Classification of rose petal colors based on optical spectrum and pigment content analyses

文献类型： 外文期刊

第一作者： Wang, Hua

作者： Wang, Hua;Fan, Youwei;Yang, Yuan;Li, Maofu;Sun, Pei;Zhang, Xinzhu;Jin, Wanmei;Wang, Hua;Fan, Youwei;Yang, Yuan;Li, Maofu;Sun, Pei;Zhang, Xinzhu;Jin, Wanmei;Wang, Hua;Fan, Youwei;Li, Maofu;Sun, Pei;Zhang, Xinzhu;Jin, Wanmei;Yang, Yuan;Zhang, Hui;Xue, Zhen

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关键词： Flower color phenotype; Pigment contents; Optical spectrum; Classification; Correlation

期刊名称：HORTICULTURE ENVIRONMENT AND BIOTECHNOLOGY （ 影响因子：2.138； 五年影响因子：2.34 ）

ISSN： 2211-3452

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收录情况： SCI

摘要： Roses (Rosa sp.) are an important ornamental crop worldwide. Their colorful flowers mainly reflect an accumulation of anthocyanins and carotenoids. Developing a reliable method to classify rose petal color and identifying relationships between pigment contents and color space values may offer better evaluation criteria for rose varieties. In this study, we classified 60 rose varieties into three groups based on their color parameters, corresponding to red varieties, white and yellow varieties, and pink and dark pink varieties. We measured the total pigment contents and identified the underlying anthocyanins and carotenoids using both UV spectrophotometry and ultraperformance convergence chromatography coupled to mass spectrometry. Flower petals of white roses contained the lowest pigment levels, while those of yellow roses contained only carotenoids (40.65-244.42 mu g/g) and mainly in the form of beta-carotene and violaxanthin. The petals of pink and dark pink roses only accumulated anthocyanins (91.72-1703.93 mu g/g) and mainly as cyanidin 3,5-diglucoside and cyanidin 3-O-glucoside. The petals of red roses contained both large amounts of anthocyanins (1484.8-3806.22 mu g/g) and small amounts of carotenoids (1.81-18.77 mu g/g). We divided the 60 rose varieties tested here into five color groups based on optical spectrum and pigment content analyses. We also explored the relationships between anthocyanin contents, carotenoid contents, and flower color space values using principal component analysis, Pearson's correlations, and non-linear models. In addition to providing a more accurate system of rose petal color classification, our results can be used to predict pigment contents based on color parameters.

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