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首页> 外文期刊>Planta: An International Journal of Plant Biology >Extraction of quantitative characteristics describing wheat leaf pubescence with a novel image-processing technique
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Extraction of quantitative characteristics describing wheat leaf pubescence with a novel image-processing technique

机译:利用新型图像处理技术提取描述小麦叶片短熟的定量特征

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摘要

Leaf pubescence (hairiness) in wheat plays an important biological role in adaptation to the environment. However, this trait has always been methodologically difficult to phenotype. An important step forward has been taken with the use of computer technologies. Computer analysis of a photomicrograph of a transverse fold line of a leaf is proposed for quantitative evaluation of wheat leaf pubescence. The image-processing algorithm is implemented in the LHDetect2 software program accessible as a Web service at "http://wheatdb. org/lhdetect2". The results demonstrate that the proposed method is rapid, adequately assesses leaf pubescence density and the length distribution of trichomes and the data obtained using this method are significantly correlated with the density of trichomes on the leaf surface. Thus, the proposed method is efficient for high-throughput analysis of leaf pubescence morphology in cereal genetic collections and mapping populations.
机译:小麦的叶片青春期(毛羽)在适应环境方面起着重要的生物学作用。但是,这种性状在方法上一直难以表型化。使用计算机技术已迈出了重要的一步。提议对叶片的横向折叠线的显微照片进行计算机分析,以定量评估小麦叶片的短柔毛。图像处理算法在LHDetect2软件程序中实现,该程序可通过Web服务从“ http:// wheatdb。org / lhdetect2”访问。结果表明,所提出的方法是快速的,能够充分评估叶片的短柔毛密度和毛状体的长度分布,并且使用该方法获得的数据与叶表面毛状体的密度显着相关。因此,所提出的方法对于谷物遗传收集和作图种群中叶片短柔毛形态的高通量分析是有效的。

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