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dc.creatorArroyo Esquivel, Jorge
dc.creatorSánchez Peña, Fabio Ariel
dc.creatorBarboza Chinchilla, Luis Alberto
dc.description.abstractCoffee rust is one of the main diseases that affect coffee plantations worldwide (Cressey, 2013 [10]). This causes an important economic impact in the coffee production industry in countries where coffee is an important part of the economy. A common method for combating this disease is using copper hydroxide as a fungicide, which can have damaging effects both on the coffee tree and on human health (Haddad et al., 2013 [13]). A novel method for biological control of coffee rust using bacteria has been proven to be an effective alternative to copper hydroxide fungicides as anti-fungal compounds (Haddad et al., 2009 [12]). In this paper, we develop and explore a spatial stochastic model for this interaction in a coffee plantation. We analyze equilibria for specific control strategies, as well as compute the basic reproductive number, R0, of individual coffee trees, conditions for local and global stability under specific conditions, parameter estimation of key parameters, as well as sensitivity analysis, and numerical experiments under local and global control strategies for key scenarios.es_ES
dc.sourceMathematical Biosciences, vol.307, pp.13-24es_ES
dc.subjectInfection modeles_ES
dc.subjectBiological controles_ES
dc.subjectSpatial modeles_ES
dc.subjectCoffee rustes_ES
dc.subjectParameter estimationes_ES
dc.subjectSensitivity analysises_ES
dc.titleInfection model for analyzing biological control of coffee rust using bacterial anti-fungal compoundses_ES
dc.typeartículo científico
dc.description.procedenceUCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Matemáticaes_ES

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