Coffee Science_v.15, 2020

URI permanente para esta coleçãohttps://thoth.dti.ufv.br/handle/123456789/12726

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    Spatial correlation between the chlorophyll index and foliar npk levels in coffee crop
    (Editora UFLA, 2020) Zanella, Marco Antonio; Rodrigues Junior, Francelino Augusto; Sousa, Emanoel Di Tarso dos Santos; Martins, Rodrigo Nogueira; Calijuri, Maria Lúcia
    Detection of spatial variability of data that can improve crop management is a key factor for precision agriculture. In agriculture, there is a need for tools to assist farmers in decision-making about proper nutrient management, aiming to achieve their full productive potential. Based on that, this study aimed to (1) determine the spatial correlations between the chlorophyll index (CI) and the foliar levels of nitrogen, phosphorus and potassium (NPK) in the coffee crop using geostatistical tools; and (2) to evaluate the potential use of this index as a tool for site-specific nutrient management in an irrigated coffee field. For that, a study was carried out in a 2.1 ha area under arabica coffee cultivation in Paula Cândido, Minas Gerais State, Brazil. Samplings of the CI were performed in 1141 plants using a portable chlorophyll meter (SPAD-502). Regarding the NPK analysis, leaf samples from one of each 10 plants used to measure the CI were taken for chemical analysis (114 plants). Then, the data were submitted to descriptive and geostatistical analysis. For the spatial correlation analysis, the Moran Bivariate Global (I) and the Local index (Ixy) were used. The results showed a moderate correlation between the CI and N (0.500), showing the potential of the chlorophyll meter as a tool for site-specific nitrogen management in the coffee crop. Differently, the CI is not recommended for P and K management since they were not well correlated. Lastly, as a tool that performs indirect measurements, the results from the chlorophyll meter should be validated by field measurements to local calibrations.
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    Technical and economic viability of manual harvesting coffee yield maps
    (Editora UFLA, 2020) Faria, Rafael de Oliveira; Silva, Fábio Moreira; Ferraz, Gabriel Araújo e Silva; Herrera, Miguel Angel Diaz; Barbosa, Brenon Diennevan Souza; Alonso, Diego José Carvalho; Soares, Daniel Veiga
    Precision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle.