Mutka Andrew M, Bart Rebecca S
Donald Danforth Plant Science Center , Saint Louis, MO, USA.
Front Plant Sci. 2015 Jan 5;5:734. doi: 10.3389/fpls.2014.00734. eCollection 2014.
Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.
植物病害在全球范围内导致农业生产力大幅下降。病害症状对作物的生长和发育具有有害影响，限制产量并使农产品不适于食用。对于许多植物 - 病原体系统，我们缺乏对将病原体感染与宿主中病害症状产生联系起来的生理机制的了解。目前正在开发各种基于图像的定量高通量方法来对植物生长和发育进行表型分析。这些方法从对单株植物随时间的详细分析到对田间数千株植物的作物冠层进行广泛评估，并且采用了各种各样的成像技术。将这些方法应用于植物病害研究能够定量研究病原体感染如何改变宿主生理。这些方法有可能深入了解病害症状发展背后的生理机制。此外，检测可见光之外电磁光谱的成像技术使我们能够量化肉眼不可见的病害症状，扩大了我们能够观察到的症状范围，并有可能实现更早、更全面的症状检测。在本综述中，我们总结了植物病害表型分析的当前进展，并提出了将加速抗性作物品种开发的未来方向。
