Morphometric Identification of An Unknown Honey Bee Colony: An Example From North India

Abstract Identification of the honey bee ( Apis mellifera ) subspecies is an important aspect of bee breeding and biodiversity conservation. The identification can be based on molecular or morphological markers. For some markers, including the cytochrome c oxidase subunit, there is a well-established methodology allowing consistent subspecies identification in different laboratories. In the case of morphological markers, identification is hindered by a lack of reference data and a standardized methodology to reuse it. There is the Morphometric Bee Data Bank in Oberursel, Germany, which provides reliable reference data for many honey bee subspecies; however, it must be expanded and updated. Moreover, there is a need for standardized protocols that allow reliable identification of unknown samples. We show here that reference data for the identification of honey bees based on geometric morphometrics can be saved in an XML file. The information in this file can be easily extracted by other users for the identification of unknown samples. We illustrate this procedure using ten samples from north India. The samples were identified as A. mellifera ; next, they were identified as lineage C; and finally, most of the samples had high similarity to honey bees from Croatia and Slovenia. We explained what data is required for such identification and how it can be reused. The method described here works correctly only if the identified species or subspecies is well represented in the reference samples. Without reference data from America, we could not confirm the importation of honey bees to India from this region.

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Publication Details

Journal
Journal of Apicultural Science
Published
2024-12-01
DOI
https://doi.org/10.2478/jas-2024-0013
Citations
3
Primary Topic
Plant and animal studies
Type
article
Field-Weighted Citation Impact
3.09

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article

Morphometric Identification of An Unknown Honey Bee Colony: An Example From North India

Adam Tofilski, Hardeep Kaur, Ganie Sajad Ahmad
3 citations
Journal of Apicultural Science
Plant and animal studies
3.09
article

Morphometric Identification of An Unknown Honey Bee Colony: An Example From North India

Adam Tofilski, Hardeep Kaur, Ganie Sajad Ahmad
article en
3 citations

Abstract

Abstract Identification of the honey bee ( Apis mellifera ) subspecies is an important aspect of bee breeding and biodiversity conservation. The identification can be based on molecular or morphological markers. For some markers, including the cytochrome c oxidase subunit, there is a well-established methodology allowing consistent subspecies identification in different laboratories. In the case of morphological markers, identification is hindered by a lack of reference data and a standardized methodology to reuse it. There is the Morphometric Bee Data Bank in Oberursel, Germany, which provides reliable reference data for many honey bee subspecies; however, it must be expanded and updated. Moreover, there is a need for standardized protocols that allow reliable identification of unknown samples. We show here that reference data for the identification of honey bees based on geometric morphometrics can be saved in an XML file. The information in this file can be easily extracted by other users for the identification of unknown samples. We illustrate this procedure using ten samples from north India. The samples were identified as A. mellifera ; next, they were identified as lineage C; and finally, most of the samples had high similarity to honey bees from Croatia and Slovenia. We explained what data is required for such identification and how it can be reused. The method described here works correctly only if the identified species or subspecies is well represented in the reference samples. Without reference data from America, we could not confirm the importation of honey bees to India from this region.

Journal of Apicultural ScienceVol. 68(2)
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (IN), University of Agriculture in Krakow (PL)
Narodowym Centrum Nauki
Openalex Percentile: Top 8%
Plant and animal studies
3.09
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