Diagrammatic scale for improved late leaf rust severity assessments in raspberry leaves

References

• Aime MC, McTaggart AR. 2020. A higher-rank classification for rust fungi, with notes on genera. Plant Fungal Syst. 7:21–47.
   Google Scholar
• Amorim L, Bergamin A. 2018. Fenologia, patometria e quantificação de danos. In: Amorim L, Rezende JAM, Bergamin A, editors. Manual de fitopatologia: princípios e conceitos. 5th ed. Ouro Fino, Brazil: Agronômica Ceres; p. 499–518.
   Google Scholar
• Barbosa CMA, Martins MMV, Spósito MB. 2019. Panorama das Exportações e Importações Brasileiras de Framboesas e Amoras-Pretas in natura. X Seminário Brasileiro sobre Pequenas Frutas, Vacaria. Anais do X Seminário Brasileiro sobre Pequenas Frutas, Vacaria, Brazil.
   Google Scholar
• Belan LL, da Matta Rafael A, Gomes CA, Alves FR, de Jesus Junior WC, Moraes WB. 2020. Standard area diagram with color photographs to estimate the severity of coffee leaf rust in Coffea canephora. Crop Protec. 130(105077):1–9. doi:10.1016/j.cropro.2020.105077
   Google Scholar
• Bock CH, Hotchkiss MW, Wood BW. 2016. Assessing disease severity: accuracy and reliability of rater estimates in relation to number of diagrams in a standard area diagram set. Plant Pathol. 65(2):261–272. doi:10.1111/ppa.12403
   Web of Science ®Google Scholar
• Bock CH, Poole GH, Parker PE, Gottwald TR. 2010. Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. Crit Rev Plant Sci. 29(2):59–107. doi:10.1080/07352681003617285
   Web of Science ®Google Scholar
• Braga K, Fantin LH, Roy JM, Canteri MG, de Paiva Custódio AA. 2020. Development and validation of a diagrammatic scale for the assessment of the severity of bacterial leaf streak of corn. Eur J Plant Pathol. 157:367–375. doi:10.1007/s10658-020-02008-7
   Web of Science ®Google Scholar
• Campbell CL, Madden LV. 1990. Introduction to plant disease epidemiology. New York, USA: John Wiley & Sons.
   Google Scholar
• Correia KC, Queiroz JVJ, Martins RB, Nicoli A, Del Ponte EM, Michereff SJ. 2017. Development and evaluation of a standard area diagram set for the severity of phomopsis leaf blight on eggplant. Eur J Plant Pathol. 149(2):269–276. doi:10.1007/s10658-017-1184-y
   Web of Science ®Google Scholar
• Cortéz FAM, Chan-Cupul W, Nava MTB, Hernández-Ortega HA, Manzo-Sánchez G, Velasco EG. 2019. Biological control of late leaf rust disease [Pucciniastrum americanum (Farl.) Arthur] in raspberry (Rubus idaeus L.) using two biological products: Bacillus subtilis (Fungizard®) and Larrea tridentata botanic extract (CleanCrop®) under screenhouse conditions. Idesia. 37(1):125–133. doi:10.4067/S0718-34292019005000504
   Google Scholar
• Del Ponte EM, Pethybridge SJ, Bock CH, Michereff SJ, Machado FJ, Spolti P. 2017. Standard area diagrams for aiding severity estimation: scientometrics, pathosystems, and methodological trends in the last 25 years. Phytopathol. 107(10):1161–1174. doi:10.1094/PHYTO-02-17-0069-FI
   PubMed Web of Science ®Google Scholar
• Dolan A, MacFarlane S, Jennings SN. 2018. Pathogens in Raspberry and other Rubus spp. In: Graham J, Brennan R, editors. Raspberry: breeding, challenges and advances. Cham, Switzerland: Springer; p. 41–61. doi:10.1007/978-3-319-99031-6
   Google Scholar
• Fantin LH, Braga K, Canteri MG, Dias AR, Borges EP. 2018. Development and validation of diagrammatic scale to assess target spot severity in cotton. Australas Plant Pathol. 47(5):491–497. doi:10.1007/s13313-018-0576-6
   Web of Science ®Google Scholar
• FAO. 2021. FAOSTAT: agricultural data. [accessed 2022 Mar 28]. http://www.fao.org/faostat/en/#data/QC.
   Google Scholar
• Foster TM, Bassil NV, Dossett M, Worthington ML, Graham J. 2019. Genetic and genomic resources for Rubus breeding: a roadmap for the future. Hort Res. 6(1):1–9. doi:10.1038/s41438-019-0199-2
   PubMedGoogle Scholar
• Franceschi VT, Alves KS, Mazaro SM, Godoy CV, Duarte HS, Del Ponte EM. 2020. A new standard area diagram set for assessment of severity of soybean rust improves accuracy of estimates and optimizes resource use. Plant Pathol. 69(3):495–505. doi:10.1111/ppa.13148
   Web of Science ®Google Scholar
• Gamer M, Lemon J, Fellows I, Singh P. 2012. Various coefficients of interrater reliability and agreement. R package version 0.84. http://CRAN.R-project.org/package=irr.
   Google Scholar
• Kranz J. 1988. Measuring plant disease. In: Kranz J, Rotem J, editors. Experimental techniques in plant disease epidemiology. Berlin, Heidelberg, Germany: Springer; p. 35–50. doi:10.1007/978-3-642-95534-1
   Google Scholar
• Lima Filho FA, Leite IC, Capucho AS, Michereff SJ, Freitas-Lopes RL, Lopes UP. 2019. Accuracy and efficiency of assessments of cassava brown leaf spot aided by standard area diagram sets based on whole compound leaves or single central leaflets. Eur J Plant Pathol. 153(2):627–638. doi:10.1007/s10658-018-1586-5
   Web of Science ®Google Scholar
• Lin L. 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 45:255–268. doi:10.2307/2532051
   PubMed Web of Science ®Google Scholar
• Lin L, Hedayat AS, Sinha B, Yang M. 2002. Statistical methods in assessing agreement. J Am Stat Assoc. 97(457):257–270. doi:10.1198/016214502753479392
   Web of Science ®Google Scholar
• Luffman M, Buszard D. 1990. A note on the susceptibility of six red raspberry cultivars and Tayberry to fruit infection by late yellow rust. Phytoprotection. 71:93–95. doi:10.7202/705987ar
   Web of Science ®Google Scholar
• Nelson S. 2011. Raspberry late leaf rust in Hawaii caused by Pucciniastrum americanum. Honolulu (HI): University of Hawaii. Plant Disease Series 73(5).
   Google Scholar
• Nita M, Ellis MA, Madden LV. 2003. Reliability and accuracy of visual estimation of Phomopsis leaf blight of strawberry. Phytopathol. 93(8):995–1005. doi:10.1094/PHYTO.2003.93.8.995
   PubMed Web of Science ®Google Scholar
• Nutter FW, Schultz PM. 1995. Improving the accuracy and precision of disease assessments: selection of methods and use of computer-aided training programs. Can J Plant Pathol. 17:174–184. doi:10.1080/07060669509500709
   Web of Science ®Google Scholar
• Pereira RCM, Laignier Filho CA, de Melo LA, Alozen PC, Mafia RG, Barros AF, Ferreira MA. 2019. Diagrammatic scale for severity evaluation of the Eremanthus erythropappus–Puccinia velata pathosystem. J Phytopathol. 168(3):135–143. doi:10.1111/jph.12855
   Web of Science ®Google Scholar
• RStudio Team. 2018. RStudio: integrated development for R. Boston (MA): RStudio, Inc. http://www.rstudio.com/.
   Google Scholar
• Santos RF, Spósito MB. 2018. Improving assessments of anthracnose severity on grapevine leaves through the development of a standard area diagram set. Australas Plant Pathol. 47(4):357–364. doi:10.1007/s13313-018-0566-8
   Web of Science ®Google Scholar
• Schwanck AA, Del Ponte EM. 2014. Accuracy and reliability of severity estimates using linear or logarithmic disease diagram sets in true colour or black and white: a study case for rice brown spot. J Phytopathol. 162:670–682. doi:10.1111/jph.12246
   Web of Science ®Google Scholar
• Stevenson M, Nunes T, Heuer C, Marshall J, Sanchez J, Thornton R. 2017. epiR: tools for the analysis of epidemiological data. R package. https://cran.rproject.org/web/packages/epiR/index.html.
   Google Scholar
• Vale FXR, Fernandes Filho EI, Liberato JR. 2003. QUANT: a software plant disease severity assessment. In: Close R, Braithwaite M, editors. Havery Proceedings of the 8th International Congress of Plant Pathology, New Zealand. Vol. 1; Sydney (Australia): Horticulture Australia; p. 105.
   Google Scholar
• Yadav NVS, De Vos SM, Bock CH, Wood BW. 2013. Development and validation of standard area diagrams to aid assessment of pecan scab symptoms on fruit. Plant Pathol. 62:325–335. doi:10.1111/j.1365-3059.2012.02641.x.
   Web of Science ®Google Scholar