Applied regional epidemiology to the inductive characterization and forecasting of blue agave gray spot (Cercospora agavicola) in Jalisco, México

Juan José Coria-Contreras, Gustavo Mora-Aguilera, María de Jesús Yañez-Morales, Gerardo Acevedo-Sánchez, Baldemar Santana-Peñaloza, Coral Mendoza-Ramos, Laura Jiménez-González, Verónica Inés Martínez-Bustamante, Dulce Cecilia García-Martínez, Ramón Rubio-Cortés

Abstract


Cercospora agavicola, causal agent of the gray spot of blue agave (Agave tequilana), is a regulated fungus under official control in states under the Tequila Denomination of Origin (TDO). This work was carried out in Jalisco, Mexico, the main TDO region, to determine the spatialtemporal epidemic inductivity of the fungus and to develop stochastic models to forecast the gray spot in order to support regional preventive programs. Monthly, from October 2016 to December 2017 the severity, incidence and number of diseased plants were evaluated in 41 plots established in commercial agave plantations of 3-4 years of age selected with weighted risk criteria in Los Altos (20), Valleys (11) and South (10). The regional epidemic inductivity of C. agavicola was heterogeneous with a greater risk for at least nine counties of Los Altos. However, low epidemic rates (0.0008-0.006 units week-1), strong restriction spread (1-4 plants), reduced annual increment of incidence (0-32 plants / 0.5 ha) and no spore capture evidenced the low parasitic fitness and reduced fungus epidemic capacity. Consequently, limited predictive capacity was found even with the best goodness of fit models (R2adj 0.51-0.60). The favorable hours (HFav) of January-April, with respect to infection, was consistent among models, so it can be used as preventive algorithm in SIVEA (www.sivea.org.mx). The regional losses, under the established epidemic parameters, were estimated between 98.01 MDD and 237 thousand US dollars. Cercosporin, a toxin associated with Cercospora genus, may be involved in atypical linear temporal progress and should be integrated in future research.

Keywords


Losses; drone; Weibull; NCBI; AUDPC; SIVEA

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References


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DOI: http://dx.doi.org/10.18781/R.MEX.FIT.1809-4

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