Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps

Šaulienė, Ingrida; Šukienė, Laura; Daunys, Gintautas; Valiulis, Gediminas; Vaitkevičius, Lukas; Matavulj, Predrag; Brdar, Sanja; Panic, Marko; Sikoparija, Branko; Clot, Bernard; Crouzy, Benoît; Sofiev, Mikhail

doi:https://doi.org/10.5194/amt-12-3435-2019

Articles | Volume 12, issue 6

https://doi.org/10.5194/amt-12-3435-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-12-3435-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 6

Research article

|

28 Jun 2019

Research article |

| 28 Jun 2019

Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps

Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev

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Final revised paper (published on 28 Jun 2019)
Supplement to the final revised paper
Preprint (discussion started on 21 Jan 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'General review', Anonymous Referee #2, 16 Feb 2019
- AC1: 'Authors response to reviewer’s comments', I. Sauliene, 01 Apr 2019
RC2: 'Reviewer 1', Anonymous Referee #3, 19 Feb 2019
- AC2: 'Authors response to reviewer’s comments', I. Sauliene, 01 Apr 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by I. Sauliene on behalf of the Authors (15 Apr 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (17 Apr 2019) by Vassilis Amiridis

RR by Anonymous Referee #4 (09 May 2019)

RR by Anonymous Referee #1 (22 May 2019)

ED: Publish as is (30 May 2019) by Vassilis Amiridis

AR by I. Sauliene on behalf of the Authors (07 Jun 2019) Manuscript

Short summary

The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.