2 resultados para predição

em Repositorio Institucional da UFLA (RIUFLA)


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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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The aim of the study was to develop a system of growth and yield models for thinned stands of Eucalyptus spp.; and to assess the behavior of the growth in scenarios with 10% decrease or increase in rainfall. The probability distribution functions Weibull 2 and 3 parameters and Johnson SB for different methods were fitted. Correlation between the fitted parameters with age was evaluated. Dominant height growth behavior was evaluated to check if thinned stand changes its growth when compared to a non-thinned stands. The stand variables dominant height and basal area were projected and simultaneously predicted and projected, respectively. Individual tree equations were fitted, which were fitted as functions of stand level variables in order to decrease the error propagation. R software was used to fit all the proposed models and consequently all the fitted models were evaluated by their parameters significance (F-test) and graphs of predicted values in relation to the observed values around the 1:1 line. Thus, the prognosis system was made by two ways, first one using the full data set, and for the second one the dataset was restricted at age 7.5. Increase and decrease in 20% of rainfall were assessed by updating the site index function. Method of moments was the most precise to describe the diameter distribution for every age in eucalyptus stands for Johnson SB and Weibull 2 parameters pdfs. When observed for each pdf the correlation for their fitted parameters with age, we noticed that shape parameters for a thinned stand were no longer correlated with age, differently of non-thinned stands. Thus, thinning effect was accounted in the basal area prediction and projection modeling. This result emphasized the necessity of applying the Parameter Recovery method in order to assess differences and capture the right pattern for thinned and non-thinned stands in the future. Dominant height was not influenced by thinning intensity. Therefore the fitted Chapman-Richards model did not account for a stand being thinned or not. All the fitted equations behaved with good precision, no matter using full or precocious dataset. The prognosis system using full and/or precocious date set was evaluated for when using Parameter Recovery method for Sb and Weibull pdfs, and by then, graphical analysis and precision statistics showed appropriated results. Finally, the increase or decrease in rainfall regime were observed for eucalyptus stand yields and we may notice how important is to observe this effect, since the growth pattern is strictly affected by water.