Literature DB >> 22204655

Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem.

Weilong Xie1, Kangfu Yu, K Peter Pauls, Alireza Navabi.   

Abstract

The effectiveness of image analysis (IA) compared with an ordinal visual scale, for quantitative measurement of disease severity, its application in quantitative genetic studies, and its effect on the estimates of genetic parameters were investigated. Studies were performed using eight backcross-derived families of common bean (Phaseolus vulgaris) (n = 172) segregating for the molecular marker SU91, known to be associated with a quantitative trait locus (QTL) for resistance to common bacterial blight (CBB), caused by Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans. Even though both IA and visual assessments were highly repeatable, IA was more sensitive in detecting quantitative differences between bean genotypes. The CBB phenotypic difference between the two SU91 genotypic groups was consistently more than fivefold for IA assessments but generally only two- to threefold for visual assessments. Results suggest that the visual assessment results in overestimation of the effect of QTL in genetic studies. This may have been caused by lack of additivity and uneven intervals of the visual scale. Although visual assessment of disease severity is a useful tool for general selection in breeding programs, assessments using IA may be more suitable for phenotypic evaluations in quantitative genetic studies involving CBB resistance as well as other foliar diseases.

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Year:  2012        PMID: 22204655     DOI: 10.1094/PHYTO-06-11-0175

Source DB:  PubMed          Journal:  Phytopathology        ISSN: 0031-949X            Impact factor:   4.025


  12 in total

1.  Quantitative, Image-Based Phenotyping Methods Provide Insight into Spatial and Temporal Dimensions of Plant Disease.

Authors:  Andrew M Mutka; Sarah J Fentress; Joel W Sher; Jeffrey C Berry; Chelsea Pretz; Dmitri A Nusinow; Rebecca Bart
Journal:  Plant Physiol       Date:  2016-07-21       Impact factor: 8.340

2.  QTL mapping for downy mildew resistance in cucumber inbred line WI7120 (PI 330628).

Authors:  Yuhui Wang; Kyle VandenLangenberg; Todd C Wehner; Peter A G Kraan; Jos Suelmann; Xiangyang Zheng; Ken Owens; Yiqun Weng
Journal:  Theor Appl Genet       Date:  2016-05-04       Impact factor: 5.699

3.  Analysis of some common pathogens and their drug resistance to antibiotics.

Authors:  Lidao Bao; Rui Peng; Xianhua Ren; Ruilian Ma; Junping Li; Yi Wang
Journal:  Pak J Med Sci       Date:  2013-01       Impact factor: 1.088

4.  Image-based phenotyping of plant disease symptoms.

Authors:  Andrew M Mutka; Rebecca S Bart
Journal:  Front Plant Sci       Date:  2015-01-05       Impact factor: 5.753

5.  Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets.

Authors:  Céline Rousseau; Gilles Hunault; Etienne Belin; Tristan Boureau; Sylvain Gaillard; Julie Bourbeillon; Gregory Montiel; Philippe Simier; Claire Campion; Marie-Agnès Jacques
Journal:  Plant Methods       Date:  2015-04-03       Impact factor: 4.993

Review 6.  Advances and Challenges in Bacterial Spot Resistance Breeding in Tomato (Solanum lycopersicum L.).

Authors:  Pragya Adhikari; Tika B Adhikari; Frank J Louws; Dilip R Panthee
Journal:  Int J Mol Sci       Date:  2020-03-03       Impact factor: 5.923

7.  The Induction of the Isoflavone Biosynthesis Pathway Is Associated with Resistance to Common Bacterial Blight in Phaseolus vulgaris L.

Authors:  Laura D Cox; Seth Munholland; Lili Mats; Honghui Zhu; William L Crosby; Lewis Lukens; Karl Peter Pauls; Gale G Bozzo
Journal:  Metabolites       Date:  2021-07-01

Review 8.  Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology.

Authors:  Kuo-Szu Chiang; Clive H Bock
Journal:  Trop Plant Pathol       Date:  2021-07-13       Impact factor: 2.404

9.  High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis.

Authors:  Céline Rousseau; Etienne Belin; Edouard Bove; David Rousseau; Frédéric Fabre; Romain Berruyer; Jacky Guillaumès; Charles Manceau; Marie-Agnès Jacques; Tristan Boureau
Journal:  Plant Methods       Date:  2013-06-13       Impact factor: 4.993

10.  Using image analysis for quantitative assessment of needle bladder rust disease of Norway spruce.

Authors:  A Ganthaler; A Losso; S Mayr
Journal:  Plant Pathol       Date:  2018-03-01       Impact factor: 2.590

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