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Data and original code for: A generalized approach to characterise optical properties of natural objects

Cite this dataset

Ospina-Rozo, Laura; Roberts, Ann; Stuart-Fox, Devi (2022). Data and original code for: A generalized approach to characterise optical properties of natural objects [Dataset]. Dryad. https://doi.org/10.5061/dryad.2v6wwpznp

Abstract

To understand the diversity of ways in which natural materials interact with light, it is important to consider how their reflectance changes with the angle of illumination or viewing and to consider wavelengths beyond the visible. We chose a set of existing measurements and parameters that are generalisable to any wavelength range and spectral shape and we highlight which subsets of measures are relevant to different biological questions. As a case study, we applied these measures to 30 species of Christmas beetles. Here we provide the raw spectral data of angle integrated and angle-dependent reflection by the beetle elytra. We also provide the original code used for our analysis and figures.

Methods

We provide angle-integrated and angle-resolved spectral data (Reflectance % per Wavelength nm) obtained with two spectrophotometers, the USB 2000+ (400-1000 nm) and NIRQuest (1000-2100 nm). 

The angle-integrated spectra (hemispherical reflectance) were taken with an integrating sphere with an inbuilt tungsten-halogen light source (400-2100 nm; ISP-REF; Ocean Optics Inc., Dunedin, FL, USA.) and 4 mm diameter sampling port. The integrating sphere was connected to the two spectrometers via a bifurcated optic fibre. The angle-resolved spectral data was obtained by coupling the two spectrometers obtained with a goniometer measure the light reflectance in different combinations of angles of incident light and collector.

The reflectance per wavelength is reported as a % compared to a diffuse 99% reflectance spectralon standard (Labsphere, North Sutton, NH, USA). Measurements were recorded using the software OceanView 1.6.7. and analyzed with R programing language particularly the R package PAVO (Maia et al. 2019). In our manuscript we explain the process and rationale to calculate spectral parameters to describe different spectral shapes. In addition, we provide an RMarkDown file with the code to calculate these parameters for both visible and near infrared light.

Funding

Australian Research Council, Award: DP190102203

Australian Research Council, Award: FT180100216