Plant high-throughput phenotyping technology is taking more and more important roles in soybean breeding and genetic research thanks to the advance in sensing and data analytic technologies. However, commercial high-throughput phenotyping systems of general purpose are expensive and complicated for many research groups, and their data analytic methods are designed for specific research projects. The goal of this study was to develop and validate a customized image-based phenotyping system that was used to automatedly collect, process and analyze imagery data of soybean cultivars to evaluate their response to salt stress in controlled environments. The imaging system consisted of a consumer-grade digital camera and an automated platform was used to take sequential images of soybean plants of five cultivars under salt stress during the experimental period. An image processing and analytic pipeline was developed to automatically extract image features and evaluate their tolerance to salt stress. Results indicated that two image features, i.e. canopy area and ExV (the difference of excess green and excess red) were highly correlated with salinity tolerance trait of soybean. The image saturation and blue channel values were able to extract salt stress characteristics and identify different types of salt stress characteristics. In addition, the ratio of damaged leaf area to canopy area was extracted as a novel image feature to quantify the salinity tolerance grade. The overall results indicated that the automatic plant phenotyping system based on low-cost image sensors and automation platform was able to quantify plant stress due to salt stress and would be useful in soybean breeding programs.

由于传感和数据分析技术的进步，植物高通量表型技术在大豆育种和遗传研究中发挥着越来越重要的作用。然而，对于许多研究小组而言，通用的商业化高通量表型系统昂贵且复杂，并且其数据分析方法是为特定研究项目设计的。这项研究的目的是开发和验证定制的基于图像的表型分析系统，该系统可用于自动收集，处理和分析大豆品种的图像数据，以评估其在受控环境中对盐胁迫的响应。该成像系统由一台消费级数码相机和一个自动化平台组成，用于在试验期间对五个品种在盐胁迫下的大豆植物进行连续拍摄。开发了图像处理和分析管道以自动提取图像特征并评估其对盐胁迫的耐受性。结果表明，两个图像特征，即冠层面积和ExV（过量绿色和过量红色之差）与大豆的耐盐性相关。图像饱和度和蓝色通道值能够提取盐胁迫特征并识别不同类型的盐胁迫特征。此外，提取受损叶面积与冠层面积之比作为一种新颖的图像特征，以量化耐盐度等级。总体结果表明，基于低成本图像传感器和自动化平台的自动植物表型分析系统能够量化由于盐胁迫引起的植物胁迫，可用于大豆育种计划。