Image-based RGB and CIELAB colour analysis of 16 carrot varieties with pigment quantification via HPLC and spectrophotometry

This dataset supports a study on the use of image-based colorimetric analysis for predicting carotenoid and anthocyanin content in carrots. The CIELAB/Ch colour space, derived from digital images, offers a non-destructive and accessible method for pigment estimation. This dataset reports the RGB and CIELAB/Ch values found in 16 carrot varieties of different genotypic colour diversity (i.e., white, yellow, orange, red, purple). Samples were photographed under six light conditions (WF -1, WF 0, WF +1, PF 0, PF +1, PF +2), with colour calibration applied prior to analysing CIELAB/Ch parameters.
Pigment content was quantified using spectrophotometry (total carotenoids and anthocyanins) and high-performance liquid chromatography (individual carotenoids).

本数据集为一项基于图像比色分析法预测胡萝卜类胡萝卜素与花青素含量的研究提供数据支撑。源自数字图像的CIELAB/Ch颜色空间，为色素含量估算提供了一种无损且便捷可行的检测方法。本数据集收录了16个具备不同基因型色泽多样性（涵盖白色、黄色、橙色、红色、紫色）的胡萝卜品种的RGB与CIELAB/Ch颜色参数值。所有样本均在6种光照条件（WF -1、WF 0、WF +1、PF 0、PF +1、PF +2）下完成拍摄，并在开展CIELAB/Ch参数分析前预先完成颜色校准。色素含量分别通过分光光度法（测定总类胡萝卜素与总花青素含量）以及高效液相色谱法（测定单体类胡萝卜素含量）进行定量检测。