Laboratory of Evolutionary Bioinformatics and Theoretical Genetics, Department of Systems Biology, Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.
Planta. 2012 Dec;236(6):1943-54. doi: 10.1007/s00425-012-1751-6. Epub 2012 Sep 19.
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.
叶片的茸毛（绒毛）在小麦适应环境中起着重要的生物学作用。然而，这种特性在表型分析方面一直具有方法学上的困难。随着计算机技术的应用，已经取得了重要的进展。本文提出了一种利用计算机分析叶片横褶线的显微照片来定量评价小麦叶片茸毛的方法。图像处理算法在 LHDetect2 软件程序中实现，该程序可作为 Web 服务在 http://wheatdb.org/lhdetect2 上访问。结果表明，该方法快速，能够充分评估叶片茸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片表面毛状体的密度显著相关。因此，该方法可用于高通量分析谷类遗传群体和作图群体的叶片茸毛形态。
