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（Anthocyanin）色素已成为进化生态学的模式性状，因其常为植物带来适应性优势。传统上，花青素多通过生化方法定量，近年来也可采用光谱反射法进行测定。但这两类方法均需破坏性取样，且操作耗时费力，对微量样本的测定尤为困难。近年来数字摄影与图像处理技术的发展，使得该类方法成为野外色彩测量的首选方案。本研究采用数字图像作为快速、非侵入性手段，对存在色彩变异的植物个体间的相对花青素浓度进行估算。
2. 本研究使用消费级数码相机与免费图像处理工具箱，从数字图像中提取RGB（红绿蓝）值以生成色彩指数。我们选取了6个物种的花瓣、茎、花梗与花萼作为测试对象，这些物种含有不同类型的花青素色素，并呈现出多样的着色模式。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，对各色彩指数进行评估。为进行对照，我们还从光谱反射数据中计算了色彩指数，并检验其与花青素浓度的相关性。
3. 色彩指数的表现因色彩变异的本质不同而存在差异。无论是数字图像还是光谱反射数据，花青素含量-色度比（anthocyanin content-chroma ratio, ACCR）、基础花青素-色度（anthocyanin-chroma basic, ACCB）以及绿色强度（strength of green, S_green）指数均能最精准地估算花青素浓度。部分由数字图像与光谱反射数据推导得到的色彩指数，与生化测定的花青素浓度具有显著相关性，但在决定系数（R²）与归一化均方根误差方面，数字图像的估算效果优于光谱反射法。这一现象在花瓣具条纹的物种中尤为显著，但对于花萼具条纹的物种，两种方法与花青素浓度的相关性表现相当。
4. 采用数字图像技术为精准定量花组织与营养组织中的花青素浓度提供了新途径。该方法高效便捷、完全非侵入性，既可用于均匀着色样本，也可用于具图案着色的样本，且适用于任意规模的样品。