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Article

Development of an Image Analysis Pipeline to Estimate Sphagnum Colony Density in the Field

1
National Plant Phenomics Centre, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3EB, UK
2
Faculty of Electrical Engineering, Mathematics and Computer Science, Technical University Delft, 2628 XE Delft, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editor: Vítězslav Plášek
Plants 2021, 10(5), 840; https://doi.org/10.3390/plants10050840
Received: 22 February 2021 / Revised: 15 April 2021 / Accepted: 19 April 2021 / Published: 22 April 2021
(This article belongs to the Special Issue New Knowledge in Bryology)
Sphagnum peatmosses play an important part in water table management of many peatland ecosystems. Keeping the ecosystem saturated, they slow the breakdown of organic matter and release of greenhouse gases, facilitating peatland’s function as a carbon sink rather than a carbon source. Although peatland monitoring and restoration programs have increased recently, there are few tools to quantify traits that Sphagnum species display in their ecosystems. Colony density is often described as an important determinant in the establishment and performance in Sphagnum but detailed evidence for this is limited. In this study, we describe an image analysis pipeline that accurately annotates Sphagnum capitula and estimates plant density using open access computer vision packages. The pipeline was validated using images of different Sphagnum species growing in different habitats, taken on different days and with different smartphones. The developed pipeline achieves high accuracy scores, and we demonstrate its utility by estimating colony densities in the field and detecting intra and inter-specific colony densities and their relationship with habitat. This tool will enable ecologists and conservationists to rapidly acquire accurate estimates of Sphagnum density in the field without the need of specialised equipment. View Full-Text
Keywords: Sphagnum; peatmoss; capitula density; image analysis; computer vision Sphagnum; peatmoss; capitula density; image analysis; computer vision
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MDPI and ACS Style

van de Koot, W.Q.M.; van Vliet, L.J.J.; Chen, W.; Doonan, J.H.; Nibau, C. Development of an Image Analysis Pipeline to Estimate Sphagnum Colony Density in the Field. Plants 2021, 10, 840. https://doi.org/10.3390/plants10050840

AMA Style

van de Koot WQM, van Vliet LJJ, Chen W, Doonan JH, Nibau C. Development of an Image Analysis Pipeline to Estimate Sphagnum Colony Density in the Field. Plants. 2021; 10(5):840. https://doi.org/10.3390/plants10050840

Chicago/Turabian Style

van de Koot, Willem Q.M., Larissa J.J. van Vliet, Weilun Chen, John H. Doonan, and Candida Nibau. 2021. "Development of an Image Analysis Pipeline to Estimate Sphagnum Colony Density in the Field" Plants 10, no. 5: 840. https://doi.org/10.3390/plants10050840

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