971 resultados para Frutífera nativa


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Estudos Linguísticos - IBILCE

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The objective of this study was to evaluate the potential of near infrared spectroscopy (NIRS) associated with multivariate statistics to distinguish coal produced from wood of planted and native forests. Timber forest species from the C errado (Cedrela sp., Aspidosperma sp., Jacaranda sp. and unknown species) and Eucalyptus clones from forestry companies (Vallourec and Cenibra) were carbonized in the final temperatures of 300, 500 and 700°C. In each heat treatment were carbonized 15 specimens of each vegetal material totaling 270 samples (3 treatments x 15 reps x 6 materials) produced in 18 carbonization (3 treatments x 6 materials). The acquisition of the spectra of coals in the near infrared using a spectrometer was performed. Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS-R) were carried out in the spectra. NIR Spectroscopy associated with PCA was not able to differentiate charcoals produced from native and planted woods when utilizing all carbonized samples at different temperatures in the same analysis; The PCA of all charcoals was able to distinguish the samples depending on temperature in which they were carbonized. However, the separation of native and planted charcoal was possible when the samples were analyzed separately by final temperature. The prediction of native or planted classes by PLS-R presented better performance for samples carbonized at 300°C followed by those at 500°C, 700°C and for all together.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Agronomia - FEIS

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The use of geostatistical techniques allows detection of the existence of dependence and the spatial distribution of soil properties, thus constituting an important tool in the analysis and detailed description of the behavior of soil physical properties. The aim of the present study was to use geostatistics in assessment of physical properties in a Latossolo (Oxisol) dystrophic under native forest and pasture in the Amazon region of Manicore. Grids with of 70 x 70 m were established in native forest and pasture, and points were marked in these grids spaced at every 10 m, for a total of 64 points. These points were then georeferenced and in each one, soil samples (128) were collected at the depths of 0.00-0.20 and 0.40-0.60 m for a survey of their physical properties. These grids are parallel at a distance of 100 m from one another. The following determinations were made: texture, bulk density and particle density, macroporosity, microporosity, total porosity and aggregate stability in water. After tabulating the data, descriptive statistical analysis and geostatistical analysis were performed. The pasture had a slight variation in its physical properties in relation to native forest, with a high coefficient of variation and weak spatial dependence. The scaled semivariograms were able to satisfactorily reproduce the spatial behavior of the properties in the same pattern as the individual semivariograms, and the use of the parameter range of the semivariogram was efficient for determining the optimal sampling density for the environments under study. The geostatistical results indicate that the removal of native forest for establishing pasture altered the natural variability of the physical properties.