Preliminary Research on the Possibility of Automating the Identification of Pollen Grains in Melissopalynology Using AI, with Particular Emphasis on Computer Image Analysis Methods.

Kacper Litwińczyk, Michał Podralski, Paulina Skorynko, Ewa Malinowska, Zuzanna Czarnota, Beata Bąk, Artur Janowski

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Kacper LitwińczykDepartment of Geodesy, Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland.

Michał PodralskiDepartment of Geodesy, Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland.

Paulina SkorynkoDepartment of Poultry Science and Apiculture, Faculty of Animal Bioengineering, University of Warmia and Mazury in Olsztyn, Sloneczna 48, 10-957 Olsztyn, Poland.

Ewa MalinowskaDepartment of Poultry Science and Apiculture, Faculty of Animal Bioengineering, University of Warmia and Mazury in Olsztyn, Sloneczna 48, 10-957 Olsztyn, Poland.ORCID 0009-0006-8175-5115

Zuzanna CzarnotaDepartment of Poultry Science and Apiculture, Faculty of Animal Bioengineering, University of Warmia and Mazury in Olsztyn, Sloneczna 48, 10-957 Olsztyn, Poland.

Beata BąkDepartment of Poultry Science and Apiculture, Faculty of Animal Bioengineering, University of Warmia and Mazury in Olsztyn, Sloneczna 48, 10-957 Olsztyn, Poland.

Artur JanowskiDepartment of Geodesy, Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland.ORCID 0000-0002-5535-408X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melissopalynological analysis is essential for determining the botanical origin of honey, corbicular pollen and bee bread, as well as detecting adulteration. However, it traditionally relies on labor-intensive and subjective manual pollen identification. As a proof-of-concept preceding full honey analysis, this study evaluates artificial intelligence methods for automated pollen grain recognition under controlled conditions. Hazel (

Indexed as

Artificial IntelligenceHoneyImage Processing, Computer-AssistedPollenAlgorithmsBeesCorylusDetection AlgorithmsTaraxacumbee pollencomputer image analysisdeep learningDINOv3identification of type of honeymelissopalinologyneural networksYOLOv12m

Identifiers

PMID41977828

DOI10.3390/s26072043

PMCPMC13074883

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.