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Using the software DeepWings© to classify honey bees across europe through wing geometric morphometrics

2022Journal article Open access
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dc.contributor.authorGarcia, Carlos A.Y.
dc.contributor.authorRodrigues, Pedro João
dc.contributor.authorTofilski, Adam
dc.contributor.authorElen, Dylan
dc.contributor.authorMcCormack, Grace P.
dc.contributor.authorOleksa, Andrzej
dc.contributor.authorHenriques, Dora
dc.contributor.authorIlyasov, Rustem
dc.contributor.authorKartashev, Anatoly
dc.contributor.authorBargain, Christian
dc.contributor.authorFried, Balser
dc.contributor.authorPinto, M. Alice
dc.date.accessioned2013-01-15T16:58:10Z
dc.date.available2013-01-15T16:58:10Z
dc.date.issued2022
dc.description.abstractDeepWings© is a software that uses machine learning to automatically classify honey bee subspecies by wing geometric morphometrics. Here, we tested the five subspecies classifier (A. m. carnica, Apis mellifera caucasia, A. m. iberiensis, Apis mellifera ligustica, and A. m. mellifera) of DeepWings© on 14,816 wing images with variable quality and acquired by different beekeepers and researchers. These images represented 2601 colonies from the native ranges of the M-lineage A. m. iberiensis and A. m. mellifera, and the C-lineage A. m. carnica. In the A. m. iberiensis range, 92.6% of the colonies matched this subspecies, with a high median probability (0.919). In the Azores, where the Iberian subspecies was historically introduced, a lower proportion (85.7%) and probability (0.842) were observed. In the A. m mellifera range, only 41.1 % of the colonies matched this subspecies, which is compatible with a history of C-derived introgression. Yet, these colonies were classified with the highest probability (0.994) of the three subspecies. In the A. m. carnica range, 88.3% of the colonies matched this subspecies, with a probability of 0.984. The association between wing and molecular markers, assessed for 1214 colonies from the M-lineage range, was highly significant but not strong (r = 0.31, p < 0.0001). The agreement between the markers was influenced by C-derived introgression, with the best results obtained for colonies with high genetic integrity. This study indicates the good performance of DeepWings© on a realistic wing image dataset.por
dc.identifier.citationGarcia, Carlos A.Y.; Rodrigues, Pedro João; Tofilski, Adam; Elen, Dylan; McCormak, Grace P.; Oleksa, Andrzej; Henriques, Dora; Ilyasov, Rustem; Kartashev, Anatoly; Bargain, Christian; Fried, Balser; Pinto, M. Alice. (2022). Using the software DeepWings© to classify honey bees across europe through wing geometric morphometrics. Insects. EISSN 2075-4450. 13:12, p. 1-18
dc.identifier.eissn2075-4450
dc.identifier.urihttp://hdl.handle.net/10198/7930
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherMDPI
dc.titleUsing the software DeepWings© to classify honey bees across europe through wing geometric morphometricspor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleInsectspor
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.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication6c5911a6-b62b-4876-9def-60096b52383a
relation.isAuthorOfPublicationd2abd09f-a90c-4cfb-9a60-7fc32f56184d
relation.isAuthorOfPublication0667fe04-7078-483d-9198-56d167b19bc5
relation.isAuthorOfPublication.latestForDiscovery0667fe04-7078-483d-9198-56d167b19bc5

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