Espectroscopia no infravermelho próximo na avaliação da qualidade de cavacos destinados à produção de energia

Abstract

So that companies producing forest biomass to deliver products that meet market demands, it is necessary that they carry out accurate assessments of their materials. Near infrared spectroscopy (NIR) is a technique that presents itself with potential feasibility for application in the characterization of lignocellulosic materials, as it delivers fast and accurate results. Faced with this, the objective of this work was to apply near infrared spectroscopy to evaluate the quality of chips used for energy generation using the NIR technique. They were evaluated the characteristics of basic density, moisture and higher calorific value of the chips. For this, two batches with 100 chip samples were collected, on different days, in the supplier company's yard, which were used in routine laboratory analyzes and in obtaining the spectra in the NIR. Thus, the spectral data were correlated with the values obtained through conventional analyzes to generate predictive models. After creating the models, they were applied to predict the characteristics of new batches of chips. The models were evaluated through Coefficient of determination (R²), Root square of the mean cross-validation error and Square root of the mean calibration error, Number of latent variables (Rank) and Bias of validation. The validation of the models presented satisfactory statistics for the basic density (R²=0.83), moisture (R2=0.90) and superior calorific value (R2=0.74), having potential for application in wood evaluation in the energy industry. The statistical results of the mathematical models were satisfactory for the purposes of the work and can be used for chip analysis from new batches.