欧亚国际

较近，来自比利时根特大学VIB研究所的Stijin Dhont博士等人，在Computers and Electronics in Agriculture Volume 162, July 2019, Pages 749-758上发表了题为“Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform”的文章，文章利用WIWAM高通量植物表型成像平台高光谱成像分析检测玉米干旱胁迫恢复研究，重点介绍了使用标准正态变量法 (SNV) 去除线性影响，研究中还使用了聚类方法来去除抑制非线性影响的像素的方法，开发出了数据驱动光谱分析法来鉴别植物生长动力学方法，通过高通量手段对玉米植物水胁迫和恢复进行了方法学验证。WIWAM植物表型成像系统是上为数不多的可整合高光谱成像系统的设备之一。北京欧亚国际科技有限公司作为其中国区总总代理，全面负责其系列产品在中国市场的推广、销售和售后服务。

Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform

Highlights

The use of the standard normal variate (SNV) to eliminate linear effects.

The use of a clustering approach to remove pixels that exhibit nonlinear effects.

The development of a data-driven spectral analysis method to charecterize plant growth dynamics.

The validation the proposed method by a large-scale study of water-stress and recovery of maize plants.

Abstract

The study of physiological processes resulting from water-limited conditions in crops is essential for the selection of drought-tolerant genotypes and the functional analysis of related genes. A promising, non-invasive technique for plant trait analysis is close-range hyperspectral imaging (HSI), which has great potential for the early detection of plant responses to water deficit stress. In this work, a data analysis method is described that, unlike vegetation indices, the present method applies spectral similarity on selected bands with high discriminative information, while requiring a careful treatment of uninformative illumination effects. The latter issue is solved by a standard normal variate (SNV) normalization that removes linear effects and a supervised clustering approach to remove pixels that exhibit nonlinear multiple scattering effects. On the remaining pixels, the stress-related dynamics is quantified by a spectral analysis procedure that involves a supervised band selection procedure and a spectral similarity measure against well-watered control plants. The proposed method was validated by a large-scale study of water-stress and recovery of maize plants in a high-throughput plant phenotyping platform. The results showed that the analysis method allows for an early detection of drought stress responses and of recovery effects shortly after re-watering.