Data from: Digital photography provides a fast, reliable and non-invasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues

1. Anthocyanin pigments have become a model trait for evolutionary ecology since 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 labour intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring colour in the wild. Here, we use digital images as a quick, non-invasive method to estimate relative anthocyanin concentration among plants exhibiting colour variation. 2. By using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate colour indices. We tested petals, stems, pedicels and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Colour indices were assessed by their correlation to biochemically determined anthocyanin concentration. For comparison, we also calculated colour indices from spectral reflectance and tested the correlation with anthocyanin concentration. 3. Indices perform differently depending on the nature of the colour variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio (ACCR), anthocyanin-chroma basic (ACCB) and strength of green (S green) indices. Some colour indices derived from digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration, but the estimates from digital images performed better than spectral reflectance in terms of 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. 4. Using digital images brings new opportunities to accurately quantify the anthocyanin concentration in both floral and vegetative tissues. This method is efficient, completely non-invasive, applicable to both uniform and patterned colour, and works with samples of any size.

1. 花青素类色素（Anthocyanin pigments）已成为进化生态学的模式性状，因其常为植物带来适应性益处。传统上，花青素类色素的定量多采用生化方法，近年来也开始使用光谱反射法（spectral reflectance）进行检测。然而这两种方法均需要破坏性取样，且劳动强度大，针对微小样本时更是颇具挑战。近年来数码摄影与图像处理技术的进步，使其成为野外色彩测量的首选方法。本研究采用数码图像作为快速、无创的检测手段，以估算存在色彩变异的植物个体间的相对花青素浓度。2. 本研究借助消费级数码相机与免费图像处理工具箱（image processing toolbox），从数码图像中提取RGB值（RGB values）以生成色彩指数（colour indices）。我们对六个物种的花瓣、茎、花梗及花萼进行了检测，这些样本含有不同类型的花青素类色素且呈现各异的着色模式。我们通过色彩指数与生化测定的花青素浓度之间的相关性来评估其性能。为便于对比，我们还从光谱反射法中计算了色彩指数，并测试其与花青素浓度的相关性。3. 色彩指数的性能取决于色彩变异的本质。无论是基于数码图像还是光谱反射法，表现最优的花青素浓度估算指标均为花青素含量-色度比（ACCR）、基础花青素-色度比（ACCB）以及绿色强度（S_green）指数。部分由数码图像与光谱反射法推导得到的色彩指数，与生化测定的花青素浓度存在显著相关性，但基于数码图像的估算结果在决定系数（R²）与归一化均方根误差（normalized root-mean-square error）方面均优于光谱反射法。这一优势在具有条纹花瓣的物种中尤为突出，但对于带有条纹花萼的样本，两种方法与花青素浓度的相关性表现相当。4. 采用数码图像技术为精准定量花组织与营养组织的花青素浓度提供了新途径。该方法高效便捷、完全无创，既适用于均匀着色样本也适用于带有图案的着色样本，且可用于任意尺寸的样本。