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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings,for Cotton Crops

American journal of Plant Sciences 2013年第11期4卷 2049-2059页

作者： Jaqueline Aguilla Pizzato dejania vieira araújo Milson Evaldo Serafim Kelly Lana araújo Rivanildo Dallacort Thiago Alexandre Santana Gílio Jair Romano Jr Vanderlei Antunes Maciel Programa de Pós-graduacao em Ambiente e Sistemas de Producao Agrícola Universidade do Estado de Mato GrossoTangaráda SerraBrasil Instituto Federal de Educacao Ciência e Tecnologia de Mato Grosso—IFMTCáceresBrasil Laboratório de Melhoramento Genético Vegetal.Universidade do Estado de Mato Grosso CáceresBrasil Programa de Pós-graduacao em Genética e Melhoramento de Plantas Universidade do Estado de Mato GrossoTangaráda SerraBrasil Laboratório de Fitopatologia Universidade do Estado de Mato GrossoTangaráda SerraBrasil

The objective of this work was to evaluate the progress of the areolate mildew of cotton under different soil cover and spacing conditions. The experiment was carried out using randomized blocks and a 2 × 3 factorial design, with two spacings (0.45 m and 0.90 m) and three soil covers (no cover, Pennisetum glaucum and Crotalaria spectabilis) with four replications. The plants were inoculated with R. areola, sixty DAS. A total of 14 evaluations of disease severity were performed. At the lower, middle and upper thirds of plants, a diagram scale with nine levels of severity was used and the resulting data were converted into the AUDPC. Gompertz, logistic, and monomolecular mathematical models were tested in the disease severity curves for each third. Agronomics characteristics were evaluated as well. Significant differences of AUDPC were found for the cotton plants thirds, and the middle third was the highest AUDPC. Significant difference for the lower and upper thirds, whose AUDPC were highest on 0.90 m spacing, was observed too. The disease progress curves of the thirds did not fit the tested models. Significant results to the both covers situations, where the treatments grown on crotalária cover and without cover had highest AUDPC, were evidenced. The treatments with C. spectabilis cover were taller than other treatments. Significant data were observed for the cover crops used and in the treatments grown at 0.90 m spacing, to residual cover and crop yield, respectively.

关键词： Pennisetum glaucum Crotalaria spectabilis Areolate Mildew High-Density Crops and No-Till

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

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American journal of Plant Sciences 2014年第15期5卷 2472-2479页

作者： Jaqueline A.Pizzato dejania V.araujo Edineia A.S.Galvanin Jair Romano Júnior Andrea N.A.Matos Michelle Vecchi Francieli D.Zavislak Center for Research Studies and Agro-Environmental Development(CPEDA)Mato Grosso State UniversityTangara da SerraBrazil Graduate Program in Environment and Agricultural Production Systems Mato Grosso State UniversityTangara da SerraBrazil Graduate Program in Environment and Agricultural Production Systems Mato Grosso State UniversityBarra BugresBrazil Biological Sciences Course Mato Grosso State UniversityTangara da SerraBrazil Agronomy Course Mato Grosso State UniversityTangara da SerraBrazil

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

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