensis, with a median probability of 84.16 (32.40). In the Dark honey bee native range, 41.1 % of the colonies were classified as A. m mellifera with a median probability of 99.36 (8.02). The low percentage of colonies matching the native subspecies was mainly due to the low values registered in Avignon (20.0%), Poland (32.9%), and Wales (41.2%). In contrast, most of the colonies analyzed in other locations of the native range of A. m. mellifera matched this subspecies: Belgium (100.0%), Groix (63.9%), Ouessant (72.7%), Ireland (78.0%), Russia (96.2%), Sweden (84.2%) and Switzerland (55.6%). In the colonies from Croatia, Hungary, and Romania, 88.0% of the samples were classified as A. m. carnica, with a median probability of 98.49 (6.76). The association between WGM and molecular data was highly significant but not very strong (Spearman r = 0.31, p < 0.0001). A good agreement between morphological and molecular methods was registered in samples originating from highly conserved M-lineage populations whereas in populations with historical records of foreign queen importations the agreement was weaker. In general, DeepWings© showed good performance when tested under realistic conditions. It is a valuable tool that can be used not only for honey bee breeding and conservation but also for research purposes.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationYadró, Carlos; Rodrigues, Pedro João; Adam, Tofilski; Elen, Dylan; McCormack, Grace P.; Henriques, Dora; Pinto, M. Alice (2022). DeepWings: a machine learning tool for identification of honey bee subspecies. In Eurbee 9: 9th European Conference of Apidology. Belgradept_PT
dc.identifier.urihttp://hdl.handle.net/10198/26007
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherEstonian University of Life Sciencept_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectWing Geometric Morphometricspt_PT
dc.subjectApis mellifera subspecies classificationpt_PT
dc.subjectHoney bee conservationpt_PT
dc.titleDeepWings: a machine learning tool for identification of honey bee subspeciespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBelgradept_PT
oaire.citation.endPage317pt_PT
oaire.citation.startPage316pt_PT
oaire.citation.titleEurbee 9: 9th European Conference of Apidologypt_PT
person.familyNameRodrigues
person.familyNameHenriques
person.familyNamePinto
person.givenNamePedro João
person.givenNameDora
person.givenNameMaria Alice
person.identifier.ciencia-id1316-21BB-9015
person.identifier.ciencia-id291F-986F-07DA
person.identifier.ciencia-idF814-A1D0-8318
person.identifier.orcid0000-0002-0555-2029
person.identifier.orcid0000-0001-7530-682X
person.identifier.orcid0000-0001-9663-8399
person.identifier.scopus-author-id55761737300
person.identifier.scopus-author-id8085507800
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication6c5911a6-b62b-4876-9def-60096b52383a
relation.isAuthorOfPublicationd2abd09f-a90c-4cfb-9a60-7fc32f56184d
relation.isAuthorOfPublication0667fe04-7078-483d-9198-56d167b19bc5
relation.isAuthorOfPublication.latestForDiscoveryd2abd09f-a90c-4cfb-9a60-7fc32f56184d

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