Coffee Science
URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3355
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Resultados da Pesquisa
Item Precision coffee growing: a review(Universidade Federal de Lavras, 2022-06-09) Santana, Lucas Santos; Ferraz, Gabriel Araújo e Silva; Santos, Sthéfany Airane dos; Dias, Jessica Ellen LimaPrecision Agriculture (PA) technologies introduction in coffee-growing is becoming essential to advances in sustainable cultivation and increase in output. Applications that involve PA techniques in coffee production are defined now as Precision Coffee growing (PC). Systematically explored, studies on the subject contribute to improvements in the area, relating soil variability to its impacts on plants. The PC’s scientific approach offers new forms of manage-ment and more security in coffee production. Aimed at reducing pesticides application and nutrients to the soil, contributing to sustainable development in coffee production. Initially, the research on coffee production had dealt with soil spatial variability, highlighting the geostatistical methods and specific ways to sample the soil. With technological advances in agriculture, new ways of monitoring spatial variability are available. In this context, studies are arising on spatial variability related to the plant, applying terrestrial, aerial and orbital sensors, possibly creating perspectives for monitoring and mapping coffee production. Artificial intelligence, Remotely Piloted Aircraft (ARP) products, harvesting yield sensors, automatic grain classifiers, and remote sensing stand out as new technologies under development in coffee production. These applications in PC involving multidisciplinary research demonstrate new relevant ways of improving crop managing and sustainability guaranteeing.Item Development of a methodology to determine the best grid sampling in precision coffee growing(Editora UFLA, 2018-07) Figueiredo, Vanessa Castro; Silva, Fabio Moreira da; Ferraz, Gabriel Araújo e Silva; Oliveira, Marcelo Silva de; Santos, Sthéfany Airane dosPrecision agriculture is based on a set of techniques that explore the spatial variability of properties related to a determined area. The aim of this study was to develop and test a methodology to evaluate the quality of grid sampling. The experiment was performed in three areas of 112, 50 and 26 ha, in coffee plantations (Coffea arabica ) with cultivar Catuai 144, in the Três Pontas Farm, located in Presidente Olegário, MG, Brazil, in 2014 and 2015. A total of 224, 100, and 52 georeferenced points (2.0 points/ha) were plotted in the areas regarding the soil chemical properties, respectively: phosphorus, potassium, calcium and magnesium. For the application methodology the standardized accuracy index (SAI), the standardized precision index (SPI) and the standardized optimal grid indicator (SOGI) were developed and tested. From grid 1 (2 points/ha), another three sampling grids (1.0, 0.7 and 0.5 point/ha) were adopted. The indexes were important to analyze the grid quality, whereas the SOGI allowed selecting the grid that best represented the properties.Item Plant sampling grid determination in precision agriculture in coffee field(Editora UFLA, 2018-01) Ferraz, Gabriel Araújo e Silva; Oliveira, Marcelo Silva de; Silva, Fábio Moreira da; Sales, Ronan Souza; Carvalho, Luis Carlos CiriloThe aim of the present study was to evaluate different grid samples applied to plant properties of a coffee plantation by using precision coffee growing and geostatistical techniques. The study was performed at the Brejão Farm in the municipality of Três Pontas, MG, Brazil, using productivity, the maturation index and the detachment force difference, sampled at georeferenced points. With the intention of choosing an optimum grid, 20 grid samples were tested through semivariogram fitting and validation tests seeking to combine the accuracy and precision that the grid sample can present through an optimal grid indicator, allowing choosing a more suitable grid. It was possible to characterize the magnitude of the spatial variability of plant properties under study in all the proposed grids. The grid that best represented the three variables under study was the grid with 64 sample points in squared grid and nine zoom grid points. The proposed methodology for the present study allowed observing the difference among different grid samples and among the variables of plant productivity, maturity index and detachment force.Item Agricultura de precisão no estudo de atributos químicos do solo e da produtividade de lavoura cafeeira(Editora UFLA, 2012-01) Ferraz, Gabriel Araújo e Silva; Silva, Fábio Moreira da; Costa, Pedro Augusto Negrini da; Silva, Antonio Carlos; Carvalho, Francisval de MeloA agricultura de precisão surge como uma importante ferramenta para melhorar o gerenciamento de fazendas cafeeiras. O conhecimento de determinadas características relacionadas à fertilidade do solo, associada à resposta de produção do cafeeiro, podem facilitar a aplicação localizada e racional dos insumos, com resultados ambientais e econômicos positivos. Objetivou-se, com esse trabalho, utilizar ferramentas de agricultura de precisão e de geoestatística para avaliar a disponibilidade de fósforo, potássio e a produtividade do cafeeiro por meio de análises dos semivariogramas e de mapas de isolinhas, obtidos por krigagem, com o intuito de demonstrar que essas ferramentas são de grande valia para o manejo da fertilidade do solo na cultura do café. Este trabalho foi conduzido na fazenda Brejão, no município de Três Pontas, Minas Gerais, utilizando-se os atributos químicos do solo-fósforo e potássio amostrados com o auxílio de um quadriciclo equipado com calador e dados de produtividade obtidos por meio de colheita manual, ambos em pontos georreferenciados. A análise desses dados por meio das técnicas estatísticas e geoestatísticas possibilitaram caracterizar a variabilidade espacial do fósforo, potássio e da produtividade de uma lavoura cafeeira, permitindo-se a análise da relação entre essas variáveis. Foi possível observar que houve dependência espacial o que permitiu a confecção de mapas de distribuição espacial das variáveis.