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URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
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Item Management zones in coffee cultivation(Departamento de Engenharia Agrícola - UFCG, 2017-02) Jacintho, João L.; Ferraz, Gabriel A. e S.; Silva, Fabio M. da; Santos, Sthéfany A.This study aimed to apply precision agriculture techniques in coffee production, using correlation analysis in the definition of management zones. This work was carried out in a 22-ha area of coffee (Coffea arabica L.), cv. ‘Topázio MG 1190’, which was sampled on a regular grid, using a topographic GPS, totaling 64 georeferenced samples (on average, 2.9 points per ha). Descriptive analysis was used in the data, followed by Pearson’s correlation analysis at 0.05 significance between soil chemical attributes, agronomic characteristics of the plants and altitude. It was possible to verify the correlation of soil chemical attributes, agronomic characteristics of the plants and altitude with coffee yield. Altitude was the variable most correlated with coffee yield through correlation analysis. Therefore, it was chosen as the best variable to define management zones and thematic maps capable to support coffee farmers. Three maps were generated to characterize the area in two, three and four management zones. There was a direct influence on mean yield.Item Geostatistical analysis of Arabic coffee yield in two crop seasons(Departamento de Engenharia Agrícola - UFCG, 2017-06) Carvalho, Luis C. C.; Silva, Fabio M. da; Ferraz, Gabriel A. e S.; Stracieri, Juliana; Ferraz, Patrícia F. P.; Ambrosano, LucasTo make the coffee activity competitive, some farmers use precision coffee farming. Thus, it is possible to create thematic maps that guide management practices for regions where there are limitation for the plant development. The objective of this study was to identify the spatial dependence of coffee crop yield, in 2012 and 2013. The experimental area is located in a Haplustox in Três Pontas, Minas Gerais. One hundred sampling points were georeferenced for the collection of yield data through manual harvest. The difference of yield between crop seasons was also evaluated. Data were processed using geostatistical analysis. It was possible to identify and characterize the spatial dependence of all variables, as well as to create contour maps. There were differences between the 2012 and 2013 maps, due to the biennial coffee phenological cycle, which can be confirmed by the map of the difference between the crop seasons. It is recommended a crop management that considers the spatial variability of yield for greater economic return.