OPIA:植物图像和相关的表型特征的开放档案
Yongrong Cao1,2,3, Dongmei Tian1,2, Zhixin Tang3,4
1National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
Nucleic acids research
|November 6, 2023
概括
开放植物图像档案 (OPIA) 为植物现象提供了宝贵的资源,提供了广泛的图像数据集和基于图像的特征 (i-traits),对于作物改进和压力识别至关重要.
科学领域:
- 植物科学 植物科学
- 生物信息学是一种生物信息学.
- 农业技术 农业技术
背景情况:
- 高通量植物表型生成大量的图像数据,这对于作物研究至关重要.
- 基于图像的表型特征 (i-特征) 加快了生殖质查和压力分类.
- 现有的数据资源往往缺乏全面的,标准化的基于图像的特征信息.
研究的目的:
- 引入开放植物图像档案 (OPIA) 作为植物图像和i-traits的集中存储库.
- 提供对各种植物数据集的开放访问,促进人工智能辅助的育种研究.
- 通过标准化的注释和评估分数来提高数据的可发现性和可用性.
主要方法:
- 从高通量表型化平台收集了11个植物物种的56个数据集.
- 从566,225张图像中提取并标记了2,417,186个实例.
- 使用植物表型和特征本体学 (PPTO) 并与GWAS Atlas联系的米和小麦品种的注释i特征.
主要成果:
- 目前OPIA托管56个数据集,包括超过566,000张图像和240万个标记实例.
- 具体数据集包括56个i-特征,用于93种大米和105种小麦品种.
- 根据数据量,分辨率和实例数量,每个数据集都被分配一个评估分数.
结论:
- OPIA提供了对有价值的植物图像数据集,预训练模型和表型特征的开放访问.
- 该档案通过提供标准化,高质量的数据来支持人工智能辅助育种.
- OPIA准备大大推进植物现象学研究和作物改进工作.
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