Please use this identifier to cite or link to this item:
Title: Geostatistical stationary space-time covariance functions modeling of Yellow Sigatoka progress in banana crop
Keywords: Musa spp.
Pseudocercospora musae
Spatio-temporal pattern
Covariance models
Banana - Doenças e pragas
Padrão espaço-temporal
Modelos de covariância
Issue Date: May-2019
Publisher: Springer Nature
Citation: RODRIGUES, J. D. P. et al. Geostatistical stationary space-time covariance functions modeling of Yellow Sigatoka progress in banana crop. Australasian Plant Pathology, [S. I.], v. 48, n. 3, p. 233-244, May 2019.
Abstract: Banana production is affected by Yellow Sigatoka, one of the causes of leaf lesions, which causes the reduction of the photosynthetic area of the plant and, consequently, the quality of the fruit and the production. The objective of this study was to analyze using geostatistics and comparing separable and non-separable spatio-temporal covariance models with different adjustment methods. The experiment was carried out in a banana plantation of the Prata-Anã variety, which presented high severity of the disease, without any control measures, which allowed the study of behavior under natural conditions. The Separable Doubly Exponential and the non-separable model of Gneiting were tested with the Weight Least Squares (WLS), Restricted Maximum Likelihood (REML) and Likelihood Pairwise estimation methods. The Gneiting model, WLS curve-fitting methods for estimatives space-time covariance structure, allowed to reduce the uncertainties of the spatial and temporal prediction of the disease, as well as to characterize the spatio-temporal pattern of the disease.
Appears in Collections:DEG - Artigos publicados em periódicos
DES - Artigos publicados em periódicos
DFP - Artigos publicados em periódicos

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.