A comparison between visual estimates and image analysis measurements to determine Septoria leaf blotch severity in winter wheat

El Jarroudi, M. and Kouadio, A. L. and Mackels, C. and Tychon, B. and Delfosse, P. and Bock, C. H. (2015) A comparison between visual estimates and image analysis measurements to determine Septoria leaf blotch severity in winter wheat. Plant Pathology, 64 (2). pp. 355-364. ISSN 0032-0862

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Abstract

Methods to estimate disease severity vary in accuracy, reliability, ease of use and cost. Severity of septoria leaf blotch (SLB, caused by Zymoseptoria tritici) was estimated by four raters and by image analysis (assumed actual values) on individual leaves of winter wheat in order to explore accuracy and reliability of estimates, and to ascertain whether there were any general characteristics of error. Specifically, the study determined: (i) the accuracy and reliability of visual assessments of SLB over the full range of severity from 0 to 100%; (ii) whether certain 10% ranges in actual disease severity between 0 and 100% were more prone to estimation error compared with others; and (iii) whether leaf position affected accuracy within those ranges. Lin's concordance correlation analysis of all severities (0-100%) demonstrated that all raters had estimates close to the actual values (agreement: ρc = 0·92-0·99). However, agreement between actual SLB severities and estimates by raters was less good when compared over short 10% subdivisions within the 0-100% range (ρc = -0·12 to 0·99). Despite common rater imprecision at estimating low and high SLB severities, individual raters differed considerably in their accuracy over the short 10% subdivisions. There was no effect of leaf position on accuracy or precision of severity estimate on separate leaves (L1-L3). Pursuing efforts in understanding error in disease estimation should aid in improving the accuracy of assessments, making visual estimates of disease severity more useful for research and applied purposes.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2014 British Society for Plant Pathology. Permanent restricted access to published version due to publisher copyright policy. Published online 30 Jun 2014.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 08 Apr 2015 23:07
Last Modified: 07 Jun 2016 23:37
Uncontrolled Keywords: digital image analysis; disease monitoring; foliar disease; Triticum aestivum
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: B Economic Development > 82 Plant Production and Plant Primary Products > 8205 Winter Grains and Oilseeds > 820507 Wheat
Identification Number or DOI: 10.1111/ppa.12252
URI: http://eprints.usq.edu.au/id/eprint/26965

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