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	Provedor de dados 63 (2) 124 (1) 64 (1) Autor Campos,Katia Alves (1) Carvalho,João Luís Nunes (1) Dias,Carlos Tadeu dos Santos (1) Farhate,Camila Viana Vieira (1) Freitas,Marcella Nunes de (1) Malta,Marcelo Ribeiro (1) Morais,Augusto Ramalho de (1) Oliveira,Luiz Felipe Ramalho de (1) Oliveira,Stanley Robson de Medeiros (1) Paixão,Crysttian Arantes (1) Pereira,Cristiane Carvalho (1) Rosa,Sttela Dellyzete Veiga Franco da (1) Santana,Reynaldo Campos (1) Santos,Ana Paula Guimarães (1) Scala Júnior,Newton La (1) Souza,Zigomar Menezes de (1) Mais... Palavra-chave Variable selection (4) Analysis of variance (1) Canonical correlation (1) Coffea arabica (1) Coffea arabica L. (1) Data mining (1) Data transformation (1) Modelling (1) Multivariate analysis (1) Physiological tests (1) Remote sensing (1) Sensory analysis (1) Soil CO2 emission (1) Soil organic matter (1) Soil temperature (1) Tree monitoring (1) Mais... Tipo do documento Info:eu-repo/semantics/article (4) Ano 2020 (2) 2018 (1) 2016 (1) País Brazil (4) Idioma Inglês (4)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 4 Primeira ... 1 ... Última Identification of physiological analysis parameters associated with coffee beverage quality 64 Freitas,Marcella Nunes de; Rosa,Sttela Dellyzete Veiga Franco da; Pereira,Cristiane Carvalho; Malta,Marcelo Ribeiro; Dias,Carlos Tadeu dos Santos. ABSTRACT The demand for high-quality coffee among consumers has generated a great deal of interest among producers in serving this market. Parameters for physiological analyses that can be associated with aspects of sensory analyses of coffee can ensure more reliable results for coffee quality assessments. The aim of this study was to investigate the potential of physiological analyses in determining coffee quality through multivariate analysis. Several samples from coffee bean/seed lots were placed in cold storage at 10 °C, after which the sensory quality, physiological quality, and chemical characteristics of the beans were evaluated before storage and after three and six months of storage. The variables of physiological quality in the coffee beans were... Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica L.; Sensory analysis; Physiological tests; Variable selection; Canonical correlation. Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542020000100213 Alternative for the evaluation of coffee seedlings using Fisher's discriminant analysis 124 Campos,Katia Alves; Morais,Augusto Ramalho de; Paixão,Crysttian Arantes. ABSTRACT One of the applications of Fisher's linear discriminant function (FDF) is its use in transforming multivariate data into a new univariate variable. This then makes possible a new option for the variance analysis of multivariate data, in addition to the multivariate analysis of variance (MANOVA). The aim of this work was to select groups of seven characteristics of quality in coffee seedlings using six criteria for selection, to use the FDF to transform such groupings of characteristics into a new variable, and then to compare interpretation of the results obtained from the univariate and multivariate analyses of variance of the characteristics and this new variable, with a view to its use in evaluating coffee seedlings. A randomised block design... Tipo: Info:eu-repo/semantics/article Palavras-chave: Variable selection; Multivariate analysis; Data transformation; Analysis of variance; Coffea arabica. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902016000200299 Classification of soil respiration in areas of sugarcane renewal using decision tree 63 Farhate,Camila Viana Vieira; Souza,Zigomar Menezes de; Oliveira,Stanley Robson de Medeiros; Carvalho,João Luís Nunes; Scala Júnior,Newton La; Santos,Ana Paula Guimarães. ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of... Tipo: Info:eu-repo/semantics/article Palavras-chave: Soil CO2 emission; Data mining; Variable selection; Soil temperature; Soil organic matter. Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300216 Estimation of leaf nutrient concentration from hyperspectral reflectance in Eucalyptus using partial least squares regression 63 Oliveira,Luiz Felipe Ramalho de; Santana,Reynaldo Campos. ABSTRACT: Leaf hyperspectral reflectance has been used to estimate nutrient concentrations in plants in narrow bands of the electromagnetic spectrum. The aim of this study was to estimate leaf nutrient concentrations using leaf hyperspectral reflectance and verify the variable selection methods using the partial least squares regression (PLSR). Two studies were carried out using stands with Eucalyptus clones. Study I was established in Eucalyptus stands with three clones, classifying leaves into five colour patterns using the Munsell chart for plant tissues. Immediately after leaf collection, leaf reflectance was read and the chemical analysis was performed. Study II was carried out in commercial clonal stands of Eucalyptus performing the same leaf... Tipo: Info:eu-repo/semantics/article Palavras-chave: Remote sensing; Tree monitoring; Modelling; Variable selection. Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000601402 Registros recuperados: 4 Primeira ... 1 ... Última

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