ShinyFruit:交互式水果表型软件及其在黑中的应用.
T Mason Chizk1, Jackie A Lee1, John R Clark1
1Department of Horticulture, University of Arkansas, Fayetteville, AR, United States.
Frontiers in plant science
|October 23, 2023
概括
基于R的Web应用程序ShinyFruit为园艺育种提供了高效的基于图像的表型. 它准确地测量了黑的大小和颜色,有助于基因组选择和育种策略.
科学领域:
- 园艺科学 园艺科学
- 植物育种 植物育种
- 生物信息学是一种生物信息学.
背景情况:
- 园艺植物育种需要广泛的表型数据来进行质量评估.
- 高通量表型管道对于先进的育种策略至关重要,如全基因组关联研究和基因组选择.
研究的目的:
- 介绍ShinyFruit,一个基于R的Web应用程序,用于基于图像的水果和蔬菜特征的表型.
- 与传统方法相比,评估ShinyFruit在测量黑大小和红色葡萄糖回归 (RDR) 中的准确性.
主要方法:
- 开发了一个基于R的Web应用程序ShinyFruit,用于自动化图像分析.
- 将ShinyFruit对黑长度,宽度和RDR的测量与ImageJ和手动测量进行了比较.
- 利用黑品种和繁殖选择的种群.
主要成果:
- 闪亮的水果显示强烈的正相关性与手动测量黑长度 (r = 0.96).
- 在ShinyFruit和ImageJ之间观察到RDR估计的高相关性 (r = 0.96).
- 在手动RDR估计中发现的相关性较弱 (r = 0.620.70);没有检测到宽度的基因型差异.
结论:
- ShinyFruit提供了一个可行的开源解决方案,用于有效的黑果尺寸和颜色的表型化.
- 该应用程序的可调节设置增强了其对各种水果和蔬菜的实用性.
- 进一步的研究可能会通过最大限度地提高像RDR这样的特征的基因型变异来加强相关性.
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