Abstract Bee pollen is a natural matrix widely studied in its nutritional and bioactive compounds, including carotenoids. That composition is usually identified by Rapid Resolution Liquid Chromatography (RRLC) coupled to UV–Vis spectrophotometry, an expensive method that requires complex sample preparation and long analysis time. In this work, a correlation between colorimetric coordinates and carotenoid composition was evaluated. Through Digital Image Analysis (DIA) by DigiEye, the color characteristics were determined, and carotenoids profile was done by RRLC. The correlations were made by multiple linear regression (MLR). From 12 carotenoids found in the samples, six had a coefficient R2 > 0.75 between reference and predict value. Heterogeneous mixtures of bee pollen samples were analyzed, and the suitability of the mathematical models could be corroborated because the relative error for most of the compounds was less than 20%. It has been demonstrated that union of Tristimulus Colorimetry and Image Analysis represent an effective tool to estimate the chemical composition in food industry.

中文翻译：

---

通过先进的数字图像分析测定蜂花粉的类胡萝卜素谱

摘要 蜂花粉是一种天然基质，在其营养和生物活性化合物（包括类胡萝卜素）方面得到广泛研究。该成分通常通过快速分离液相色谱 (RRLC) 与紫外-可见分光光度法相结合进行鉴定，这是一种昂贵的方法，需要复杂的样品制备和较长的分析时间。在这项工作中，评估了比色坐标和类胡萝卜素组成之间的相关性。通过 DigiEye 的数字图像分析 (DIA)，确定颜色特征，并通过 RRLC 完成类胡萝卜素分布。相关性是通过多元线性回归 (MLR) 得出的。在样品中发现的 12 种类胡萝卜素中，有 6 种在参考值和预测值之间的系数 R2 > 0.75。分析了蜂花粉样品的异质混合物，并且可以证实数学模型的适用性，因为大多数化合物的相对误差小于 20%。已经证明，三色比色法和图像分析的结合是估计食品工业化学成分的有效工具。