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	Provedor de dados Ciencia e Investigación Agraria (1) AgEcon (1) Autor Debaene,Guillaume (1) Escribano Sanchez, Miguel (1) Gaspar, P. (1) Mesias, F.J. (1) Niedźwiecki,Jacek (1) Pikuła,Dorota (1) Pulido, F. (1) Mais... Palavra-chave Partial least square regression (2) Crop Production/Industries (1) Dehesa (1) Gross output (1) Livestock Production/Industries (1) Livestock farming systems (1) Manure (1) Near-infrared spectroscopy (1) Nitrogen fertilizer (1) Research Methods/ Statistical Methods (1) Soil organic carbon (1) Support Vector Machine (1) Mais... Tipo do documento Conference Paper or Presentation (1) Journal article (1) Ano 2014 (1) 2008 (1) País Chile (1) United States (1) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Use of VIS-NIRS for land management classification with a support vector machine and prediction of soil organic carbon and other soil properties Ciencia e Investigación Agraria Debaene,Guillaume; Pikuła,Dorota; Niedźwiecki,Jacek. The objective of this research was to investigate the effects of a long-term experiment on soil spectral properties and to develop prediction models of these properties (soil organic carbon (SOC), N, pH, Hh, P2O5, K2O, Ca, Mg, K, and Na content) from texturally homogeneous samples (loamy sand). To this aim, chemometric techniques, such as partial least square (PLS) regression and support vector machine (SVM) classification, were used. Our results show that visible and near infrared spectroscopy (VIS-NIRS) is suitable for the prediction of properties of texturally homogeneous samples. The effects of fertilizer applications were sufficient to modify the soil chemical composition to a range suitable for using VIS-NIRS for calibration and modeling purposes.... Tipo: Journal article Palavras-chave: Manure; Near-infrared spectroscopy; Nitrogen fertilizer; Partial least square regression; Soil organic carbon; Support Vector Machine. Ano: 2014 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202014000100003 Gross output and livestock sales modelling in Spanish extensive farms using PLSR AgEcon Gaspar, P.; Mesias, F.J.; Escribano Sanchez, Miguel; Pulido, F.. The aim of this paper is to model some production variables in extensive livestock farms located in the dehesa ecosystem. We intend to use not only purely economic variables in the construction of the model, but also structural variables in order to identify the characteristics of the farms that have the higher influence. Another objective is to be able to predict these variables at the farm level, using structural variables that are easy to measure. The data used in this work were obtained from a questionnaire survey to the holders/managers of a sample of 69 dehesa farms in Extremadura (SW Spain). The statistical methodology used for the construction of the model was Partial Least Square Regression (PLSR). It can be concluded that the variables relative... Tipo: Conference Paper or Presentation Palavras-chave: Dehesa; Livestock farming systems; Partial least square regression; Gross output; Crop Production/Industries; Livestock Production/Industries; Research Methods/ Statistical Methods. Ano: 2008 URL: http://purl.umn.edu/6463 Registros recuperados: 2 Primeira ... 1 ... Última

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