TITLE:
Geostatistics as a Methodology for Studying the Spatiotemporal Dynamics of Ramularia areola in Cotton Crops
AUTHORS:
Jaqueline A. Pizzato, Dejânia V. Araújo, Edinéia A. S. Galvanin, Jair Romano Júnior, Ândrea N. A. Matos, Michelle Vecchi, Francieli D. Zavislak
KEYWORDS:
Ramularia areola, Spatial Dependence, Isotropic Exponential Semivariogram, Kriging
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.5 No.15,
July
30,
2014
ABSTRACT:
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.