Abstract
Coffee leaf rust (Hemileia vastatrix) is considered the main disease of conilon coffee (Coffea canephora). Sampling methods aiming at accurate estimation of disease intensity are key for epidemiological studies and management, but there is not one method available for leaf rust of conilon. Thus, the objective with this study was to develop and validate a method to sample leaves to estimate the incidence of rust in conilon coffee plants. Nine within-plant sampling methods for rust incidence (proportion of symptomatic leaves), based on a combination of canopy height of plagiotropic branches, node position and leaf number per branch were established and evaluated during monthly assessment of natural epidemics from October 2011 to April 2013, representing two stages of crop development. The monthly estimated incidence values were compared to the actual rust incidence using linear regression, Lin’s concordance correlation (ρc) and progress curve. The most efficient method was selected based on accuracy and precision. The most accurate and precise sampling method by which to represent the actual incidence was of all the leaves from four plagiotropic branches distributed in the four quadrants in the upper third of the plant. This method was efficient during all crop development stages. Moreover, the estimated incidence progress curve showed the same pattern of temporal distribution as the actual incidence. Thus, a specific method for leaf sampling and estimating the incidence of leaf rust in conilon coffee plants was developed and validated.
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Acknowledgements
This research was supported by the Fundação de Amparo à Pesquisa e Inovação do Espírito Santo (FAPES) [1006/2015] and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [300280/2016-5].
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Belan, L.L., Belan, L.L., Satiro, L.S. et al. A comparison of sampling methods to accurately estimate the incidence of leaf rust on conilon coffee. Australasian Plant Pathol. 50, 729–737 (2021). https://doi.org/10.1007/s13313-021-00823-y
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DOI: https://doi.org/10.1007/s13313-021-00823-y