Development of an automated phenotyping platform for quantifying for soybean dynamic responses to salinity stress in greenhouse environment

文献类型： 外文期刊

第一作者： Zhou, Jianfeng

作者： Zhou, Jianfeng;Zhou, Jing;Fu, Xiuqing;Chen, Huatao;Ye, Heng;Nguyen, Henry T.;Chen, Huatao;Fu, Xiuqing

作者机构：

关键词： High-throughput phenotyping; Imaging sensor; Soybean salt tolerance; Genetic variations

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：5.565； 五年影响因子：5.494 ）

ISSN： 0168-1699

年卷期： 2018 年 151 卷

页码：

收录情况： SCI

摘要： Soybean is a salt sensitive crop and saline soil results in substantial reduction in crop productivity. The genetic resources for salt tolerance in soybean were observed but are not fully evaluated due to the difficulty in capturing and quantifying the dynamic responses to salinity stress for large, diverse germplasm collections. This study aimed to develop an automated plant phenotyping system in an established greenhouse and validate this system in capturing dynamic responses in soybean to salinity stress. A digital camera (red, green and blue) was used to take sequential images of soybean for salt tolerance in 21 diverse accessions with three replicates (63 plants in total). Data processing pipeline was built to extract plant morphological and color-based image features. Thirty-nine image features were extracted and used to estimate plant leaf chlorophyll content and rate the soybean tolerance for salinity stress. Statistical analysis shows that the extracted image features could be used to quantify the dynamic responses of plants to salinity stress. It is found that both leaf chlorophyll content and visual salt tolerance rate (STR) had high correlations with image features. This study demonstrated the usefulness of the developed system in measuring soybean dynamic response to salinity stress.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序