DiasMorph: a dataset of morphological traits and images of Central European diaspores
We present DiasMorph , a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores agains...
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| Published in | Scientific data Vol. 11; no. 1; pp. 781 - 8 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
16.07.2024
Nature Publishing Group Nature Portfolio |
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| Abstract | We present
DiasMorph
, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. |
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| AbstractList | We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications.We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. Abstract We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. We present DiasMorph , a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. |
| ArticleNumber | 781 |
| Author | Ott, Tankred Begemann, Lina Poschlod, Peter Dayrell, Roberta L. C. |
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| References | HintzeCD3: The Dispersal and Diaspore Database - Baseline data and statistics on seed dispersalPerspect Plant Ecol Evol Syst20131518019210.1016/j.ppees.2013.02.001 LinLI-KA Concordance Correlation Coefficient to Evaluate ReproducibilityBiometrics1989452552681:STN:280:DyaL1M3kslKrtg%3D%3D10.2307/25320512720055 OttTTankredO/traitor: 0.1.0202310.5281/zenodo.7876319Zenodo Brouwer, W. & Stählin, A. Handbuch Der Samenkunde Für Landwirtschaft, Gartenbau Und Forstwirtschaft. (DLG-Verlag, Frankfurt, 1975). Cappers, R. T., Bekker, R. M. & Jans, J. E. Digitale Zadenatlas von Nederland. 2nd ed. (Barkhuis Publishing & Groningen University Library, Groningen, 2012). Beijerinck, W. Zadenatlas Der Nederlandsche Flora. (Backhuys & Meesters, Amsterdam, 1976). Society for Ecological Restoration, International Network for Seed Based Restoration and Royal Botanic Gardens Kew. Seed Information Database (SID). https://ser-sid.org/ (2023). SaatkampAA research agenda for seed-trait functional ecologyNew Phytologist20192211764177510.1111/nph.1550230269352 Martin, A. C. & Barkley, W. D. Seed Identification Manual. (University of California Press, Berkeley and Los Angeles, 1961). Bojňanský, V. & Fargašová, A. Atlas of Seeds and Fruits of Central and East-European Flora. (Springer Netherlands, Dordrecht, 2007). Römermann, C., Tackenberg, O., Götzenberg, L. & Poschlod, P. Morphology dispersal unit. in The LEDA Traitbase Collecting and Measuring Standards (eds. Knevel, I. C., Bekker, R. M., Kunzmann, D., Stadler, M. & Thompson, K.) 112–118 (Groningen University, Groningen, 2005). GEVES. I.D.SEED®. https://mediatheque.geves.fr/geves/identification (2022). DayrellRLCOttTHorrocksTPoschlodPAutomated extraction of seed morphological traits from imagesMethods Ecol Evol2023141708171810.1111/2041-210X.14127 DayrellRLCBegemannLOttTPoschlodPDiasMorph: a dataset of morphological traits and images of Central European diaspores202410.6084/m9.figshare.21206507.v5figshare KleyerMThe LEDA Traitbase: a database of life-history traits of the Northwest European floraJournal of Ecology2008961266127410.1111/j.1365-2745.2008.01430.x KindtRWorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone dataAppl Plant Sci2020810.1002/aps3.11388330146327526431 Signorell, A. & et mult. al. DescTools: tools for descriptive statistics. R package version 0.99.47. (2022). Sweedman, L. & Merritt, D. Australian Seeds: A Guide to Their Collection, Identification and Biology. (CSIRO Publishing, Melbourne, 2006). Lürig, M. D., Donoughe, S., Svensson, E. I., Porto, A. & Tsuboi, M. Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology. Front Ecol Evol9, 642774 (2021). BorowiecMLDeep learning as a tool for ecology and evolutionMethods Ecol Evol2022131640166010.1111/2041-210X.13901 LoddoAAn effective and friendly tool for seed image analysisVis Comput20233933535210.1007/s00371-021-02333-w Buttler, K. P., May, R. & Metzing, D. Liste der Gefäßpflanzen Deutschlands - Florensynopse und Synonyme. (Bundesamt für Naturschutz, Bonn, 2018). HorrocksTAutomated extraction of seed morphological traits from images202310.5281/zenodo.7877540Zenodo 3607_CR10 R Kindt (3607_CR18) 2020; 8 3607_CR21 3607_CR12 3607_CR1 3607_CR11 3607_CR3 3607_CR13 C Hintze (3607_CR9) 2013; 15 3607_CR17 RLC Dayrell (3607_CR19) 2024 LI-K Lin (3607_CR20) 1989; 45 3607_CR4 3607_CR5 3607_CR6 3607_CR7 A Loddo (3607_CR15) 2023; 39 T Horrocks (3607_CR22) 2023 RLC Dayrell (3607_CR16) 2023; 14 T Ott (3607_CR23) 2023 ML Borowiec (3607_CR14) 2022; 13 A Saatkamp (3607_CR2) 2019; 221 M Kleyer (3607_CR8) 2008; 96 |
| References_xml | – reference: SaatkampAA research agenda for seed-trait functional ecologyNew Phytologist20192211764177510.1111/nph.1550230269352 – reference: Römermann, C., Tackenberg, O., Götzenberg, L. & Poschlod, P. Morphology dispersal unit. in The LEDA Traitbase Collecting and Measuring Standards (eds. Knevel, I. C., Bekker, R. M., Kunzmann, D., Stadler, M. & Thompson, K.) 112–118 (Groningen University, Groningen, 2005). – reference: BorowiecMLDeep learning as a tool for ecology and evolutionMethods Ecol Evol2022131640166010.1111/2041-210X.13901 – reference: HorrocksTAutomated extraction of seed morphological traits from images202310.5281/zenodo.7877540Zenodo – reference: Bojňanský, V. & Fargašová, A. Atlas of Seeds and Fruits of Central and East-European Flora. (Springer Netherlands, Dordrecht, 2007). – reference: LoddoAAn effective and friendly tool for seed image analysisVis Comput20233933535210.1007/s00371-021-02333-w – reference: Brouwer, W. & Stählin, A. Handbuch Der Samenkunde Für Landwirtschaft, Gartenbau Und Forstwirtschaft. (DLG-Verlag, Frankfurt, 1975). – reference: Buttler, K. P., May, R. & Metzing, D. Liste der Gefäßpflanzen Deutschlands - Florensynopse und Synonyme. (Bundesamt für Naturschutz, Bonn, 2018). – reference: KleyerMThe LEDA Traitbase: a database of life-history traits of the Northwest European floraJournal of Ecology2008961266127410.1111/j.1365-2745.2008.01430.x – reference: Signorell, A. & et mult. al. DescTools: tools for descriptive statistics. R package version 0.99.47. (2022). – reference: Cappers, R. T., Bekker, R. M. & Jans, J. E. Digitale Zadenatlas von Nederland. 2nd ed. (Barkhuis Publishing & Groningen University Library, Groningen, 2012). – reference: HintzeCD3: The Dispersal and Diaspore Database - Baseline data and statistics on seed dispersalPerspect Plant Ecol Evol Syst20131518019210.1016/j.ppees.2013.02.001 – reference: DayrellRLCBegemannLOttTPoschlodPDiasMorph: a dataset of morphological traits and images of Central European diaspores202410.6084/m9.figshare.21206507.v5figshare – reference: Sweedman, L. & Merritt, D. Australian Seeds: A Guide to Their Collection, Identification and Biology. (CSIRO Publishing, Melbourne, 2006). – reference: LinLI-KA Concordance Correlation Coefficient to Evaluate ReproducibilityBiometrics1989452552681:STN:280:DyaL1M3kslKrtg%3D%3D10.2307/25320512720055 – reference: GEVES. I.D.SEED®. https://mediatheque.geves.fr/geves/identification (2022). – reference: DayrellRLCOttTHorrocksTPoschlodPAutomated extraction of seed morphological traits from imagesMethods Ecol Evol2023141708171810.1111/2041-210X.14127 – reference: Beijerinck, W. Zadenatlas Der Nederlandsche Flora. (Backhuys & Meesters, Amsterdam, 1976). – reference: Society for Ecological Restoration, International Network for Seed Based Restoration and Royal Botanic Gardens Kew. Seed Information Database (SID). https://ser-sid.org/ (2023). – reference: KindtRWorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone dataAppl Plant Sci2020810.1002/aps3.11388330146327526431 – reference: Martin, A. C. & Barkley, W. D. Seed Identification Manual. (University of California Press, Berkeley and Los Angeles, 1961). – reference: Lürig, M. D., Donoughe, S., Svensson, E. I., Porto, A. & Tsuboi, M. Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology. Front Ecol Evol9, 642774 (2021). – reference: OttTTankredO/traitor: 0.1.0202310.5281/zenodo.7876319Zenodo – ident: 3607_CR17 – volume: 14 start-page: 1708 year: 2023 ident: 3607_CR16 publication-title: Methods Ecol Evol doi: 10.1111/2041-210X.14127 – ident: 3607_CR21 – ident: 3607_CR4 – year: 2023 ident: 3607_CR23 doi: 10.5281/zenodo.7876319 – ident: 3607_CR5 – volume: 15 start-page: 180 year: 2013 ident: 3607_CR9 publication-title: Perspect Plant Ecol Evol Syst doi: 10.1016/j.ppees.2013.02.001 – year: 2024 ident: 3607_CR19 doi: 10.6084/m9.figshare.21206507.v5 – volume: 96 start-page: 1266 year: 2008 ident: 3607_CR8 publication-title: Journal of Ecology doi: 10.1111/j.1365-2745.2008.01430.x – ident: 3607_CR7 – ident: 3607_CR10 – volume: 39 start-page: 335 year: 2023 ident: 3607_CR15 publication-title: Vis Comput doi: 10.1007/s00371-021-02333-w – volume: 8 year: 2020 ident: 3607_CR18 publication-title: Appl Plant Sci doi: 10.1002/aps3.11388 – ident: 3607_CR3 doi: 10.1071/9780643094079 – ident: 3607_CR11 – ident: 3607_CR13 doi: 10.3389/fevo.2021.642774 – volume: 221 start-page: 1764 year: 2019 ident: 3607_CR2 publication-title: New Phytologist doi: 10.1111/nph.15502 – ident: 3607_CR12 – volume: 13 start-page: 1640 year: 2022 ident: 3607_CR14 publication-title: Methods Ecol Evol doi: 10.1111/2041-210X.13901 – year: 2023 ident: 3607_CR22 doi: 10.5281/zenodo.7877540 – volume: 45 start-page: 255 year: 1989 ident: 3607_CR20 publication-title: Biometrics doi: 10.2307/2532051 – ident: 3607_CR1 doi: 10.1525/9780520318724 – ident: 3607_CR6 doi: 10.1163/9789004629790 |
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DiasMorph
, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214... We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records.... Abstract We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214... |
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| Title | DiasMorph: a dataset of morphological traits and images of Central European diaspores |
| URI | https://link.springer.com/article/10.1038/s41597-024-03607-3 https://www.ncbi.nlm.nih.gov/pubmed/39013933 https://www.proquest.com/docview/3081477930 https://www.proquest.com/docview/3081774409 https://pubmed.ncbi.nlm.nih.gov/PMC11252285 https://doaj.org/article/30431929dfad45128702566e9e79db4c |
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