当前位置: X-MOL 学术Planta › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
High-throughput phenotyping platform for analyzing drought tolerance in rice
Planta ( IF 4.3 ) Pub Date : 2020-08-10 , DOI: 10.1007/s00425-020-03436-9
Song Lim Kim 1 , Nyunhee Kim 1 , Hongseok Lee 1, 2 , Eungyeong Lee 1, 3 , Kyeong-Seong Cheon 1 , Minsu Kim 1 , JeongHo Baek 1 , Inchan Choi 1 , Hyeonso Ji 1 , In Sun Yoon 1 , Ki-Hong Jung 4 , Taek-Ryoun Kwon 1 , Kyung-Hwan Kim 1
Affiliation  

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.

中文翻译:

用于分析水稻耐旱性的高通量表型平台

构建了一个新的成像平台来分析水稻的耐旱性状。水稻被用于通过基于图像的参数和分析工具来量化干旱表型。气候变化增加了干旱的频率和严重程度,从而限制了全世界的作物生产。开发具有更高耐旱性和较短育种周期的新品种至关重要。然而,实现这一目标需要在短时间内以准确的方式对大量繁殖种群进行表型分析。新的尖端技术,例如基于远程传感器的技术,正在被用来解决这个问题。本研究应用新技术获取和分析成像数据,并利用耐旱突变体osphyb建立水稻耐旱性的高效筛选平台。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水分含量,红外用于评估植物温度,荧光用于检查光合作用效率。DroughtSpotter 技术用于确定水分利用效率、植物水分流失率和蒸腾速率。结果表明,这些方法可以检测耐受植物和易感植物之间的差异,表明它们作为高通量表型分析方法的价值,可用于短育种周期以及对干旱胁迫耐受性的功能遗传研究。和荧光用于检查光合作用效率。DroughtSpotter 技术用于确定水分利用效率、植物水分流失率和蒸腾速率。结果表明,这些方法可以检测耐受植物和易感植物之间的差异,表明它们作为高通量表型分析方法的价值,可用于短育种周期以及对干旱胁迫耐受性的功能遗传研究。和荧光用于检查光合作用效率。DroughtSpotter 技术用于确定水分利用效率、植物水分流失率和蒸腾速率。结果表明,这些方法可以检测耐受植物和易感植物之间的差异,表明它们作为高通量表型分析方法的价值,可用于短育种周期以及对干旱胁迫耐受性的功能遗传研究。
更新日期:2020-08-10
down
wechat
bug