Navegando por Autor "Freitas, Aurivan Soares de"

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Development of warning systems for Phoma leaf spot in coffee
(Editora da Universidade Estadual de Maringá - EDUEM, 2025-08-04) Silva, Humberson Rocha; Pozza, Edson Ampélio; Freitas, Aurivan Soares de; Freitas, Marcelo Loran de Oliveira; Belan, Leônidas Leoni; Barbosa Junior, Mauro Peraro; Vivanco, Mário Javier Ferrua; Santos Neto, Helon
Statistical models can help in decision-making for the control of plant diseases, leading to less use of inputs, greater economy, and less negative environmental impact. Thus, this study aimed to use environmental variables to fit multiple linear regression (MLR) models for estimating the Phoma leaf spot incidence in coffee to develop a warning system. The experiment was conducted over two years (September 2013 to August 2015) with monthly disease assessments in the Coffea arabica L. cultivar “Catucaí amarelo 2SL”. A regular grid of 7.65 ha with 85 points delimited the area, with the points spaced 30 x 30 m. The incidence progress curve was constructed by considering the overall mean of the 85 points in each month. Fifty-two environmental variables were generated using an automatic station installed in the crop, and these variables were used in the development of the MLR models. A total of 126 models were fit, of which four were more successful in estimating disease dynamics over time. Two of these models allowed the acquisition of estimated values for disease incidence two weeks prior to the disease assessments, with high precision and accuracy. Nowadays the disease management has been performed exclusively with the use of fixed spraying schedules of fungicides. The models obtained in our research can contribute to sustainability of coffee production, to avoid unnecessary use of fungicides and become coffee cultivation more profitable.
Temporal analysis of Phoma leaf spot of coffee plants at different altitudes
(Universidade Federal de Viçosa, 2025-04-25) Silva, Humberson Rocha; Pozza, Edson Ampélio; Freitas, Aurivan Soares de; Freitas, Marcelo Loran de Oliveira; Barbosa Junior, Mauro Peraro; Cirillo, Marcelo Angelo
Phoma leaf spot (Phoma spp.) of coffee causes losses of between 15 and 43%, and presents significant variability over time and space, especially in mountain coffee production. Thus, the objective of this study was to evaluate the behavior of this disease at different altitudes and to use time series techniques and regression models to explain disease behavior. The experiment was conducted over two years (from September 2013 to August 2015) with monthly evaluations in a Coffea arabica L. plantation. The incidence and severity progress curves showed irregular behavior most of the time, typical of the disease. Higher altitudes provided higher disease incidence and severity values. Only the incidence and severity progress curves at the altitude of 1143.2 m showed significant autocorrelation over time. Thus, the first-order autocorrelation structure, AR(1), was incorporated in the estimates of the parameters of the linear and nonlinear models. Only the months from February to June/July 2014 were considered, when the disease progressed regularly. The rates obtained for the incidence, overall mean of the 85 points and mean altitude of 1143.2 m, were 5.2 and 4.6%, respectively, while the estimated rates for the severity data under the same conditions were 0.3 and 0.1%, respectively. These values represent the expected increase in incidence and severity each month. The Phoma leaf spot presents complex temporal dynamics, influenced by microclimatic variables associated with altitude.