A mathematical model for frogeye leaf spot epidemics in soybean

Chayu Yang; Jin Wang; Chayu Yang; Jin Wang

doi:10.3934/mbe.2024048

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 1: 1144-1166. doi: 10.3934/mbe.2024048

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Research article

A mathematical model for frogeye leaf spot epidemics in soybean

Chayu Yang ¹,
Jin Wang ^{2
,
,}

1.
Department of Mathematics, University of Nebraska-Lincoln, 1400 R St., Lincoln, NE 68588, USA
2.
Department of Mathematics, University of Tennessee at Chattanooga, 615 McCallie Avenue, Chattanooga, TN 37403, USA

Academic Editor: De Li Liu

Received: 26 September 2023 Revised: 24 November 2023 Accepted: 11 December 2023 Published: 25 December 2023

We propose a new mathematical model based on differential equations to investigate the transmission and spread of frogeye leaf spot, a major soybean disease caused by the fungus Cercospora sojina. The model incorporates the primary and secondary transmission routes of the disease as well as the intrinsic dynamics of the pathogen in the contaminated soil. We conduct detailed equilibrium and stability analyses for this model using theories of dynamical systems. We additionally conduct numerical simulations to verify the analytical predictions and to implement the model for a practical application.
- frogeye leaf spot,
- soybean disease,
- plant pathology,
- epidemic modeling and simulation
Citation: Chayu Yang, Jin Wang. A mathematical model for frogeye leaf spot epidemics in soybean[J]. Mathematical Biosciences and Engineering, 2024, 21(1): 1144-1166. doi: 10.3934/mbe.2024048

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Abstract

We propose a new mathematical model based on differential equations to investigate the transmission and spread of frogeye leaf spot, a major soybean disease caused by the fungus Cercospora sojina. The model incorporates the primary and secondary transmission routes of the disease as well as the intrinsic dynamics of the pathogen in the contaminated soil. We conduct detailed equilibrium and stability analyses for this model using theories of dynamical systems. We additionally conduct numerical simulations to verify the analytical predictions and to implement the model for a practical application.

References

[1]	J. Barro, D. Neves, E. D. Ponte, C. Bradley, Frogeye leaf spot caused by Cercospora sojina: A review, Trop. Plant Pathol., 48 (2023), 363–374. https://doi.org/10.1007/s40858-023-00583-8 doi: 10.1007/s40858-023-00583-8
[2]	M. Mian, A. Missaoui, D. Walker, D. Phillips, H. Boerma, Frogeye leaf spot of soybean: A review and proposed race designations for isolates of Cercospora sojina Hara, Crop Sci., 48 (2008), 14–24. https://doi.org/10.2135/cropsci2007.08.0432 doi: 10.2135/cropsci2007.08.0432
[3]	A. Mengistu, N. Kurtzweil, C. Grau, First report of frogeye leaf spot (Cercospora sojina) in Wisconsin, Plant Dis., 86 (2002), 1272. https://doi.org/10.1094/PDIS.2002.86.11.1272B doi: 10.1094/PDIS.2002.86.11.1272B
[4]	D. Neves, M. Chilvers, T. Jackson-Ziems, D. Malvick, C. Bradley, Resistance to quinone outside inhibitor fungicides conferred by the G143A mutation in Cercospora sojina (causal agent of frogeye leaf spot) isolates from Michigan, Minnesota, and Nebraska soybean fields, Plant Health Prog., 21 (2020), 230–231. https://doi.org/10.1094/PHP-06-20-0052-BR doi: 10.1094/PHP-06-20-0052-BR
[5]	X. Yang, M. Uphoff, S. Sanogo, Outbreaks of soybean frogeye leaf spot in Iowa, Plant Dis., 85 (2001), 443. https://doi.org/10.1094/PDIS.2001.85.4.443A doi: 10.1094/PDIS.2001.85.4.443A
[6]	K. Dashiell, C. Akem, Yield losses in soybeans from frogeye leaf spot caused by Cercospora sojina, Crop Prot., 10 (1991), 465–468. https://doi.org/10.1016/S0261-2194(91)80134-2 doi: 10.1016/S0261-2194(91)80134-2
[7]	M. Mian, H. Boerma, D. Phillips, M. Kenty, G. Shannon, E. Shipe, et al., Performance of frogeye leaf spot–resistant and –susceptible near-isolines of soybean, Plant Dis., 82 (1998), 1017–1021. https://doi.org/10.1094/PDIS.1998.82.9.1017 doi: 10.1094/PDIS.1998.82.9.1017
[8]	M. Sepulcri, R. Moschini, M. Carmona, Soybean frogeye leaf spot (Cercospora sojina): first weather-based prediction models developed from weather station and satellite data, Adv. Appl. Agric. Sci., 3 (2015), 1–13.
[9]	T. Allen, C. Bradley, A. Sisson, E. Byamukama, M. Chilvers, C. Coker, et al., Soybean yield loss estimates due to diseases in the United States and Ontario, Canada from 2010 to 2014, Plant Health Prog., 18 (2017), 19–27. https://doi.org/10.1094/PHP-RS-16-0066 doi: 10.1094/PHP-RS-16-0066
[10]	C. Bradley, T. Allen, A. Sisson, G. Bergstrom, K. Bissonnette, J. Bond, et al., Soybean yield loss estimates due to diseases in the United States and Ontario, Canada from 2015 to 2019, Plant Health Prog., 22 (2021), 483–495. https://doi.org/10.1094/PHP-01-21-0013-RS doi: 10.1094/PHP-01-21-0013-RS
[11]	C. Cruz, A. Dorrance, Characterization and survival of Cercospora sojina in Ohio, Plant Health Prog., 10 (2009), 17. https://doi.org/10.1094/PHP-2009-0512-03-RS doi: 10.1094/PHP-2009-0512-03-RS
[12]	K. Wise, M. Newman, Frogeye leaf spot, in Compendium of Soybean Diseases and Pests (eds. G. Hartman, J. Rupe, E. Sikora, L. Domier, J. Davis and K. Steffey), American Phytopathological Society, St. Paul, (2015), 43–45.
[13]	N. Osherov, G. May, The molecular mechanisms of conidial germination, FEMS Microbiol. Lett., 199 (2001), 153–160. https://doi.org/10.1111/j.1574-6968.2001.tb10667.x doi: 10.1111/j.1574-6968.2001.tb10667.x
[14]	P. Nazarov, D. Baleev, M. Ivanova, L. Sokolova, M. Karakozova, Infectious plant diseases: Etiology, current status, problems and prospects in plant protection, Acta Nat., 12 (2020), 46–59. https://doi.org/10.32607/actanaturae.11026 doi: 10.32607/actanaturae.11026
[15]	J. van der Plank, Plant Diseases: Epidemics and Control, Academic Press, New York and London, 1963.
[16]	C. Campbell, L. Madden, Introduction to Plant Disease Epidemiology, John Wiley & Sons, New York, 1990.
[17]	L. Contreras-Medina, I. Torres-Pacheco, R. Guevara-González, R. Romero-Troncoso, I. Terol-Villalobos, R. Osornio-Rios, Mathematical modeling tendencies in plant pathology, Afr. J. Biotechnol., 8 (2009), 7399–7408.
[18]	M. Jeger, The use of mathematical models in plant disease epidemiology, Sci. Hortic., 35 (1984), 11–27.
[19]	D. Jones, The Epidemiology of Plant Diseases, Kluwer Academic Publishers, Dordrecht, 1998.
[20]	J. Kranz, Epidemics of Plant Diseases: Mathematical Analysis and Modeling, Springer-Verlag, Berlin, 1990.
[21]	L. Madden, Botanical epidemiology: some key advances and its continuing role in disease management, Eur. J. Plant Pathol., 115 (2006), 3–23. https://doi.org/10.1007/s10658-005-1229-5 doi: 10.1007/s10658-005-1229-5
[22]	A. van Maanen, X. Xu, Modelling plant disease epidemics, Eur. J. Plant Pathol., 109 (2003), 669–682. https://doi.org/10.1023/A:1026018005613 doi: 10.1023/A:1026018005613
[23]	G. Agrios, Plant Pathology, Elsevier Academic Press, London, 2005.
[24]	X. Xu, Modelling and interpreting disease progress in time, in The Epidemiology of Plant Disease, Springer, Dordrecht, (2006), 215–238. https://doi.org/10.1007/1-4020-4581-6_8
[25]	M. Jeger, S. Viljanen-Rollinson, The use of the area under the disease-progress curve (AUDPC) to assess quantitative disease resistance in crop cultivars, Theor. Appl. Genet., 102 (2001), 32–40. https://doi.org/10.1007/s001220051615 doi: 10.1007/s001220051615
[26]	T. Ji, I. Salotti, C. Dong, M. Li, V. Rossi, Modeling the effects of the environment and the host plant on the ripe rot of grapes, caused by the Colletotrichum species, Plants, 10 (2021), 2288. https://doi.org/10.3390/plants10112288 doi: 10.3390/plants10112288
[27]	V. Rossi, T. Caffi, S. Giosuè, R. Bugiani, A mechanistic model simulating primary infections of downy mildew in grapevine, Ecol. Modell., 212 (2008), 480–491. https://doi.org/10.1016/j.ecolmodel.2007.10.046 doi: 10.1016/j.ecolmodel.2007.10.046
[28]	I. Salotti, V. Rossi, A mechanistic weather-driven model for Ascochyta rabiei infection and disease development in chickpea, Plants, 10 (2021), 464. https://doi.org/10.3390/plants10030464 doi: 10.3390/plants10030464
[29]	L. Madden, M. Jeger, F. van den Bosch, A theoretical assessment of the effects of vector-virus transmission mechanism on plant virus disease epidemics, Phytopathology, 90 (2000), 576–594. https://doi.org/10.1094/PHYTO.2000.90.6.576 doi: 10.1094/PHYTO.2000.90.6.576
[30]	D. Daley, J. Gani, Epidemic Modeling: An Introduction, Cambridge University Press, New York, 2005.
[31]	W. Kermack, A. McKendrick, Contributions to the mathematical theory of epidemics – Ⅰ, Proc. R. Soc., 115A (1927), 700–721.
[32]	H. Hethcote, The mathematics of infectious diseases, SIAM Rev., 42 (2000), 599–653. https://doi.org/10.1137/S0036144500371907 doi: 10.1137/S0036144500371907
[33]	P. O. Lolika, S. Mushayabasa, C. P. Bhunu, C. Modnak, J. Wang, Modeling and analyzing the effects of seasonality on brucellosis infection, Chaos, Solitons Fractals, 104 (2017), 338–349. https://doi.org/10.1016/j.chaos.2017.08.027 doi: 10.1016/j.chaos.2017.08.027
[34]	J. Wang, Mathematical models for cholera dynamics–A review, Microorganisms, 10 (2022), 2358. https://doi.org/10.3390/microorganisms10122358 doi: 10.3390/microorganisms10122358
[35]	C. Yang, J. Wang, On the intrinsic dynamics of bacteria in waterborne infections, Math. Biosci., 296 (2018), 71–81. https://doi.org/10.1016/j.mbs.2017.12.005 doi: 10.1016/j.mbs.2017.12.005
[36]	J. Yang, C. Modnak, J. Wang, Dynamical analysis and optimal control simulation for an age-structured cholera transmission model, J. Franklin Inst., 356 (2019), 8438–8467. https://doi.org/10.1016/j.jfranklin.2019.08.016 doi: 10.1016/j.jfranklin.2019.08.016
[37]	A. Mengistu, H. Kelly, N. Bellaloui, P. Arelli, K. Reddy, A. Wrather, Tillage, fungicide, and cultivar effects on frogeye leaf spot severity and yield in soybean, Plant Dis., 98 (2014), 1476–1484. https://doi.org/10.1094/PDIS-12-13-1268-RE doi: 10.1094/PDIS-12-13-1268-RE
[38]	C. Huang, S. Ma, C. Zhu, Z. Zhang, M. Guo, B. Li, et al., Study on forecasting the epidemiology of frogeye leaf spot and yield loss in soyabean, Soybean Sci., 17 (1998), 48–52.
[39]	M. T. Li, Z. Jin, G. Q. Sun, J. Zhang, Modeling direct and indirect disease transmission using multi-group model, J. Math. Anal. Appl., 446 (2017), 1292–1309. https://doi.org/10.1016/j.jmaa.2016.09.043 doi: 10.1016/j.jmaa.2016.09.043
[40]	G. Wang, J. Yang, X. Li, An age-space structured cholera model linking within- and between-host dynamics with Neumann boundary condition, Z. Angew. Math. Phys., 74 (2023), 14. https://doi.org/10.1007/s00033-022-01910-w doi: 10.1007/s00033-022-01910-w
[41]	J. Yang, P. Jia, J. Wang, Z. Jin, Rich dynamics of a bidirectionally linked immuno-epidemiological model for cholera, J. Math. Biol., 87 (2023), 71. https://doi.org/10.1007/s00285-023-02009-0 doi: 10.1007/s00285-023-02009-0
[42]	P. van den Driessche, J. Watmough, Reproduction number and subthreshold endemic equilibria for compartment models of disease transmission, Math. Biosci., 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
[43]	J. LaSalle, The stability of dynamical systems, in CBMS-NSF Regional Conference Series in Applied Mathematics, SIAM, Philadelphia, 1976.
[44]	H. Freedman, S. Ruan, M. Tang, Uniform persistence and flows near a closed positively invariant set, J. Dyn. Differ. Equations, 6 (1994), 583–600. https://doi.org/10.1007/BF02218848 doi: 10.1007/BF02218848
[45]	Z. Shuai, P. van den Driessche, Global stability of infectious disease models using Lyapunov functions, SIAM J. Appl. Math., 73 (2013), 1513–1532. https://doi.org/10.1137/120876642 doi: 10.1137/120876642
[46]	M. Li, J. Graef, L. Wang, J. Karsai, Global dynamics of a SEIR model with varying total population size, Math. Biosci., 160 (1999), 191–213. https://doi.org/10.1016/S0025-5564(99)00030-9 doi: 10.1016/S0025-5564(99)00030-9
[47]	M. Castro, R. de Boer, Testing structural identifiability by a simple scaling method, PLoS Comput. Biol., 16 (2020), e1008248. https://doi.org/10.1371/journal.pcbi.1008248 doi: 10.1371/journal.pcbi.1008248
[48]	H. Miao, X. Xia, A. Perelson, H. Wu, On identifiability of nonlinear ODE models and applications in viral dynamics, SIAM Rev., 53 (2011), 3–39. https://doi.org/10.1137/090757009 doi: 10.1137/090757009

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