RESUMEN
ABSTRACT: The harvesting process is a current challenge for the commercial production of microalgae because the biomass is diluted in the culture medium. Several methods have been proposed to harvest microalgae cells, but there is not a consensus about the optimum method for such application. Herein, the methods based on sedimentation, flocculation, and centrifugation were evaluated on the recovery of Chlorella sorokiniana BR001 cultivated in a low-nitrogen medium. C. sorokiniana BR001 was cultivated using a low-nitrogen medium to trigger the accumulation of neutral lipids and neutral carbohydrates. The biomass of C. sorokiniana BR001 cultivated in a low-nitrogen medium showed a total lipid content of 1.9 times higher (23.8 ± 4.5%) when compared to the biomass produced in a high-nitrogen medium (12.3 ± 1.2%). In addition, the biomass of the BR001 strain cultivated in a low-nitrogen medium showed a high content of neutral carbohydrates (52.1 ± 1.5%). The natural sedimentation-based process was evaluated using a sedimentation column, and it was concluded that C. sorokiniana BR001 is a non-flocculent strain. Therefore, it was evaluated the effect of different concentrations of ferric sulfate (0.005 to 1 g L-1) or aluminum sulfate (0.025 to 0.83 g L-1) on the flocculation process of C. sorokiniana BR001, but high doses of flocculant agents were required for an efficient harvest of biomass. It was evaluated the centrifugation at low speed (300 to 3,000 g) as well, and it was possible to conclude that this process was the most adequate to harvest the non-flocculent strain C. sorokiniana BR001.
RESUMO: O processo de colheita é um desafio atual para a produção comercial de microalgas porque a biomassa é diluída no meio de cultivo. Diversos métodos têm sido propostos para coletar células de microalgas, porém não existe um consenso sobre um método ótimo para tal aplicação. Neste estudo, métodos baseados em sedimentação, floculação e centrifugação foram avaliados na recuperação de Chlorella sorokiniana BR001 cultivada em um meio com baixo teor de nitrogênio. C. sorokiniana BR001 foi cultivada em um meio com baixo teor de nitrogênio para induzir ao acúmulo de lipídeos e carboidratos neutros. A biomassa de C. sorokiniana BR001 cultivada em um meio com baixo teor de nitrogênio apresentou um teor de lipídeos 1,9 vezes superior (23,8 ± 4,5%), quando comparada à biomassa produzida em um meio com alto teor de nitrogênio (12,3 ± 1,2%). Adicionalmente, a biomassa da linhagem BR001 cultivada em um meio com baixo teor de nitrogênio apresentou alto teor de carboidratos neutros (52,1 ± 1,5%). O processo baseado em sedimentação natural foi avaliado utilizando uma coluna de sedimentação e concluiu-se que C. sorokiniana BR001 é uma linhagem não floculante. Portanto, o efeito de diferentes concentrações de sulfato férrico (0,005 a 1 g L-1) ou sulfato de alumínio (0,025 a 0,83 g L-1) foram avaliados no processo de floculação de C. sorokiniana BR001, mas altas doses de floculantes foram necessárias para uma colheita de biomassa eficiente. Também foi avaliada a centrifugação em baixa velocidade (300 a 3.000 g), e foi possível concluir que este processo constituiu o mais adequado para a colheita da linhagem não floculante C. sorokiniana BR001.
RESUMEN
Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface ('skin') (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.
