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高通量表型分析平台在水稻耐旱性分析中的应用。

High-throughput phenotyping platform for analyzing drought tolerance in rice.

机构信息

The National Institute of Agricultural Sciences, 370 Nongsaengmyeong-ro, Wansan-gu, Jeonju-si, Jeollabuk-do, Republic of Korea.

Department of Agricultural Machinery Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea.

出版信息

Planta. 2020 Aug 10;252(3):38. doi: 10.1007/s00425-020-03436-9.

DOI:10.1007/s00425-020-03436-9
PMID:32779032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7417419/
Abstract

A new imaging platform was constructed to analyze drought-tolerant traits of rice. Rice was used to quantify drought phenotypes through image-based parameters and analyzing tools. Climate change has increased the frequency and severity of drought, which limits crop production worldwide. Developing new cultivars with increased drought tolerance and short breeding cycles is critical. However, achieving this goal requires phenotyping a large number of breeding populations in a short time and in an accurate manner. Novel cutting-edge technologies such as those based on remote sensors are being applied to solve this problem. In this study, new technologies were applied to obtain and analyze imaging data and establish efficient screening platforms for drought tolerance in rice using the drought-tolerant mutant osphyb. Red-Green-Blue images were used to predict plant area, color, and compactness. Near-infrared imaging was used to determine the water content of rice, infrared was used to assess plant temperature, and fluorescence was used to examine photosynthesis efficiency. DroughtSpotter technology was used to determine water use efficiency, plant water loss rate, and transpiration rate. The results indicate that these methods can detect the difference between tolerant and susceptible plants, suggesting their value as high-throughput phenotyping methods for short breeding cycles as well as for functional genetic studies of tolerance to drought stress.

摘要

构建了一个新的成像平台来分析水稻的耐旱特性。通过基于图像的参数和分析工具,利用水稻来量化干旱表型。气候变化增加了干旱的频率和严重程度,从而限制了全球的作物生产。开发具有更高耐旱性和更短育种周期的新品种至关重要。然而,要实现这一目标,需要在短时间内准确地对大量的育种群体进行表型分析。基于远程传感器的新技术等新型前沿技术正在被应用来解决这个问题。在这项研究中,应用了新技术来获取和分析成像数据,并利用耐旱突变体 osphyb 建立了一个高效的水稻耐旱性筛选平台。红-绿-蓝图像用于预测植物面积、颜色和紧凑度。近红外成像用于确定水稻的含水量,红外线用于评估植物温度,荧光用于检查光合作用效率。DroughtSpotter 技术用于确定水利用效率、植物水分损失率和蒸腾速率。结果表明,这些方法可以检测出耐旱和易感植物之间的差异,这表明它们作为高通量表型分析方法具有很高的价值,适用于短育种周期,也适用于耐旱胁迫的功能遗传研究。

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