The real-time prediction in biorefinery industries has become essential. Models using partial least square regression (PLS) were developed to predict moisture, ash, volatile matter, fixed carbon and organic matter of coconut and coffee residues. On this study, 49 samples were collected and near infrared spectroscopy were applied to predict moisture, ash, volatile matter, fixed carbon and organic matter. For external validation 25% of the set samples were used. Moisture and volatile matter were predicted with coefficients of determination (R 2 cal) above 0.90, and standard errors (RSD) of the estimate of 14.4% and 2.26%, respectively. Models of ash and organic matter show R 2 cal > 0.77 and RSD values < 20.4%. For the external validation, the low deviations show the approximation between reference and predicted values and good prediction with R 2 pred > 0.70. All calibration models were acceptable for sample screening. This study demonstrates that PLS can be used to predict biomass composition of different species, with very low costs and time.

Cocos nucifera L. is a palm tree of paramount importance in the food and chemistry industries, although over 50% of its biomass is discarded as waste. The aim of the study is to investigate different pretreatments in to coconut husks (CH), based on acid, alkaline, ionic liquid (IL), and peroxidative, in order to produce fermentable sugars. Severity factors were calculated for pretreatments; values ranged from 0.3 to 1.7 for peroxide, from 0.01 to 1.4 for alkaline, from 1.4 to 2.8 for acid and from 2.0 to 3.0 for ionic liquid. Pretreatments were optimized (time and temperature) to maximize the sugar yield and to remove the total lignin after acid hydrolysis. Reducing sugar yield (70%) was higher when CH waste was alkaline-pretreated for 2 h at 76.21 °C. The highest lignin removal rate was recorded when alkaline (21.4%) and peroxide solutions (27.2%) were used. The IL did not increase sugar yield and was not effective in lignin removal. These outcomes were confirmed through infrared spectroscopy, whereas scanning electron microscopy showed increased biomass porosity during alkaline, acid and peroxide pretreatments. The IL showed little and non-significant changes. The crystallinity index notably increased after each pretreatment; besides, it was directly associated with sugar content.

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O baru (Dipteryx alata Vog.) possui grande potencial energético para a produção de bioprodutos, a partir do pericarpo e mesocarpo. O objetivo do trabalho foi caracterizar a biomassa residual (endocarpo e mesocarpo) de baru para a obtenção de bioprodutos em processos de biorrefinarias. Cada amostra foi analisada em duplicata e o espectro médio foi utilizado. Foram realizadas análises aproximadas de umidade, cinzas, VMC, FC e matéria orgânica. As biomassas foram pré-tratadas com peroxidativos e solução alcalina submetidos à hidrólise ácida para produção de açúcares. As caracterizações físico-químicas mostraram que, em geral, as biomassas do endocarpo e mesocarpo de baru podem fornecer uma gama de produtos de valor agregado, pois seus parâmetros se encaixam nas exigências da biorrefinaria, tais como: alto teor de carboidratos, baixo teor de umidade, extrativos e cinzas. Maiores teores de lignina contribuem para a obtenção de insumos aromáticos e carvão, do qual foram obtidos para o epicarpo bruto.

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