A user-friendly software to accurately count and measure cysts from the parasitic nematode Heterodera glycines

dc.contributor.author Mejias, Joffrey
dc.contributor.author Kozlowski, Djampa K. L.
dc.contributor.author Goshon, Jackson
dc.contributor.author Maier, Thomas R.
dc.contributor.author Baum, Thomas
dc.contributor.department Plant Pathology, Entomology and Microbiology
dc.date.accessioned 2025-02-27T19:18:01Z
dc.date.available 2025-02-27T19:18:01Z
dc.date.issued 2025-02-06
dc.description.abstract The soybean-cyst nematode (SCN; Heterodera glycines) is one of the most destructive pests affecting soybean crops. Effective management of SCN is imperative for the sustainability of soybean agriculture. A promising approach to achieving this goal is the development and breeding of new resistant soybean varieties. Researchers and breeders typically employ exploratory methods such as Genome-Wide Association Studies or Quantitative Trait Loci mapping to identify genes linked to resistance. These methods depend on extensive phenotypic screening. The primary phenotypic measure for assessing SCN resistance is often the number of cysts that form on a plant’s root system. Manual counting hundreds of cysts on a given root system is not only laborious but also subject to variability due to individual assessor differences. Additionally, while measuring cyst size could provide valuable insights due to its correlation with cyst development, this aspect is frequently overlooked because it demands even more hands-on work. To address these challenges, we have created Nemacounter, an intuitive software designed to detect, count, and measure the size of cysts autonomously. Nemacounter boasts a user-friendly graphical interface, simplifying the process for users to obtain reliable results. It enhances productivity by delivering annotated images and compiling data into csv files for easy analysis and reporting.
dc.description.comments This article is published as Mejias, J., Kozlowski, D.K.L., Goshon, J. et al. A user-friendly software to accurately count and measure cysts from the parasitic nematode Heterodera glycines. Sci Rep 15, 4468 (2025). https://doi.org/10.1038/s41598-025-88289-6.
dc.description.sponsorship This publication contains work funded by the Iowa Agriculture and Home Economics Experiment Station, Ames, IA, supported by Hatch Act and State of Iowa funds and grants from the North Central Soybean Research Program (C00075686/C000838723).
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/EzR2Y85z
dc.language.iso en
dc.publisher Nature Research
dc.rights © The Author(s) 2025. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
dc.source.uri https://doi.org/10.1038/s41598-025-88289-6 *
dc.subject.disciplines DegreeDisciplines::Life Sciences::Plant Sciences::Plant Pathology
dc.subject.keywords Neural network
dc.subject.keywords YOLOv5
dc.subject.keywords Soybean cyst nematode
dc.subject.keywords Nemacounter
dc.title A user-friendly software to accurately count and measure cysts from the parasitic nematode Heterodera glycines
dc.type article
dspace.entity.type Publication
relation.isAuthorOfPublication ea8d53ba-1a8f-4f5c-9b4a-1ecbd67e2f43
relation.isOrgUnitOfPublication 159d7e06-88d7-4610-9153-9481a37fbc61
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