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

Article


El Jarroudi, M., Kouadio, A. L., Mackels, C., Tychon, B., 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. https://doi.org/10.1111/ppa.12252
Article Title

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

ERA Journal ID2652
Article CategoryArticle
AuthorsEl Jarroudi, M. (Author), Kouadio, A. L. (Author), Mackels, C. (Author), Tychon, B. (Author), Delfosse, P. (Author) and Bock, C. H. (Author)
Journal TitlePlant Pathology
Journal Citation64 (2), pp. 355-364
Number of Pages10
Year2015
PublisherJohn Wiley & Sons
Place of PublicationUnited Kingdom
ISSN0032-0862
1365-3059
Digital Object Identifier (DOI)https://doi.org/10.1111/ppa.12252
Web Address (URL)https://bsppjournals.onlinelibrary.wiley.com/doi/full/10.1111/ppa.12252
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.

Keywordsdigital image analysis; disease monitoring; foliar disease; Triticum aestivum
ANZSRC Field of Research 2020300207. Agricultural systems analysis and modelling
300409. Crop and pasture protection (incl. pests, diseases and weeds)
460306. Image processing
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Byline AffiliationsUniversity of Liege, Belgium
Agriculture and Agri-Food, Canada
Luxembourg Institute of Science and Technology, Luxembourg
Department of Agriculture, United States
Institution of OriginUniversity of Southern Queensland
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Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale
Kouadio, Louis, Newlands, Nathaniel K., Davidson, Andrew, Zhang, Yinsuo and Chipanshi, Aston. 2014. "Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale." Remote Sensing. 6 (10), pp. 10193-10214. https://doi.org/10.3390/rs61010193
Brown rust disease control in winter wheat: II. Exploring the optimization of fungicide sprays through a decision support system
El Jarroudi, Moussa, Kouadio, Louis, Giraud, Frederic, Delfosse, Philippe and Tychon, Bernard. 2014. "Brown rust disease control in winter wheat: II. Exploring the optimization of fungicide sprays through a decision support system." Environmental Science and Pollution Research. 21 (7), pp. 4809-4818. https://doi.org/10.1007/s11356-014-2557-9
Brown rust disease control in winter wheat: I. Exploring an approach for disease progression based on night weather conditions
El Jarroudi, Moussa, Kouadio, Louis, Delfosse, Philippe and Tychon, Bernard. 2014. "Brown rust disease control in winter wheat: I. Exploring an approach for disease progression based on night weather conditions." Environmental Science and Pollution Research. 21 (7), pp. 4797-4808. https://doi.org/10.1007/s11356-013-2463-6
An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty
Newlands, Nathaniel K., Zamar, David S., Kouadio, Louis A., Zhang, Yinsuo, Chipanshi, Aston, Potgieter, Andries, Toure, Souleymane and Hill, Harvey S. J.. 2014. "An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty." Frontiers in Environmental Science. 2, pp. 1-21. https://doi.org/10.3389/fenvs.2014.00017
A comparison of raters and disease assessment methods for estimating disease severity for purposes of hypothesis testing
Bock, Clive, El Jarroudi, Moussa, Kouadio, Louis, Mackels, Christophe, Chiang, Kuo-Szu and Delfosse, Philippe. 2014. "A comparison of raters and disease assessment methods for estimating disease severity for purposes of hypothesis testing." Phytopathology: International Journal of the American Phytopathological Society. 104 (11), pp. 15-16.
Importance of a well-distributed frequency of measurements in the senescence monitoring of winter wheat and yield estimates
Kouadio, Louis, Djaby, Bakary, El Jarroudi, Moussa and Tychon, Bernard. 2012. "Importance of a well-distributed frequency of measurements in the senescence monitoring of winter wheat and yield estimates." Journal of Agricultural Science and Technology . 2 (12), pp. 1203-1213.
Estimating winter wheat yield through the decreasing phase of its green area [Cinetique de decroissance de la surface verte et estimation du rendement du ble d'hiver]
Kouadio, Amani Louis, Djaby, Bakary, Duveiller, Gregory, El Jarroudi, Moussa and Tychon, Bernard. 2012. "Estimating winter wheat yield through the decreasing phase of its green area [Cinetique de decroissance de la surface verte et estimation du rendement du ble d'hiver]." Biotechnology, Agronomy, Society and Environment. 16 (2), pp. 179-191.
Typology of the main fungal diseases affecting winter wheat in the Grand Duchy of Luxembourg
El Jarroudi, Moussa, Kouadio, Louis, Delfosse, Philippe, Giraud, Frederic, Junk, Jurgen, Hoffmann, Lucien, Maraite, Henri and Tychon, Bernard. 2012. "Typology of the main fungal diseases affecting winter wheat in the Grand Duchy of Luxembourg." Journal of Agricultural Science and Technology . 2 (12), pp. 1386-1399.
Spatial distribution of calibrated WOFOST parameters and their influence on the performances of a regional yield forecasting system
Djaby, Bakary, de Wit, Allard, Kouadio, Louis, El Jarroudi, Moussa and Tychon, Bernard. 2013. "Spatial distribution of calibrated WOFOST parameters and their influence on the performances of a regional yield forecasting system." Sustainable Agriculture Research. 2 (4), pp. 12-29. https://doi.org/10.5539/sar.v2n4p12
Disease severity assessment in epidemiological studies: accuracy and reliability of visual estimates of Septoria leaf blotch (SLB) in winter wheat
El Jarroudi, Moussa, Kouadio, Louis, Mackels, Christophe, Tychon, Bernard, Delfosse, Philippe and Bock, Clive H.. 2014. "Disease severity assessment in epidemiological studies: accuracy and reliability of visual estimates of Septoria leaf blotch (SLB) in winter wheat." 2014 APS-CPS Joint Meeting. Minneapolis, United States of America 09 - 13 Aug 2014 United States. American Phytopathological Society. https://doi.org/10.1094/PHYTO-104-11-S3.1
Profitability of using warning system for foliar disease of wheat in the Grand-Duchy of Luxembourg
El Jarroudi, M., Kouadio, L., Beyer, M., Tychon, B. and Delfosse, P.. 2013. "Profitability of using warning system for foliar disease of wheat in the Grand-Duchy of Luxembourg." 2013 APS-MSA Joint Meeting. United States 10 - 14 Aug 2013 United States. American Phytopathological Society. https://doi.org/10.1094/PHYTO-103-6-S2.1