Geostatistics as a Methodology for Studying the Spatiotemporal Dynamics of <i>Ramularia areola</i>in Cotton Crops

• 作者: ?ndrea N. A. Matos Dejania V. Araújo Edinéia A. S. Galvanin Francieli D. Zavislak Jair Romano Júnior Jaqueline A. Pizzato Michelle Vecchi
• 来源期刊: 美国植物学期刊(英文)
• 学科: 医学
• 关键词: Ramularia AREOLA Spatial Dependence ISOTROPIC Exponential SEMIVARIOGRAM Kriging
• 年，卷（期）: 2014,（15）
• 页码范围: 2472-2479
• 页数: 8页
• 分类号: R73

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.