Abstract
Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer‐level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content‐chroma ratio, anthocyanin content‐chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root‐mean‐square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.
Highlights
Apart from chlorophylls, anthocyanins are one of the main pigments conferring color in plants, being almost ubiquitous among angiosperms (Tanaka, Sasaki, & Ohmiya, 2008)
We focused on flower parts containing anthocyanin pigments; we analyzed petals for all species except for B. officinalis and S. littorea for which we collect pedicels and calyces, respectively (Figure 1)
The relationship between anthocyanin concentration estimated with the biochemical method and H, Hue-segment classification (HSC), and B calculated from spectral reflectance data was weak or nonsignificant for most species and tissues, except for B. officinalis pedicels and S. littorea calyces, with a moderate-high coefficient of determination (Table 4)
Summary
Apart from chlorophylls, anthocyanins are one of the main pigments conferring color in plants, being almost ubiquitous among angiosperms (Tanaka, Sasaki, & Ohmiya, 2008). There have been several intriguing applications of digital photography to study plant and animal coloration, such as assessment of color change, pigment patterns, and camouflage (Akkaynak et al, 2014; Gómez & Liñán-Cembrano, 2016; Stevens et al, 2014; Strauss & Cacho, 2013; Taylor, Gilbert, & Reader, 2013) In spite of these advantages, the use of digital images to faithfully quantify color variation in plants is in its infancy. UV reflectance may occur in the flowers of some plant species (Glover, 2007; Koski & Ashman, 2016), this is primarily caused by other flavonoids such as flavones, flavonols, and flavanones (Merken & Beecher, 2000) These nonanthocyanin flavonoids do not absorb in the visible region; they not interfere in the anthocyanin estimates can acts as co-pigments. To estimate anthocyanin concentration, we focus on the use of digital images to capture data from the visible region of the spectrum
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