Literature DB >> 22990907

Extraction of quantitative characteristics describing wheat leaf pubescence with a novel image-processing technique.

Mikhail A Genaev1, Alexey V Doroshkov, Tatyana A Pshenichnikova, Nikolay A Kolchanov, Dmitry A Afonnikov.   

Abstract

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.

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Year:  2012        PMID: 22990907     DOI: 10.1007/s00425-012-1751-6

Source DB:  PubMed          Journal:  Planta        ISSN: 0032-0935            Impact factor:   4.116


  13 in total

1.  Trichome cell growth in Arabidopsis thaliana can be derepressed by mutations in at least five genes.

Authors:  D Perazza; M Herzog; M Hülskamp; S Brown; A M Dorne; J M Bonneville
Journal:  Genetics       Date:  1999-05       Impact factor: 4.562

Review 2.  Phenomics: the next challenge.

Authors:  David Houle; Diddahally R Govindaraju; Stig Omholt
Journal:  Nat Rev Genet       Date:  2010-12       Impact factor: 53.242

3.  Gamma-radiation induces leaf trichome formation in Arabidopsis.

Authors:  T Nagata; S Todoriki; T Hayashi; Y Shibata; M Mori; H Kanegae; S Kikuchi
Journal:  Plant Physiol       Date:  1999-05       Impact factor: 8.340

4.  From genotype to phenotype: systems biology meets natural variation.

Authors:  Philip N Benfey; Thomas Mitchell-Olds
Journal:  Science       Date:  2008-04-25       Impact factor: 47.728

5.  [Morphological and genetic characteristics of leaf hairiness in wheat (Triticum aestivum L.) as analyzed by computer-aided phenotyping].

Authors:  A V Doroshkov; T A Pshenichnikova; D A Afonnikov
Journal:  Genetika       Date:  2011-06

6.  Chloroplast 2010: a database for large-scale phenotypic screening of Arabidopsis mutants.

Authors:  Yan Lu; Linda J Savage; Matthew D Larson; Curtis G Wilkerson; Robert L Last
Journal:  Plant Physiol       Date:  2011-01-11       Impact factor: 8.340

7.  GERMINATOR: a software package for high-throughput scoring and curve fitting of Arabidopsis seed germination.

Authors:  Ronny V L Joosen; Jan Kodde; Leo A J Willems; Wilco Ligterink; Linus H W van der Plas; Henk W M Hilhorst
Journal:  Plant J       Date:  2009-12-22       Impact factor: 6.417

8.  Quantitative analysis of heterogeneous spatial distribution of Arabidopsis leaf trichomes using micro X-ray computed tomography.

Authors:  Eli Kaminuma; Takeshi Yoshizumi; Takuji Wada; Minami Matsui; Tetsuro Toyoda
Journal:  Plant J       Date:  2008-07-04       Impact factor: 6.417

9.  Genetic control of trichome branch number in Arabidopsis: the roles of the FURCA loci.

Authors:  D Luo; D G Oppenheimer
Journal:  Development       Date:  1999-12       Impact factor: 6.868

10.  Optogenetic manipulation of neural activity in freely moving Caenorhabditis elegans.

Authors:  Andrew M Leifer; Christopher Fang-Yen; Marc Gershow; Mark J Alkema; Aravinthan D T Samuel
Journal:  Nat Methods       Date:  2011-01-16       Impact factor: 28.547

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  4 in total

1.  LSM-W2: laser scanning microscopy worker for wheat leaf surface morphology.

Authors:  Ulyana S Zubairova; Pavel Yu Verman; Polina A Oshchepkova; Alina S Elsukova; Alexey V Doroshkov
Journal:  BMC Syst Biol       Date:  2019-03-05

2.  FlowerMorphology: fully automatic flower morphometry software.

Authors:  Sergey M Rozov; Elena V Deineko; Igor V Deyneko
Journal:  Planta       Date:  2018-02-02       Impact factor: 4.116

3.  HairNet: a deep learning model to score leaf hairiness, a key phenotype for cotton fibre yield, value and insect resistance.

Authors:  Vivien Rolland; Moshiur R Farazi; Warren C Conaty; Deon Cameron; Shiming Liu; Lars Petersson; Warwick N Stiller
Journal:  Plant Methods       Date:  2022-01-19       Impact factor: 4.993

4.  Quantitative characteristics of pubescence in wheat (Triticum aestivum L.) are associated with photosynthetic parameters under conditions of normal and limited water supply.

Authors:  Tatyana A Pshenichnikova; Alexey V Doroshkov; Svetlana V Osipova; Alexey V Permyakov; Marina D Permyakova; Vadim M Efimov; Dmitry A Afonnikov
Journal:  Planta       Date:  2018-11-16       Impact factor: 4.116

  4 in total

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