| Title: |
Automated calculation of spectral-reflectance marker-points to enable analysis of plant colour-signalling to pollinators |
| Authors: |
Alan Dorin, Mani Shrestha, Matthieu Herrmann, Martin Burd, Adrian G. Dyer |
| Source: |
MethodsX, Vol 7, Iss , Pp 100827- (2020) |
| Publisher Information: |
Elsevier, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Science |
| Subject Terms: |
Pollinator vision, Marker-point, Spectral-reflectance, Flower colour, Science |
| More Details: |
A spectral reflectance curve for a coloured surface can be constructed from a set of radiation reflectance value measurements made across the spectrum at discrete wavelengths. The curve gives an indication of the pattern of light entering the eye of an organism viewing an illuminated object. Marker points represent the positions along a reflectance curve at which sharp transitions in reflectance occur, these being potentially important to visual perception, for instance by insects discriminating between two flowers, each of a different colour. Consequently, methods of marker point analysis have been applied in several studies evaluating flower colours. These studies have sometimes required researchers to place marker points on reflectance curves by eye, or they have used algorithms written as unreleased software. To automate the process systematically and provide open access, we implemented special-purpose software in C++. Below we provide a summary of the approach adopted in our implementation and made available online in a port to TypeScript. The main benefits of our method are summarized as being: • Automation and repeatability. • Standardisation, cross-platform compatibility and Open Access. • Interactive exploration of the effects of parameter variation. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2215-0161 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2215016120300479; https://doaj.org/toc/2215-0161 |
| DOI: |
10.1016/j.mex.2020.100827 |
| Access URL: |
https://doaj.org/article/c04589ec9b314d4abf54cbe2293ed93f |
| Accession Number: |
edsdoj.04589ec9b314d4abf54cbe2293ed93f |
| Database: |
Directory of Open Access Journals |
