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Phakopsora Pachyrhizi) in MEXICO Yáñez-López et al. Distribution for soybean rust in Mexico 2(6):291-302,2015 POTENTIAL DISTRIBUTION ZONES FOR SOYBEAN RUST (Phakopsora pachyrhizi) IN MEXICO Zonas de distribución potencial para roya de la soya (Phakopsora pachyrhizi) en México 1∗Ricardo Yáñez-López, 1María Irene Hernández-Zul, 2Juan Ángel Quijano-Carranza, 3Antonio Palemón Terán-Vargas, 4Luis Pérez-Moreno, 5Gabriel Díaz-Padilla, 1Enrique Rico-García 1Cuerpo Académico de Ingeniería de Biosistemas, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Centro Universitario, Cerro de las Campanas s/n, CP. 76010, Querétaro, México. [email protected] 2Campo Experimental Bajío, (CEBAJ-INIFAP). Km 6.5 Carretera Celaya-San Miguel de Allende. Celaya, Guanajuato, México. 3Campo Experimental las Huastecas, Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias, Carretera Tampico-Mante Km. 55, Villa Cuauhtémoc, Tamaulipas, México. 4Universidad de Guanajuato, Instituto de Ciencias Agricolas, Apdo. Postal 311. Irapuato, Guanajuato, México. 5Campo Experimental Cotaxtla. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias. Km. 3.5 Carretera Xalapa-Veracruz. Colonia Ánimas. Xalapa, Veracruz. Mexico. Artículo cientíco recibido: 18 de julio de 2014, aceptado: 16 de febrero de 2015 ABSTRACT. Asian Soybean Rust is one of the most important soybean diseases. Since the past decade, some im- portant soybean production areas in America, like Brazil and the United States of America, have been aected by this disease. Due to the seriousness of this threaten, in 2009, the Mexican government implemented a surveillance program based on the installation and monitoring of sentinel plots in areas planted with crops considered as susceptible hosts for this organism. In order to support the strategy to prevent the establishment of the disease in Mexico, in the present study the potential distribution of the organism was evaluated considering the following criteria: 1) the suitability of climatic conditions for soybean rust; 2) the extent of the cultivated areas with susceptible hosts, and 3) the inoculums availability. Favorable days for Asian soybean rust infection were calculated with a simple model which uses climatic variables as inputs. The model was applied to classify the agricultural areas of the country according to the probability of occurrence of favorable conditions for infection of soybean rust in the summer and winter growing seasons. The Results indicate that in the summer the greatest number of favorable days for infection occurs, mainly in Tamaulipas, Veracruz, Yucatan, Chiapas, Oaxaca, Guerrero, Michoacan, Jalisco, Nayarit, Sinaloa and Sonora. In the winter, the favorable days decrease considerably. Based on these results we conclude that the probability that the Asian soybean rust would be overwintering in Mexico is low. Key words: Phakopsora pachyrhizi, soybean, soybean rust, risk analysis Resumen. La roya asiática es una de las enfermedades más importantes para el cultivo de la soya. Desde la década pasada zonas productoras de soya en América en Brasil y Estados Unidos se han visto afectadas por esta enfermedad. Debido a la gravedad de esta amenaza, en el 2009 el Gobierno mexicano puso en marcha un programa de vigilancia basado en la instalación y seguimiento de parcelas centinelas en zonas con cultivos hospederos. Con el n de mejorar la delimitación de las zonas de riesgo para esta enfermedad se evaluó el potencial de distribución en México. Para ello, se tomó en cuenta factores que pueden causar una epidemia: 1) la idoneidad de las condiciones climáticas para la roya de la soya, 2) supercie sembrada con cultivos hospederos y 3) cantidad de inóculo. Para esto se cuanticaron los días favorables para la infección utilizando un modelo con datos meteorológicos diarios de temperatura, precipitación y humedad relativa de todo el país, para clasicar las zonas agrícolas de acuerdo a la probabilidad de ocurrencia de condiciones favorables para la infección de roya asiática en verano e invierno. Los resultados indicaron que en verano se tienen más días con condiciones favorables para la infección en los estados de Tamaulipas, Veracruz, Yucatán, Chiapas, Oaxaca, Guerrero, Michoacán, Jalisco, Nayarit, Sinaloa y Sonora. En temporada de invierno el número de www.ujat.mx/era 291 Yáñez-López et al. Distribution for soybean rust in Mexico 2(6):291-302,2015 días favorables disminuyeron de forma considerable. Basado en los resultados podemos concluir que la probabilidad de que la roya asiática hiberne en México es baja. Key words: Phakopsora pachyrhizi, soya, roya soya, análisis de riesgo INTRODUCTION important host and could play an important role in the pathogen spread because of its extensive area of Soybean rust (SBR) is one of the most cultivation in Mexico. destructive diseases of soybeans in Asia and America According to the epidemiological disease (Christiano and Scherm 2007). Yield losses caused triangle, three factors determine the occurrence of by SBR range from 10 to 90 % (Sharma and a disease: the environment, a susceptible host, and Gupta 2006) depending on the host susceptibility, the pathogen. These components interactively in- inoculum quantity, and environmental conditions uence the complex and dynamic nature of the (Twizeyimana et al. 2011). The pathogen respon- disease (Bonde et al. 2007). Moreover, evi- sible for SBR is the fungus Phakopsora pachyrhizi dence shows that epidemic components, environ- Syd. & P. Syd that was rst reported in Japan in mental conditions and meteorological factors have 1902 (Park et al. 2008). For decades, this disease the greatest roles in aecting SBR epidemiology was reported only in the eastern hemisphere, but (Melching et al. 1989, Isard et al. 2006, Bonde in the last twenty years, the fungus was detected et al. 2007). Thus, meteorological factors aect in new areas (Bonde et al. 2007). In 1994, the the host and pathogen directly or indirectly, which disease was located in Hawaii, and the rst report results in complex interactions. For P. pachyrhizi, of the disease in Africa was in Uganda by the end of specic temperature and humidity conditions pro- 1996 (Levy 2005). In 2001, P. pachyrhizi was found vide a stimulus to which the fungus responds at infecting soybeans in Paraguay and Brazil and one specic stages of its life cycle (Kochman 1979). year later was detected in Argentina (Rossi 2003). In the characterization of P. pachyrhizi, By 2004, the fungus was reported in Colombia, important advances have been achieved. The Ecuador and the United States (Pan et al. 2006), processes of spore germination, infection, la- and in 2005, it was reported in Mexico, infecting tent period, lesion expansion and sporulation are soybeans and yam beans (Carcamo-Rodríguez and inuenced by meteorological variables (Marchetti et Aguilar-Ríos 2006, Yáñez-Morales et al. 2009). In al. 1975, 1976, Kochman 1979, Melching et al. Mexico, yield losses caused by SBR range from 25 1989). In general, moisture (rainfall and dew) and to 80 % (Terán-Vargas et al. 2007) in both crops, temperature aect important features of disease be- which makes chemical control necessary. havior such as successful initial establishment, infec- Phakopsora pachyrhizi is an obligate parasite. tion eciency, and the rate of development of the Therefore, fungal survival depends on continued epidemic (Bonde et al. 2007). Pest risk analysis production of uredospores on a suitable host (Ed- (PRA), based on science, is used to estimate the wards and Bonde 2011). Phakopsora pachyrhizi likelihood of entry, establishment and spread of a naturally infects 95 species from 42 genera of harmful organism in a dened area, and includes legumes (Slaminko et al. 2008), but the limits of an impact evaluation (Pivonia et al. 2005, Pivonia its host range are unknown. The reported hosts and Yang 2006, Gutierrez and Ponti 2011). The for this pathogen include soybeans (Glycine max) use of modeling techniques in PRA is an emerging and yam beans (Pachyrhizus erosus). When these trend that assists the search for a more comprehen- crops are severely infected, plants show early defo- sive and quantitative analysis. The modeling ap- liation and a reduction in green leaf area, which di- proaches to predict SBR epidemics vary from sim- rectly aects yield (Hartman et al. 1991, Yang et al. ple equations, such as linear regression, to com- 1992). Dry beans (Phaseolus vulgaris) are another plex algorithms such as neural networks and mecha- www.ujat.mx/era 292 Yáñez-López et al. Distribution for soybean rust in Mexico 2(6):291-302,2015 nistic models of population dynamics. According reported, the positive detections of SBR in Mexico to Del Ponte et al. (2006a), SBR modeling is were integrated. The host availability was incor- classied into two groups, simulation and empiri- porated using statistical data of planted areas with cal models. The simulation models are based on the susceptible hosts in summer and winter seasons. concepts derived from a pathosystem and reproduce Subsequently, the climate analysis of potential dis- biological processes such as the disease cycle, dis- tribution zones for soybean rust was performed using persion, and airborne inoculum deposition over long the SIMPEC software developed by Quijano et al. distances. These models are used to estimate the (2011), which integrated a daily climatic time series likelihood of entry of a pest into a region and the for Mexico and a platform to construct and cali- severity of damage that may be caused to hosts brate crop and pest models. With the purpose to (Kim et al. 2005, Pan et al. 2006, Pivonia and evaluate the suitability for P. pachyrhizi in zones Yang 2006). The empirical models are typically where the susceptible hosts were planted, it was as- constructed through statistical relationships of ex- sumed that the inoculum was not a limiting factor. planatory variables that employ eld data and are The favorable days for infection were determined built using techniques such linear and nonlinear re- through the analysis of daily meteorological data of gression, neural networks and fuzzy logic (Reis et temperature, rainfall, and relative humidity (RH).
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