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Arthropods dataset from different genetically modified maize events and associated controls
Arthropods from four genetically modified (GM) maize hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant+herbicide tolerant and coleopteran resistant and herbicide tolerant) and non-GM varieties were sampled during a two-year field assessment. A total numbe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819483/ https://www.ncbi.nlm.nih.gov/pubmed/29461517 http://dx.doi.org/10.1038/sdata.2018.19 |
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author | Pálinkás, Zoltán Zalai, Mihály Szénási, Ágnes Dorner, Zita Kiss, József North, Samuel Woodward, Guy Balog, Adalbert |
author_facet | Pálinkás, Zoltán Zalai, Mihály Szénási, Ágnes Dorner, Zita Kiss, József North, Samuel Woodward, Guy Balog, Adalbert |
author_sort | Pálinkás, Zoltán |
collection | PubMed |
description | Arthropods from four genetically modified (GM) maize hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant+herbicide tolerant and coleopteran resistant and herbicide tolerant) and non-GM varieties were sampled during a two-year field assessment. A total number of 363 555 arthropod individuals were collected. This represents the most comprehensive arthropod dataset from GM maize, and together with weed data, is reasonable to determine functional groups of arthropods and interactions between species. Trophic groups identified from both phytophagous and predatory arthropods were previously considered non-target organisms on which possible detrimental effects of Bacillus thuringiensis (Bt) toxins may have been directly (phytophagous species) or indirectly (predators) detected. The high number of individuals and species and their dynamics through the maize growing season can predict that interactions are highly correlational, and can thus be considered a useful tool to assess potential deleterious effects of Bt toxins on non-target organisms, serving to develop biosafety risk hypotheses for invertebrates exposed to GM maize plants. |
format | Online Article Text |
id | pubmed-5819483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-58194832018-03-05 Arthropods dataset from different genetically modified maize events and associated controls Pálinkás, Zoltán Zalai, Mihály Szénási, Ágnes Dorner, Zita Kiss, József North, Samuel Woodward, Guy Balog, Adalbert Sci Data Data Descriptor Arthropods from four genetically modified (GM) maize hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant+herbicide tolerant and coleopteran resistant and herbicide tolerant) and non-GM varieties were sampled during a two-year field assessment. A total number of 363 555 arthropod individuals were collected. This represents the most comprehensive arthropod dataset from GM maize, and together with weed data, is reasonable to determine functional groups of arthropods and interactions between species. Trophic groups identified from both phytophagous and predatory arthropods were previously considered non-target organisms on which possible detrimental effects of Bacillus thuringiensis (Bt) toxins may have been directly (phytophagous species) or indirectly (predators) detected. The high number of individuals and species and their dynamics through the maize growing season can predict that interactions are highly correlational, and can thus be considered a useful tool to assess potential deleterious effects of Bt toxins on non-target organisms, serving to develop biosafety risk hypotheses for invertebrates exposed to GM maize plants. Nature Publishing Group 2018-02-20 /pmc/articles/PMC5819483/ /pubmed/29461517 http://dx.doi.org/10.1038/sdata.2018.19 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Pálinkás, Zoltán Zalai, Mihály Szénási, Ágnes Dorner, Zita Kiss, József North, Samuel Woodward, Guy Balog, Adalbert Arthropods dataset from different genetically modified maize events and associated controls |
title | Arthropods dataset from different genetically modified maize events and associated controls |
title_full | Arthropods dataset from different genetically modified maize events and associated controls |
title_fullStr | Arthropods dataset from different genetically modified maize events and associated controls |
title_full_unstemmed | Arthropods dataset from different genetically modified maize events and associated controls |
title_short | Arthropods dataset from different genetically modified maize events and associated controls |
title_sort | arthropods dataset from different genetically modified maize events and associated controls |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819483/ https://www.ncbi.nlm.nih.gov/pubmed/29461517 http://dx.doi.org/10.1038/sdata.2018.19 |
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