Development of warning systems for Phoma leaf spot in coffee
Abstract
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.
Downloads
References
Campbell, C. L., & Madden, L. V. (1990). Introduction to Plant Disease Epidemiology. John Wiley & Sons.
Companhia Nacional de Abastecimento [CONAB]. (2024). Boletim café janeiro 2024. https://www.conab.gov.br/info-agro/safras/cafe/boletim-da-safra-de-cafe
Huber, L., & Gillespie, T. J. (1992). Modeling leaf wetness in relation to plant disease epidemiology. Annual Review of Phytopathology, 30(1), 553-577. https://doi.org/10.1146/annurev.py.30.090192.003005
Lorenzetti, E. R., Pozza, E. A., Souza, P. E., Santos, L. A., Alves, E., Silva, A. C., Maia, F. G. M., & Carvalho, R. R. C. (2015). Effect of temperature and leaf wetness on Phoma tarda and Phoma leaf spot in coffee seedlings. Coffee Science, 10(1), 1-9. https://doi.org/10.25186/cs.v10i1.688
Matiello, J. B., Santinato, R., Almeida, S. R., & Garcia, A. W. R. (2015). Cultura de Café no Brasil – Manual de Recomendações. Fundação Procafé.
Pozza, E. A., & Alves, M. C. (2008). Impacto potencial de mudanças climáticas sobre as doenças fúngicas do cafeeiro no Brasil. In R. Ghini, & E. Ramada (Eds.), Mudanças climáticas: impactos sobre doenças de plantas no Brasil (pp. 220-238). Embrapa.
Pozza, E. A., Carvalho, V. L., & Chalfoun, S. M., (2010). Sintomas de injúrias causadas por doenças em cafeeiro. In Semiologia do cafeeiro: sintomas de desordens nutricionais, fitossanitárias e fisiológicas. UFLA.
Pozza, E. A. (2021). Diagnose e controle de doenças. In G. R. Carvalho, A. D. Ferreira, V. T. Andrade, C. E. Botelho, & J. P. F. Carvalho (Eds.), Cafeicultura do Cerrado. Epamig.
Pozza, E. A., Santos, É. R. D., Gaspar, N. A., Vilela, X. M. D. S., Alves, M. D. C., & Colares, M. R. N. (2021). Coffee rust forecast systems: Development of a warning platform in a Minas Gerais State, Brazil. Agronomy, 11(11), 1-22. https://doi.org/10.3390/agronomy11112284
R Development Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing.
Rossi, V., Giosuè, S., & Caffi, T. (2010). Modelling plant diseases for decision making in crop protection. In E. C. Oerke, R. Gerhards, G. Menz, & R. A. Sikora (Eds.), Precision crop protection: The challenge and use of heterogeneity (pp. 241-256). Springer. https://doi.org/10.1007/978-90-481-9277-9
Salgado, M., & Pfenning, L. H. (2000). Identificação e caracterização morfológica de espécies de Phoma do cafeeiro no Brasil, In Anais do I Simpósio de Pesquisa dos cafés do Brasil (pp. 183-186). Emprapa.
Santos, L. S. D., Pozza, E. A., Faria, M. A., Silva, M. L. O., Custódio, A. A. P., & Vasco, G. B. (2014). Incidência da Mancha de Phoma em cafeeiro irrigado por gotejamento, sob diferentes manejos de irrigação. Coffee Science, 9(1), 77-89.
Sera, G. H., Carvalho, C. H. S., Abrahão, J. C. R., Pozza, E. A., Matiello, J. B., Almeida, S. R., Bartelega, L., & Botelho, D. M. S. (2022). Coffee leaf rust in Brazil: historical events, current situation, and control measures. Agronomy, 12(2), 1-19. https://doi.org/10.3390/agronomy12020496
StatSoft Inc. (2004). Statistica (data analysis software system - version 7).
United States Department of Agriculture [USDA]. (2023). Coffee: World Markets and Trade. Foreign Agricultural Service/USDA 2023. https://www.fas.usda.gov/data/coffee-world-markets-and-trade
Copyright (c) 2025 Humberson Rocha Silva, Edson Ampélio Pozza, Aurivan Soares de Freitas, Marcelo Loran de Oliveira Freitas, Leônidas Leoni Belan, Mauro Peraro Barbosa Junior, Mário Javier Ferrua Vivanco, Helon Santos Neto (Autor)
This work is licensed under a Creative Commons Attribution 4.0 International License.
DECLARATION OF ORIGINALITY AND COPYRIGHTS
I Declare that current article is original and has not been submitted for publication, in part or in whole, to any other national or international journal.
The copyrights belong exclusively to the authors. Published content is licensed under Creative Commons Attribution 4.0 (CC BY 4.0) guidelines, which allows sharing (copy and distribution of the material in any medium or format) and adaptation (remix, transform, and build upon the material) for any purpose, even commercially, under the terms of attribution.
