Identification of pollen taxa by different microscopy techniques

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62157124%3A16270%2F21%3A43879465" target="_blank" >RIV/62157124:16270/21:43879465 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/21:PU144076
Result on the web
<a href="https://doi.org/10.1371/journal.pone.0256808" target="_blank" >https://doi.org/10.1371/journal.pone.0256808</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pone.0256808" target="_blank" >10.1371/journal.pone.0256808</a>

Result language
angličtina
Original language name
Identification of pollen taxa by different microscopy techniques
Original language description
Melissopalynology is an important analytical method to identify botanical origin of honey. Pollen grain recognition is commonly performed by visual inspection by a trained person. An alternative method for visual inspection is automated pollen analysis based on the image analysis technique. Image analysis transfers visual information to mathematical descriptions. In this work, the suitability of three microscopic techniques for automatic analysis of pollen grains was studied. 2D and 3D morphological characteristics, textural and colour features, and extended depth of focus characteristics were used for the pollen discrimination. In this study, 7 botanical taxa and a total of 2482 pollen grains were evaluated. The highest correct classification rate of 93.05% was achieved using the phase contrast microscopy, followed by the dark field microscopy reaching 91.02%, and finally by the light field microscopy reaching 88.88%. The most significant discriminant characteristics were morphological (2D and 3D) and colour characteristics. Our results confirm the potential of using automatic pollen analysis to discriminate pollen taxa in honey. This work provides the basis for further research where the taxa dataset will be increased, and new descriptors will be studied.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
21101 - Food and beverages

Project
<a href="/en/project/QK1920344" target="_blank" >QK1920344: Assessment of honey authenticity by pollen grain analysis.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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