Bouillon Pierre, Fanciullino Anne-Laure, Belin Etienne, Bréard Dimitri, Boisard Séverine, Bonnet Béatrice, Hanteville Sylvain, Bernard Frédéric, Celton Jean-Marc
Univ Angers, Institut Agro, INRAE, IRHS, SFR QUASAV, F-49000 , Angers, France.
IFO, 49140, Seiches sur le Loir, France.
Plant Methods. 2024 May 16;20(1):71. doi: 10.1186/s13007-024-01196-1.
The genetic basis of colour development in red-flesh apples (Malus domestica Borkh) has been widely characterised; however, current models do not explain the observed variations in red pigmentation intensity and distribution. Available methods to evaluate the red-flesh trait rely on the estimation of an average overall colour using a discrete class notation index. However, colour variations among red-flesh cultivars are continuous while development of red colour is non-homogeneous and genotype-dependent. A robust estimation of red-flesh colour intensity and distribution is essential to fully capture the diversity among genotypes and provide a basis to enable identification of loci influencing the red-flesh trait.
In this study, we developed a multivariable approach to evaluate the red-flesh trait in apple. This method was implemented to study the phenotypic diversity in a segregating hybrid F1 family (91 genotypes). We developed a Python pipeline based on image and colour analysis to quantitatively dissect the red-flesh pigmentation from RGB (Red Green Blue) images and compared the efficiency of RGB and CIELab* colour spaces in discriminating genotypes previously classified with a visual notation. Chemical destructive methods, including targeted-metabolite analysis using ultra-high performance liquid chromatography with ultraviolet detection (UPLC-UV), were performed to quantify major phenolic compounds in fruits' flesh, as well as pH and water contents. Multivariate analyses were performed to study covariations of biochemical factors in relation to colour expression in CIELab* colour space. Our results indicate that anthocyanin, flavonol and flavanol concentrations, as well as pH, are closely related to flesh pigmentation in apple.
Extraction of colour descriptors combined to chemical analyses helped in discriminating genotypes in relation to their flesh colour. These results suggest that the red-flesh trait in apple is a complex trait associated with several biochemical factors.
红肉苹果（苹果属植物）颜色发育的遗传基础已得到广泛研究；然而，目前的模型无法解释观察到的红色素沉着强度和分布的变化。现有的评估红肉性状的方法依赖于使用离散分类符号指数来估计平均整体颜色。然而，红肉品种之间的颜色变化是连续的，而红色的发育是不均匀的且依赖于基因型。对红肉颜色强度和分布进行可靠估计对于充分捕捉基因型之间的多样性并为识别影响红肉性状的基因座提供基础至关重要。
在本研究中，我们开发了一种多变量方法来评估苹果的红肉性状。该方法用于研究一个分离的杂交F1家族（91个基因型）中的表型多样性。我们基于图像和颜色分析开发了一个Python管道，以从RGB（红、绿、蓝）图像中定量分析红肉色素沉着，并比较了RGB和CIELab颜色空间在区分先前用视觉符号分类的基因型方面的效率。进行了化学破坏方法，包括使用超高效液相色谱-紫外检测（UPLC-UV）进行靶向代谢物分析，以定量果肉中的主要酚类化合物以及pH值和水分含量。进行多变量分析以研究CIELab颜色空间中生化因素与颜色表达的协变关系。我们的结果表明，花青素、黄酮醇和黄烷醇浓度以及pH值与苹果果肉色素沉着密切相关。
结合化学分析提取颜色描述符有助于根据果肉颜色区分基因型。这些结果表明，苹果的红肉性状是一个与多种生化因素相关的复杂性状。
