References

Agrios, G. N. 2005a. INTRODUCTION. In Elsevier, p. 3–75. Available at: http://dx.doi.org/10.1016/b978-0-08-047378-9.50007-5.

Agrios, G. N. 2005b. Plant disease epidemiology. In Elsevier, p. 265–291. Available at: http://dx.doi.org/10.1016/b978-0-08-047378-9.50014-2.

Alves, K. S., and Del Ponte, E. M. 2021. Analysis and simulation of plant disease progress curves in R: introducing the epifitter package. Phytopathology Research. 3 Available at: http://dx.doi.org/10.1186/s42483-021-00098-7.

Alves, K. S., Guimarães, M., Ascari, J. P., Queiroz, M. F., Alfenas, R. F., Mizubuti, E. S. G., et al. 2021. RGB-based phenotyping of foliar disease severity under controlled conditions. Tropical Plant Pathology. 47:105–117 Available at: http://dx.doi.org/10.1007/S40858-021-00448-Y.

Baddeley, A., Diggle, P. J., Hardegen, A., Lawrence, T., Milne, R. K., and Nair, G. 2014. On tests of spatial pattern based on simulation envelopes. Ecological Monographs. 84:477–489 Available at: http://dx.doi.org/10.1890/13-2042.1.

Baddeley, A., Turner, R., Moller, J., and Hazelton, M. 2005. Residual analysis for spatial point processes (with discussion). Journal of the Royal Statistical Society: Series B (Statistical Methodology). 67:617–666 Available at: http://dx.doi.org/10.1111/j.1467-9868.2005.00519.x.

Barnhart, H. X., Haber, M., and Song, J. 2002. Overall Concordance Correlation Coefficient for Evaluating Agreement Among Multiple Observers. Biometrics. 58:1020–1027 Available at: http://dx.doi.org/10.1111/j.0006-341x.2002.01020.x.

Bates, D., Mächler, M., Bolker, B., and Walker, S. 2015. Fitting Linear Mixed-Effects Models Usinglme4. Journal of Statistical Software. 67 Available at: http://dx.doi.org/10.18637/jss.v067.i01.

Bock, C. H., Chiang, K.-S., and Del Ponte, E. M. 2021a. Plant disease severity estimated visually: a century of research, best practices, and opportunities for improving methods and practices to maximize accuracy. Tropical Plant Pathology. 47:25–42 Available at: http://dx.doi.org/10.1007/s40858-021-00439-z.

Bock, C. H., Pethybridge, S. J., Barbedo, J. G. A., Esker, P. D., Mahlein, A.-K., and Del Ponte, E. M. 2021b. A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter-disciplinary dialogues. Tropical Plant Pathology. 47:14–24 Available at: http://dx.doi.org/10.1007/s40858-021-00454-0.

Bourke, P. M. A. 1970. Use of Weather Information in the Prediction of Plant Disease Epiphytotics. Annual Review of Phytopathology. 8:345–370 Available at: http://dx.doi.org/10.1146/annurev.py.08.090170.002021.

Brooks, M. E., Kristensen, K., van Benthem, K. J., Magnusson, A., Berg, C. W., Nielsen, A., et al. 2017. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal. 9:378–400.

Brown, V. A. 2021. An Introduction to Linear Mixed-Effects Modeling in R. Advances in Methods and Practices in Psychological Science. 4:251524592096035 Available at: http://dx.doi.org/10.1177/2515245920960351.

Café-Filho, A. C., Santos, G. R., and Laranjeira, F. F. 2010. Temporal and spatial dynamics of watermelon gummy stem blight epidemics. European Journal of Plant Pathology. 128:473–482 Available at: http://dx.doi.org/10.1007/s10658-010-9674-1.

Campbell, C. L., and Madden. L., V. 1990. Introduction to plant disease epidemiology. Wiley.

Chester, K. S. 1950. Plant disease losses : Their appraisal and interpretation /. Available at: http://dx.doi.org/10.5962/bhl.title.86198.

Chiang, K.-S., and Bock, C. H. 2021. Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology. Tropical Plant Pathology. 47:58–73 Available at: http://dx.doi.org/10.1007/s40858-021-00446-0.

Chiang, K.-S., Chang, Y. M., Liu, H. I., Lee, J. Y., El Jarroudi, M., and Bock, C. 2023. Survival Analysis as a Basis to Test Hypotheses When Using Quantitative Ordinal Scale Disease Severity Data. Phytopathology®. Available at: http://dx.doi.org/10.1094/PHYTO-02-23-0055-R.

Chiang, K.-S., Liu, S.-C., Bock, C. H., and Gottwald, T. R. 2014. What Interval Characteristics Make a Good Categorical Disease Assessment Scale? Phytopathology®. 104:575–585 Available at: http://dx.doi.org/10.1094/phyto-10-13-0279-r.

Cruz, C. D., and Valent, B. 2017. Wheat blast disease: danger on the move. Tropical Plant Pathology. 42:210–222 Available at: http://dx.doi.org/10.1007/s40858-017-0159-z.

Dalla Lana, F., Ziegelmann, P. K., Maia, A. de H. N., Godoy, C. V., and Del Ponte, E. M. 2015. Meta-Analysis of the Relationship Between Crop Yield and Soybean Rust Severity. Phytopathology®. 105:307–315 Available at: http://dx.doi.org/10.1094/PHYTO-06-14-0157-R.

De Rossi, R. L., Guerra, F. A., Plazas, M. C., Vuletic, E. E., Brücher, E., Guerra, G. D., et al. 2022. Crop damage, economic losses, and the economic damage threshold for northern corn leaf blight. Crop Protection. 154:105901 Available at: http://dx.doi.org/10.1016/j.cropro.2021.105901.

De Wolf, E. D., Madden, L. V., and Lipps, P. E. 2003. Risk Assessment Models for Wheat Fusarium Head Blight Epidemics Based on Within-Season Weather Data. Phytopathology®. 93:428–435 Available at: http://dx.doi.org/10.1094/PHYTO.2003.93.4.428.

Del Ponte, E. M., Cazón, L. I., Alves, K. S., Pethybridge, S. J., and Bock, C. H. 2022. How much do standard area diagrams improve accuracy of visual estimates of the percentage area diseased? A systematic review and meta-analysis. Tropical Plant Pathology. 47:43–57 Available at: http://dx.doi.org/10.1007/s40858-021-00479-5.

Del Ponte, E. M., Pethybridge, S. J., Bock, C. H., Michereff, S. J., Machado, F. J., and Spolti, P. 2017. Standard Area Diagrams for Aiding Severity Estimation: Scientometrics, Pathosystems, and Methodological Trends in the Last 25 Years. Phytopathology®. 107:1161–1174 Available at: http://dx.doi.org/10.1094/PHYTO-02-17-0069-FI.

Duffeck, M. R., Santos Alves, K. dos, Machado, F. J., Esker, P. D., and Del Ponte, E. M. 2020. Modeling Yield Losses and Fungicide Profitability for Managing Fusarium Head Blight in Brazilian Spring Wheat. Phytopathology®. 110:370–378 Available at: http://dx.doi.org/10.1094/PHYTO-04-19-0122-R.

Esser, D. S., Leveau, J. H. J., Meyer, K. M., and Wiegand, K. 2014. Spatial scales of interactions among bacteria and between bacteria and the leaf surface. FEMS Microbiology Ecology. 91 Available at: http://dx.doi.org/10.1093/femsec/fiu034.

Franceschi, V. T., Alves, K. S., Mazaro, S. M., Godoy, C. V., Duarte, H. S. S., and Del Ponte, E. M. 2020. A new standard area diagram set for assessment of severity of soybean rust improves accuracy of estimates and optimizes resource use. Plant Pathology. 69:495–505 Available at: http://dx.doi.org/10.1111/ppa.13148.

Francl, L. J. 2001. The..disease triangle: A plant pathological paradigm revisited. The Plant Health Instructor. Available at: http://dx.doi.org/10.1094/PHI-T-2001-0517-01.

Gigot, C. 2018. Epiphy: Analysis of plant disease epidemics.

Godoy, C. V., Seixas, C. D. S., Soares, R. M., Marcelino-Guimarães, F. C., Meyer, M. C., and Costamilan, L. M. 2016. Asian soybean rust in brazil: Past, present, and future. Pesquisa Agropecuária Brasileira. 51:407–421 Available at: http://dx.doi.org/10.1590/S0100-204X2016000500002.

González-Domínguez, E., Martins, R. B., Del Ponte, E. M., Michereff, S. J., García-Jiménez, J., and Armengol, J. 2014. Development and validation of a standard area diagram set to aid assessment of severity of loquat scab on fruit. European Journal of Plant Pathology. Available at: http://dx.doi.org/10.1007/s10658-014-0400-2.

Hebert, T. T. 1982. The rationale for the horsfall-barratt plant disease assessment scale. Phytopathology. 72:1269 Available at: http://dx.doi.org/10.1094/phyto-72-1269.

Islam, M. T., Kim, K.-H., and Choi, J. 2019. Wheat Blast in Bangladesh: The Current Situation and Future Impacts. The Plant Pathology Journal. 35:1–10 Available at: http://dx.doi.org/10.5423/ppj.rw.08.2018.0168.

Jeger, M. J., and Viljanen-Rollinson, S. L. H. 2001. The use of the area under the disease-progress curve (AUDPC) to assess quantitative disease resistance in crop cultivars. Theoretical and Applied Genetics. 102:32–40 Available at: http://dx.doi.org/10.1007/s001220051615.

Jesus Junior, W. C. de, and Bassanezi, R. B. 2004. Análise da dinâmica e estrutura de focos da morte súbita dos citros. Fitopatologia Brasileira. 29:399–405 Available at: http://dx.doi.org/10.1590/S0100-41582004000400007.

Krause, R. A., and Massie, L. B. 1975. Predictive Systems: Modern Approaches to Disease Control. Annual Review of Phytopathology. 13:31–47 Available at: http://dx.doi.org/10.1146/annurev.py.13.090175.000335.

Krause, R. A., Massie, L. B., and Hyre, R. A. 1975. BLITECAST: A computerized forecast of potato late blight. The Plant Disease Reporter. 59:95.

Laranjeira, F. F., Bergamin Filho, A. R., and Amorim, L. I. 1998. Dinâmica e estrutura de focos da clorose variegada dos citros (CVC). Fitopatologia Brasileira. 23:36–41.

Laranjeira, F. F., Bergamin Filho, A., Amorim, L., and Gottwald, T. R. 2004. Dinâmica espacial da clorose variegada dos citros em três regiões do estado de são paulo. Fitopatologia Brasileira. 29:56–65 Available at: http://dx.doi.org/10.1590/S0100-41582004000100009.

Lehner, M. S., Pethybridge, S. J., Meyer, M. C., and Del Ponte, E. M. 2016. Meta-analytic modelling of the incidenceyield and incidencesclerotial production relationships in soybean white mould epidemics. Plant Pathology. 66:460–468 Available at: http://dx.doi.org/10.1111/ppa.12590.

Leiminger, J. H., and Hausladen, H. 2012. Early Blight Control in Potato Using Disease-Orientated Threshold Values. Plant Disease. 96:124–130 Available at: http://dx.doi.org/10.1094/PDIS-05-11-0431.

Li, B., Madden, L. V., and Xu, X. 2011. Spatial analysis by distance indices: an alternative local clustering index for studying spatial patterns. Methods in Ecology and Evolution. 3:368–377 Available at: http://dx.doi.org/10.1111/j.2041-210x.2011.00165.x.

Li, F., Upadhyaya, N. M., Sperschneider, J., Matny, O., Nguyen-Phuc, H., Mago, R., et al. 2019. Emergence of the Ug99 lineage of the wheat stem rust pathogen through somatic hybridisation. Nature Communications. 10 Available at: http://dx.doi.org/10.1038/s41467-019-12927-7.

Lin, L. I.-K. 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 45:255 Available at: http://dx.doi.org/10.2307/2532051.

Liu, H. I., Tsai, J. R., Chung, W. H., Bock, C. H., and Chiang, K. S. 2019. Effects of Quantitative Ordinal Scale Design on the Accuracy of Estimates of Mean Disease Severity. Agronomy. 9:565 Available at: http://dx.doi.org/10.3390/agronomy9090565.

Madden, L. 1978. FAST, a forecast system for alternaria solani on tomato. Phytopathology. 68:1354 Available at: http://dx.doi.org/10.1094/phyto-68-1354.

Madden, L. V. 1982. Evaluation of tests for randomness of infected plants. Phytopathology. 72:195 Available at: http://dx.doi.org/10.1094/phyto-72-195.

Madden, L. V., Esker, P. D., and Pethybridge, S. J. 2021. Forrest W. Nutter, Jr.: a career in phytopathometry. Tropical Plant Pathology. 47:5–13 Available at: http://dx.doi.org/10.1007/s40858-021-00469-7.

Madden, L. V., Hughes, G., and Bosch, F. van den, eds. 2007a. CHAPTER 12: Epidemics and crop yield. In The American Phytopathological Society, p. 353–388. Available at: http://dx.doi.org/10.1094/9780890545058.012.

Madden, L. V., Hughes, G., and van den Bosch, F. 2007b. Spatial aspects of epidemicsIII: Patterns of plant disease. In The American Phytopathological Society, p. 235–278. Available at: http://dx.doi.org/10.1094/9780890545058.009.

Madden, L. V., Hughes, G., and van den Bosch, F. 2007c. Temporal analysis i: Quantifying and comparing epidemics. In The American Phytopathological Society, p. 63–116. Available at: http://dx.doi.org/10.1094/9780890545058.004.

Madden, L. V., Hughes, G., and van den Bosch, F. 2007d. The study of plant disease epidemics. The American Phytopathological Society. Available at: http://dx.doi.org/10.1094/9780890545058.

Madden, L. V., and Paul, P. A. 2009. Assessing Heterogeneity in the Relationship Between Wheat Yield and Fusarium Head Blight Intensity Using Random-Coefficient Mixed Models. Phytopathology®. 99:850–860 Available at: http://dx.doi.org/10.1094/PHYTO-99-7-0850.

Madden, L. V., and Paul, P. A. 2011. Meta-Analysis for Evidence Synthesis in Plant Pathology: An Overview. Phytopathology®. 101:16–30 Available at: http://dx.doi.org/10.1094/PHYTO-03-10-0069.

Malaker, P. K., Barma, N. C. D., Tiwari, T. P., Collis, W. J., Duveiller, E., Singh, P. K., et al. 2016. First Report of Wheat Blast Caused by Magnaporthe oryzae Pathotype triticum in Bangladesh. Plant Disease. 100:2330–2330 Available at: http://dx.doi.org/10.1094/pdis-05-16-0666-pdn.

Mikaberidze, A., Mundt, C. C., and Bonhoeffer, S. 2015. Data from: Invasiveness of plant pathogens depends on the spatial scale of host distribution. Available at: http://datadryad.org/stash/dataset/doi:10.5061/dryad.f2j8s.

Moran, P. A. P. 1950. Notes on continuous stochastic phenomena. Biometrika. 37:17.

Moreira, R. R., Silva Silveira Duarte, H. da, and De Mio, L. L. M. 2018. Improving accuracy, precision and reliability of severity estimates of Glomerella leaf spot on apple leaves using a new standard area diagram set. European Journal of Plant Pathology. 153:975–982 Available at: http://dx.doi.org/10.1007/s10658-018-01610-0.

Mumford, J. D., and Norton, G. A. 1984. Economics of Decision Making in Pest Management. Annual Review of Entomology. 29:157–174 Available at: http://dx.doi.org/10.1146/annurev.en.29.010184.001105.

Mundt, C. C., Ahmed, H. U., Finckh, M. R., Nieva, L. P., and Alfonso, R. F. 1999. Primary Disease Gradients of Bacterial Blight of Rice. Phytopathology®. 89:64–67 Available at: http://dx.doi.org/10.1094/phyto.1999.89.1.64.

Nelson, S. C. 1996. A simple analysis of disease foci. Phytopathology. 86:432–439.

Nutter, F. W., and Esker, P. D. 2006. The Role of Psychophysics in Phytopathology: The WeberFechner Law Revisited. European Journal of Plant Pathology. 114:199–213 Available at: http://dx.doi.org/10.1007/s10658-005-4732-9.

Nutter, F. W., Esker, P. D., and Netto, R. A. C. 2006. Disease Assessment Concepts and the Advancements Made in Improving the Accuracy and Precision of Plant Disease Data. European Journal of Plant Pathology. 115:95–103 Available at: http://dx.doi.org/10.1007/s10658-005-1230-z.

Nutter, F., Teng, P., and Royer, M. 1993. Terms and concepts for yield, crop loss, and disease thresholds. Plant Disease. 77:193–211 Available at: http://doi.org/10.1094/PD-77-211.

Olivoto, T. 2022. Lights, camera, pliman! An R package for plant image analysis. Methods in Ecology and Evolution. 13:789–798 Available at: http://dx.doi.org/10.1111/2041-210X.13803.

Olivoto, T., Andrade, S. M. P., and M. Del Ponte, E. 2022. Measuring plant disease severity in R: introducing and evaluating the pliman package. Tropical Plant Pathology. 47:95–104 Available at: http://dx.doi.org/10.1007/s40858-021-00487-5.

Onofri, A., Piepho, H.-P., and Kozak, M. 2018. Analysing censored data in agricultural research: A review with examples and software tips. Annals of Applied Biology. 174:3–13 Available at: http://dx.doi.org/10.1111/aab.12477.

Parker, S. K., Nutter, F. W., and Gleason, M. L. 1997. Directional Spread of Septoria Leaf Spot in Tomato Rows. Plant Disease. 81:272–276 Available at: http://dx.doi.org/10.1094/pdis.1997.81.3.272.

Pedigo, L. P., Hutchins, S. H., and Higley, L. G. 1986. Economic Injury Levels in Theory and Practice. Annual Review of Entomology. 31:341–368 Available at: http://dx.doi.org/10.1146/annurev.en.31.010186.002013.

Pereira, W. E. L., Andrade, S. M. P. de, Del Ponte, E. M., Esteves, M. B., Canale, M. C., Takita, M. A., et al. 2020. Severity assessment in the Nicotiana tabacum-Xylella fastidiosa subsp. pauca pathosystem: design and interlaboratory validation of a standard area diagram set. Tropical Plant Pathology. 45:710–722 Available at: http://dx.doi.org/10.1007/s40858-020-00401-5.

Reis, E. M., Hoffmann, L. L., and Blum, M. 2002. Modelo de ponto crítico para estimar os danos causados pelo oídio em cevada. Fitopatologia Brasileira. 27:644–646.

Sackett, K. E., and Mundt, C. C. 2005. Primary Disease Gradients of Wheat Stripe Rust in Large Field Plots. Phytopathology®. 95:983–991 Available at: http://dx.doi.org/10.1094/PHYTO-95-0983.

Savary, S., Teng, P. S., Willocquet, L., and Nutter, F. W. 2006. Quantification and Modeling of Crop Losses: A Review of Purposes. Annual Review of Phytopathology. 44:89–112 Available at: http://dx.doi.org/10.1146/annurev.phyto.44.070505.143342.

Savary, S., Willocquet, L., Pethybridge, S. J., Esker, P., McRoberts, N., and Nelson, A. 2019. The global burden of pathogens and pests on major food crops. Nature Ecology & Evolution. 3:430–439 Available at: http://dx.doi.org/10.1038/s41559-018-0793-y.

Scott, P. R., and Hollins, T. W. 1974. Effects of eyespot on the yield of winter wheat. Annals of Applied Biology. 78:269–279 Available at: http://dx.doi.org/10.1111/j.1744-7348.1974.tb01506.x.

Shah, D. A., and Madden, L. V. 2004. Nonparametric Analysis of Ordinal Data in Designed Factorial Experiments. Phytopathology®. 94:33–43 Available at: http://dx.doi.org/10.1094/PHYTO.2004.94.1.33.

Shrout, P. E., and Fleiss, J. L. 1979. Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin. 86:420–428 Available at: http://dx.doi.org/10.1037/0033-2909.86.2.420.

Simko, I., and Piepho, H.-P. 2012. The Area Under the Disease Progress Stairs: Calculation, Advantage, and Application. Phytopathology®. 102:381–389 Available at: http://dx.doi.org/10.1094/phyto-07-11-0216.

Tembo, B., Mulenga, R. M., Sichilima, S., M’siska, K. K., Mwale, M., Chikoti, P. C., et al. 2020. Detection and characterization of fungus (Magnaporthe oryzae pathotype Triticum) causing wheat blast disease on rain-fed grown wheat (Triticum aestivum L.) in Zambia ed. Zonghua Wang. PLOS ONE. 15:e0238724 Available at: http://dx.doi.org/10.1371/journal.pone.0238724.

Thresh, J. M. 1998. In memory of James Edward Vanderplank 19091997. Plant Pathology. 47:114–115 Available at: http://dx.doi.org/10.1046/j.1365-3059.2998.00220.x.

Vanderplank, J. 1963. Plant disease epidemics and control. Elsevier. Available at: http://dx.doi.org/10.1016/C2013-0-11642-X.

Viechtbauer, W. 2010. Conducting Meta-Analyses inRwith themetaforPackage. Journal of Statistical Software. 36 Available at: http://dx.doi.org/10.18637/jss.v036.i03.

Wallin, J. R. 1962. Summary of recent progress in predicting late blight epidemics in United States and Canada. American Potato Journal. 39:306–312 Available at: http://dx.doi.org/10.1007/bf02862155.

Wiegand, T., and A. Moloney, K. 2004. Rings, circles, and null-models for point pattern analysis in ecology. Oikos. 104:209–229 Available at: http://dx.doi.org/10.1111/j.0030-1299.2004.12497.x.

Willbur, J. F., Fall, M. L., Bloomingdale, C., Byrne, A. M., Chapman, S. A., Isard, S. A., et al. 2018. Weather-Based Models for Assessing the Risk of Sclerotinia sclerotiorum Apothecial Presence in Soybean (Glycine max) Fields. Plant Disease. 102:73–84 Available at: http://dx.doi.org/10.1094/PDIS-04-17-0504-RE.

Xu, X.-M., and Madden, L. V. 2004. Use of SADIE statistics to study spatial dynamics of plant disease epidemics. Plant Pathology. 53:38–49 Available at: http://dx.doi.org/10.1111/j.1365-3059.2004.00949.x.

Yadav, N. V. S., Vos, S. M. de, Bock, C. H., and Wood, B. W. 2012. Development and validation of standard area diagrams to aid assessment of pecan scab symptoms on fruit. Plant Pathology. 62:325–335 Available at: http://dx.doi.org/10.1111/j.1365-3059.2012.02641.x.

Yorinori, J. T., Paiva, W. M., Frederick, R. D., Costamilan, L. M., Bertagnolli, P. F., Hartman, G. E., et al. 2005. Epidemics of Soybean Rust (Phakopsora pachyrhizi) in Brazil and Paraguay from 2001 to 2003. Plant Disease. 89:675–677 Available at: http://dx.doi.org/10.1094/PD-89-0675.

Zadoks, J. C., and Schein, R. D. 1988. James Edward Vanderplank: Maverick* and Innovator. Annual Review of Phytopathology. 26:31–37 Available at: http://dx.doi.org/10.1146/annurev.py.26.090188.000335.