Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/28812
metadata.artigo.dc.title: Geostatistical analysis of fruit yield and detachment force in coffee
metadata.artigo.dc.creator: Ferraz, Gabriel Araújo e Silva
Silva, Fábio Moreira da
Alves, Marcelo de Carvalho
Bueno, Rafael de Lima
Costa, Pedro Augusto Negrini da
metadata.artigo.dc.subject: Coffee – Productivity – Spatial distribution
Coffee – Maturation
Precision farming – Statistical methods
Geology – Statistical methods
Café – Produtividade – Distribuição espacial
Café – Maturação
Agricultura de precisão – Métodos estatísticos
Geologia – Métodos estatísticos
Coffea arabica
metadata.artigo.dc.publisher: Springer
metadata.artigo.dc.date.issued: Feb-2012
metadata.artigo.dc.identifier.citation: FERRAZ, G. A. e S. et al. Geostatistical analysis of fruit yield and detachment force in coffee. Precision Agriculture, [Dordrecht], v. 13, n. 1, p. 76-89, Feb. 2012.
metadata.artigo.dc.description.abstract: The aim of this study was to use geostatistical analysis to evaluate the spatial variation in the detachment force of coffee fruit and coffee yield by variograms and kriging for precision agriculture. This study was conducted at Brejão farm, Três Pontas, Minas Gerais, Brazil. The detachment force of green and mature coffee fruit was measured with a prototype dynamometer and georeferenced. The yield data were obtained from manual harvesting and were georeferenced. The data were evaluated by variograms estimated by residual maximum likelihood (REML), which provided a satisfactory approach for modeling all the variables with a small sample size. Spherical and exponential models were fitted, the first provided the better fit to mature fruit detachment force and the latter provided the better fit to coffee yield and green fruit detachment force. They were used to describe the structure and magnitude of spatial variation in the variables studied. Kriged estimates were obtained with the best fitting variogram models and mapped. The statistical and geostatistical analyses enabled us to characterize the spatial variation of the detachment force of green and mature coffee fruit and coffee yield and to visualize the spatial relations among these variables. The precision agriculture techniques used in this paper to collect, map and analyze the variables studied will help coffee farmers to manage their fields. Maps of coffee yield will enable farmers to apply nutrients site-specifically and manage harvesting either manually or mechanically. In addition, maps of detachment force of coffee fruit can enable farmers to harvest coffee selectively by choosing the appropriate places and the right time to start. This will improve the quality of the final product and also increase profits.
metadata.artigo.dc.identifier.uri: https://link.springer.com/article/10.1007/s11119-011-9223-8
http://repositorio.ufla.br/jspui/handle/1/28812
metadata.artigo.dc.language: en_US
Appears in Collections:DEG - Artigos publicados em periódicos

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