Visualization as a modern tool supporting statistical analyses in plant protection

Jan Bocianowski

jan.bocianowski@up.poznan.pl
Katedra Metod Matematycznych i Statystyczny, Uniwersytet Przyrodniczy w Poznaniu (Poland)
https://orcid.org/0000-0002-0102-0084

Abstract

The paper discusses the importance of graphical presentation of experimental results in plant protection, with particular emphasis on its role in the analysis, interpretation, and communication of scientific findings. It was indicated that plant protection experiments generate complex and multidimensional data concerning the effectiveness of chemical, biological, and integrated protection methods, and that their clear presentation is essential for both agricultural practice and scientific communication. The study presents the most commonly used methods of data visualization, including bar charts, line graphs, scatter plots, box plots, and phytosanitary risk maps, highlighting their significance in evaluating the effectiveness of protection treatments, the dynamics of biological processes, and the relationships between environmental and technological factors. The main advantages of graphical data presentation were discussed, including facilitation of data interpretation, rapid comparison of experimental objects, support for statistical analysis, and improvement of the clarity and attractiveness of scientific publications. Attention was also paid to the growing importance of spatial visualization in the context of precision agriculture and phytosanitary threat monitoring. At the same time, the study points out the limitations and potential risks associated with the improper use of graphical methods, such as oversimplification of data, manipulation through scale selection, limited precision of numerical information, and difficulties in presenting multifactorial data. It was emphasized that properly prepared data visualization should complement, rather than replace, statistical and descriptive analysis. In conclusion, it was stated that the importance of graphical presentation of results in plant protection will continue to increase along with the development of modern research methods and precision agriculture.


Keywords:

plant protection, data visualization, graphical presentation, phytosanitary risk maps, precision agriculture, scientific communication

Cleveland W.S. 1993. Visualizing data. Hobart Press, Summit, NJ, USA.
Google Scholar

Cleveland W.S. 1994. The elements of graphing data. 2nd ed., Hobart, 1994.
Google Scholar

Cleveland W.S., McGill R. 1984. Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79, 387, 531–554. https://doi.org/10.1080/01621459.1984.10478080
Google Scholar

Danielewicz J., Horoszkiewicz J., Jajor E., Korbas M., Bocianowski J., Nowaczyk K. 2023. Podatność odmian owsa (Avena sativa L.) na porażenie przez Drechslera avenae (helmintosporioza owsa) i jej wpływ na plon. Progress in Plant Protection, 63, 3, 173–180. DOI:10.14199/ppp-2023-019
Google Scholar

Erlichowski T. 2025. Wpływ warunków sezonowych na dynamikę, liczebność populacji mszyc oraz presję infekcyjną wirusów na plantacjach ziemniaka w wybranych lokalizacjach w 2025 roku. Ziemniak Polski, 35, 4, p. 43
Google Scholar

Friedman A., Rahman M., Dinh L., Rosen P. 2026. Designing for Engagement: A Comparison of Canvas and a Visual Peer Review Dashboard. ACM Transactions on Computing Education, 26, 3, 54. https://doi.org/10.1145/380096
Google Scholar

Gazdecki M., Beba P., Goryńska-Goldmann E., Wiza-Augustyniak P. 2025. Postrzeganie i ocena biologicznych środków ochrony roślin przez rolników w Polsce. Zagadnienia Doradztwa Rolniczego, 120, 2, 95–115.
Google Scholar

Horoszkiewicz J., Bocianowski J., Danielewicz J., Jajor E., Korbas M., Mikos-Szymańska M., Podleśny M., Świerczyńska I. 2026. The Impact of Plant Extracts and Fermentation Products on the Growth of Mycelium of Selected Fungi Examined by the Additive Main Effects and a Multiplicative Interaction Model. Agronomy, 16, 9, 871. https://doi.org/10.3390/agronomy16090871
Google Scholar

Huff D. 2023. How to lie with statistics. Penguin UK.
Google Scholar

Hulme P. 2024. Thematic mapping of biosecurity highlights divergent conceptual foundations in human, animal, plant and ecosystem health. NeoBiota, 95, 221–239. DOI:10.3897/neobiota.95.130178
Google Scholar

Jambor H., Antonietti A., Alicea B., Audisio T.L., Auer S., Bhardwaj V., Burgess S.J., Ferling I., Gazda M.A., Hoeppner L.H., Ilangovan V., Lo H., Olson M., Mohamed S.Y., Sarabipour S., Varma A., Walavalkar K., Wissink E.M., Weissgerber T.J. 2021. Creating clear and informative image-based figures for scientific publications. PLoS Biology, 19, 3, e3001161. https://doi.org/10.1371/journal.pbio.3001161
Google Scholar

Jambor H.K. 2025. A checklist for designing and improving the visualization of scientific data. Nature Cell Biology, 27, 879–883. https://doi.org/10.1038/s41556-025-01684-z
Google Scholar

Jop B., Marczewska-Kolasa K., Abdallah I., Bocianowski J., Synowiec A. 2026. Temperature effects on germination indices in herbicide-resistant and susceptible silky bentgrass (Apera spica-venti) populations. Progress in Plant Protection, 66, 1, 5–15. DOI:10.14199/ppp-2026-001
Google Scholar

Kelleher C., Wagener T. 2011. Ten Guidelines for Effective Data Visualization in Scientific Publications. Environmental Modelling & Software, 26, 6, 822–827. https://doi.org/10.1016/j.envsoft.2010.12.006
Google Scholar

Kończak G. (2024). Wizualizacja wyników badań naukowych. Wydawnictwo Uniwersytetu Ekonomicznego w Katowicach. doi.org/10.22367/uekat.9788378759010
Google Scholar

Kowalska J., Krzymińska J., Łukaszyk J. 2024. Przegląd aktualnych narzędzi internetowych wspierających ochronę roślin oraz wybranych badań w rolnictwie ekologicznym w Polsce. Progress in Plant Protection, 64, 3, 117–126. DOI:10.14199/ppp-2024-011
Google Scholar

Kozak M. 2010. Basic principles of graphing data. Scientia Agricola, 67, 4, 483–494. https://doi.org/10.1590/S0103-90162010000400017
Google Scholar

Lin M., Huang Q., Deng Z., Schreck T., Cai Y. 2026. DensityBars: A Space-Efficient Visualization for Event Temporal Distribution. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 408, 1–17. https://doi.org/10.1145/3772318.3791169
Google Scholar

Micek J. 2025. Monitoring chorób i szkodników w uprawie roślin. Jak działa system Farm Smart? Agro Smart Lab. https://agrosmartlab.pl/blog/monitoring-chorob-i-szkodnikow-w-uprawie-roslin-jak-dziala-system-farm-smart/
Google Scholar

Midway S.R. 2020. Principles of Effective Data Visualization. Patterns (N Y), 1, 9, 100141. DOI:10.1016/j.patter.2020.100141
Google Scholar

Musiał K. 2025. Przemiany strukturalne w rolnictwie i ich potencjalne następstwa w sferze podtrzymania usług ekosystemowych. Przykład obszarów cennych przyrodniczo w województwie pomorskim. Annals of the Polish Association of Agricultural & Agribusiness Economists, 27, 4, 114–127. DOI:10.5604/01.3001.0055.4387
Google Scholar

Mühl D.D., De Oliveira L. 2022. A bibliometric and thematic approach to agriculture 4.0. Heliyon, 8, 5, e09369. https://doi.org/10.1016/j.heliyon.2022.e09369
Google Scholar

Piesik D., Krasińska A., Twardowski J., Krawczyk K., Bocianowski J., Buszewski B., Wejnerowska G., Narloch I., Mayhew C.A. 2026. An investigation of the major volatile organic compounds released by maize plants following the application of methyl jasmonate and Z-jasmone. Journal of Plant Physiology, 320, 154763. https://doi.org/10.1016/j.jplph.2026.154763
Google Scholar

Rakuschek J., Hauser H., Schreck T. 2026. Guided spiral visualization for periodic time series and residual analysis. Computers and Graphics, 135, C. https://doi.org/10.1016/j.cag.2026.104535
Google Scholar

Rougier N.P., Droettboom M., Bourne P.E. 2014. Ten Simple Rules for Better Figures. PLoS Computational Biology, 10, 9, e1003833. https://doi.org/10.1371/journal.pcbi.1003833
Google Scholar

Rys M., Jurczyk B., Pociecha E., Curci P.L., Bocianowski J., Szaleniec M., Waligórski P., Janeczko A. 2026. Climate change-related deacclimation disrupts sugar allocation and transport in winter oilseed rape (Brassica napus L.). Environmental and Experimental Botany, 243, 106332. https://doi.org/10.1016/j.envexpbot.2026.106332
Google Scholar

Tufte E.R. 1997. Visual explanations: Images and quantities, evidence and narrative. Graphics Press.
Google Scholar

Tukey J.W. 1977. Exploratory data analysis (Vol. 2, pp. 131–160). Reading, MA: Addison-Wesley.
Google Scholar

Tukey J.W. 1993. Exploratory data analysis: past, present and future (No. ARO2699710MA).
Google Scholar


Published
2026-08-18

Cited by

Bocianowski, J. (2026) “Visualization as a modern tool supporting statistical analyses in plant protection”, Bulletin of Plant Breeding and Acclimatization Institute. doi: 10.37317/biul-2026-0002.

Authors

Jan Bocianowski 
jan.bocianowski@up.poznan.pl
Katedra Metod Matematycznych i Statystyczny, Uniwersytet Przyrodniczy w Poznaniu Poland
https://orcid.org/0000-0002-0102-0084

Statistics

Abstract views: 33
PDF downloads: 10


License

Copyright (c) 2026 Jan Bocianowski

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Upon submitting the article, the Authors grant the Publisher a non-exclusive and free license to use the article for an indefinite period of time throughout the world in the following fields of use:

  1. Production and reproduction of copies of the article using a specific technique, including printing and digital technology.
  2. Placing on the market, lending or renting the original or copies of the article.
  3. Public performance, exhibition, display, reproduction, broadcasting and re-broadcasting, as well as making the article publicly available in such a way that everyone can access it at a place and time of their choice.
  4. Including the article in a collective work.
  5. Uploading an article in electronic form to electronic platforms or otherwise introducing an article in electronic form to the Internet or other network.
  6. Dissemination of the article in electronic form on the Internet or other network, in collective work as well as independently.
  7. Making the article available in an electronic version in such a way that everyone can access it at a place and time of their choice, in particular via the Internet.

Authors by sending a request for publication:

  1. They consent to the publication of the article in the journal,
  2. They agree to give the publication a DOI (Digital Object Identifier),
  3. They undertake to comply with the publishing house's code of ethics in accordance with the guidelines of the Committee on Publication Ethics (COPE), (http://ihar.edu.pl/biblioteka_i_wydawnictwa.php),
  4. They consent to the articles being made available in electronic form under the CC BY-SA 4.0 license, in open access,
  5. They agree to send article metadata to commercial and non-commercial journal indexing databases.

Most read articles by the same author(s)

1 2 3 4 5 > >>