Reliability and accuracy of visual methods to quantify severity of foliar bacterial spot symptoms on peach and nectarine

Plant Pathology

Volumn 62, Issue 2, 2013, Pages 460-474

  Bardsley, S J ^a   Ngugi, H K ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Inter class correlation coefficient; Kendall's tau a; Kendall's W; Lin's concordance

Indexed keywords

ACCURACY ASSESSMENT; BACTERIAL DISEASE; DATA PROCESSING; DISEASE SEVERITY; ESTIMATION METHOD; LEAF; RELIABILITY ANALYSIS; STATISTICAL ANALYSIS; VISUAL ANALYSIS;

BACTERIA (MICROORGANISMS); PRUNUS PERSICA; PRUNUS PERSICA NUCIPERSICA; XANTHOMONAS ARBORICOLA PV. PRUNI;

EID: 84874936296     PISSN: 00320862     EISSN: 13653059     Source Type: Journal    
DOI: 10.1111/j.1365-3059.2012.02651.x     Document Type: Article

References (33)

1. Agresti A, 2002. Categorical Data Analysis, 2nd edn. New York, NY, USA: Wiley-Interscience.
2. Battilani P, Rossi V, Saccardi A, 1999. Development of Xanthomonas arboricola pv. pruni epidemics on peaches. Journal of Plant Pathology81, 161-71.
3. Bland JM, Altman DG, 1999. Measuring agreement in method comparison studies. Statistical Methods in Medical Research8, 135-60.
4. Bock CH, Parker PE, Cook AZ, Gottwald TR, 2008. Visual rating and the use of image analysis for assessing different symptoms of citrus canker on grapefruit leaves. Plant Disease92, 530-41.
5. Bock CH, Parker PE, Cook AZ, Gottwald TR, 2009a. Automated image analysis of severity of foliar citrus canker. Plant Disease93, 660-5.
6. Bock CH, Gottwald TR, Parker PE et al., 2009b. The Horsfall-Barratt scale and severity estimates of citrus canker. European Journal of Plant Pathology125, 23-38.
7. Bock CH, Gottwald TR, Parker PE et al., 2010a. Some consequences of using the Horsfall-Barratt scale for hypothesis testing. Phytopathology100, 1030-41.
8. Bock CH, Poole GH, Parker PE, Gottwald TR, 2010b. Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. Critical Reviews in Plant Sciences29, 59-107.
9. Campbell CL, Madden LV, 1990. Introduction to Plant Disease Epidemiology. New York, USA: John Wiley and Sons.
10. Citadin I, Assmann AP, Mazaro SM, de Gouvêa A, Danner MA, Malagi G, 2008. Diagramatic scale to evaluate the severity of bacteriose in peach trees. Revista Brasileira de Fruticultura30, 327-30.
11. Crisosto CH, Mitchell FG, Johnson S, 1995. Factors in fresh market stone fruit quality. Postharvest News and Information6, 17N-21N.
12. Everitt BS, 1999. Dictionary of Statistics. Cambridge, UK: Cambridge University Press.
13. Forbes GA, Jeger MJ, 1987. Factors affecting the estimation of disease intensity in simulated plant structures. Zeitschrift fur Pflanzenkrankheiten und Pflanzenschutz94, 113-20.
14. Forbes GA, Korva JT, 1994. The effect of using a Horsfall-Barratt scale on precision and accuracy of visual estimation of potato late blight severity in the field. Plant Pathology43, 675-82.
15. Horsfall JG, Barratt RW, 1945. An improved grading system for measuring plant disease. Phytopathology35, 655.
16. Kendall MG, 1945. The treatment of ties in ranking problems. Biometrika33, 239-51.
17. Kendall MG, Babington Smith B, 1939. The problem of m rankings. Annals of Mathematical Statistics10, 275-87.
18. Lin L-K, 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics45, 255-68.
19. Madden LV, Hughes G, van den Bosch F, 2007. The Study of Plant Disease Epidemics. St Paul, MN, USA: APS Press.
20. Newson R, 2002. Parameters behind "nonparametric" statistics: Kendall's tau, Somers' D and median differences. Stata Journal2, 45-64.
21. Newton AC, Hackett CA, 1994. Subjective components of mildew assessment on spring barley. European Journal of Plant Pathology100, 395-412.
22. Nita M, Ellis MA, Madden LV, 2003. Reliability and accuracy of visual estimation of Phomopsis leaf blight of strawberry. Phytopathology93, 995-1005.
23. Nutter FW Jr, Littwiller D, 1993. ALFALFA.PRO- a computerized disease assessment training program for foliar diseases of alfalfa. In: Proceedings of the 23rd Central Alfalfa Improvement Conference, 20-22 June 1993. Lincoln, NE, USA: University of Nebraska, 15.
24. Parker SR, Shaw MW, Royle DJ, 1995. Reliable measurement of disease severity. Aspects of Applied Biology43, 205-14.
25. Ritchie DF, 1995. Bacterial spot. In: Ogawa JM, Zehr EI, Bird GW, Ritchie DF, Uriu K, Uyemoto JK, eds. Compendium of Stone Fruit Diseases. St Paul, MN, USA: American Phytopathological Society, 50-2.
26. Rousson V, Gasser T, Seifert B, 2002. Assessing the intrarater, interrater and test retest reliability of continuous measurements. Statistics in Medicine21, 3431-46.
27. Sherwood RT, Berg CC, Hoover MR, Zeiders KE, 1983. Illusions in visual assessment of Stagonospora leaf spot of orchardgrass. Phytopathology73, 173-7.
28. Shoukri MM, 2004. Measure of Interobserver Agreement. Boca Raton, FL, USA: Chapman and Hall/CRC.
29. Stokes ME, Davis CS, Koch GG, 2000. Categorical Data Analysis Using the SAS System, 2nd edn. Carry, NC, USA: SAS Institute Inc.
30. Svensson E, 2000. Concordance between ratings using different scales for the same variable. Statistics in Medicine19, 3483-96.
31. Tomerlin JR, Howell TA, 1988. DISTRAIN: a computer program for training people to estimate disease severity on cereal leaves. Plant Disease72, 455-9.
32. Yi Q, Wang PP, He Y, 2008. Reliability analysis for continuous measurements: equivalence test for agreement. Statistics in Medicine27, 2816-25.
33. Zehr EI, Shepard DP, Bridges Jr WC, 1996. Bacterial spot of peach as influenced by water congestion, leaf wetness duration, and temperature. Plant Disease80, 339-41.