Pollen analysis using multispectral imaging flow cytometry and deep learning-Reference-Cited by-同舟云学术

Pollen analysis using multispectral imaging flow cytometry and deep learning

Published:2020-09-22 Issue:1 Volume:229 Page:593-606
ISSN:0028-646X
Container-title:New Phytologist
language:en
Short-container-title:New Phytol

Author:

Dunker Susanne¹²^ORCID,Motivans Elena²³⁴,Rakosy Demetra¹²^ORCID,Boho David⁵,Mäder Patrick⁵^ORCID,Hornick Thomas¹²^ORCID,Knight Tiffany M.²³⁴^ORCID

Affiliation:

1. Helmholtz‐Centre for Environmental Research – UFZ Permoserstraße 15 Leipzig04318Germany

2. German Centre for Integrative Biodiversity Research – iDiv Deutscher Platz 5a Leipzig04103Germany

3. Helmholtz‐Centre for Environmental Research – UFZ Am Kirchtor 1 Halle (Saale)06120Germany

4. Martin Luther University Halle‐Wittenberg Am Kirchtor 1 Halle (Saale)06108Germany

5. Software Engineering for Safety‐Critical Systems Group Technische Universität Ilmenau Ilmenau98693Germany

Funder

Helmholtz Association

Deutsche Forschungsgemeinschaft

Publisher

Wiley

Subject

Plant Science,Physiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/nph.16882

Reference90 articles.

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2. Easy determination of ploidy level in Arabidopsis thaliana plants by means of pollen size measurement

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4. Constructing more informative plant–pollinator networks: visitation and pollen deposition networks in a heathland plant community

5. Analysis of pollen loads in a wild bee community (Hymenoptera: Apidae) – a method for elucidating habitat use and foraging distances

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