Geostatistics as a Methodology for Studying the Spatiotemporal Dynamics of Ramularia areola in Cotton Crops  

作　　者：Jaqueline A.Pizzato Dejania V.Araujo Edineia A.S.Galvanin Jair Romano Júnior Andrea N.A.Matos Michelle Vecchi Francieli D.Zavislak 

机构地区：[1]Center for Research,Studies and Agro-Environmental Development(CPEDA),Mato Grosso State University,Tangara da Serra,Brazil [2]Graduate Program in Environment and Agricultural Production Systems,Mato Grosso State University,Tangara da Serra,Brazil [3]Graduate Program in Environment and Agricultural Production Systems,Mato Grosso State University,Barra Bugres,Brazil [4]Biological Sciences Course,Mato Grosso State University,Tangara da Serra,Brazil [5]Agronomy Course,Mato Grosso State University,Tangara da Serra,Brazil

出　　处：《American Journal of Plant Sciences》2014年第15期2472-2479,共8页美国植物学期刊（英文）

摘　　要：Geostatistics as a methodology for studying the spatiotemporal dynamics of Ramularia areola in cotton crops. Geostatistics is a tool that has been used to study plant pathology, by modeling the spatiotemporal pattern of diseases, generating hypotheses about their epidemiological aspects in order to use tactics and strategies of rational control. The objective of this study was to use geostatistics to study the spatiotemporal dynamics of Ramularia areola in cotton crops. The experiment was conducted at the experimental area of Mato Grosso State University-Tangará da Serra campus, and arranged in a 2 × 3 factorial design, with randomized blocks, with two spaicngs (0.45 and 0.90 cm) and three conditions of soil coverage (no cover, P. glaucum and C. spectabilis). Geostatistical analysis of data was performed using data from temporal and spatial progress of R. areola, obtained through assessments of the incidence and severity of the disease in plants, and spatial dependence, and analyzed using semivariogram fittings. Through the isotropic exponential semivariogram model, it was possible to check the distribution pattern and spatial dependence of Ramularia leaf spot. Spatial dependence was observed for the disease—moderate to strong for most data evaluated. The pathogen spread from the primary source of inoculum, from the center portion towards the edges, forming foci originating from a source of secondary inoculum.Geostatistics as a methodology for studying the spatiotemporal dynamics of Ramularia areola in cotton crops. Geostatistics is a tool that has been used to study plant pathology, by modeling the spatiotemporal pattern of diseases, generating hypotheses about their epidemiological aspects in order to use tactics and strategies of rational control. The objective of this study was to use geostatistics to study the spatiotemporal dynamics of Ramularia areola in cotton crops. The experiment was conducted at the experimental area of Mato Grosso State University-Tangará da Serra campus, and arranged in a 2 × 3 factorial design, with randomized blocks, with two spaicngs (0.45 and 0.90 cm) and three conditions of soil coverage (no cover, P. glaucum and C. spectabilis). Geostatistical analysis of data was performed using data from temporal and spatial progress of R. areola, obtained through assessments of the incidence and severity of the disease in plants, and spatial dependence, and analyzed using semivariogram fittings. Through the isotropic exponential semivariogram model, it was possible to check the distribution pattern and spatial dependence of Ramularia leaf spot. Spatial dependence was observed for the disease—moderate to strong for most data evaluated. The pathogen spread from the primary source of inoculum, from the center portion towards the edges, forming foci originating from a source of secondary inoculum.

关 键 词：Ramularia areola Spatial Dependence Isotropic Exponential Semivariogram KRIGING 

分 类 号：R73[医药卫生—肿瘤]