Purification of phlorotannins from Macrocystis pyrifera using macroporous resins

Phlorotannins are secondary metabolites produced by brown seaweed, which are known for their nutraceutical and pharmacological properties. The aim of this work was to determine the type of macroporous resin and the conditions of operation that improve the purification of phlorotannins extracted from brown seaweed, Macrocystis pyrifera. For the purification of phlorotannins, six resins (HP-20, SP-850, XAD-7, XAD-16N, XAD-4 and XAD-2) were assessed. The kinetic adsorption allowed determination of an average adsorption time for the resins of 9h. The highest level of purification of phlorotannins was obtained with XAD-16N, 42%, with an adsorption capacity of 183±18mgPGE/g resin, and a desorption ratio of 38.2±7.7%. According to the adsorption isotherm the best temperature of operation was 25°C, and the model that best described the adsorption properties was the Freundlich model. The purification of phlorotannins might expand their use as a bioactive substance in the food, nutraceutical and pharmaceutical industries.

Effects of distillation system and yeast strain on the aroma profile of Albariño (Vitis vinifera L.) grape pomace spirits

Orujo is a traditional alcoholic beverage produced in Galicia (northwest Spain) from distillation of grape pomace, a byproduct of the winemaking industry. In this study, the effect of the distillation system (copper charentais alembic versus packed column) and the yeast strain (native yeast L1 versus commercial yeast L2) on the chemical and sensory characteristics of orujo obtained from Albariño (Vitis vinifera L.) grape pomace has been analyzed. Principal component analysis, with two components explaining 74% of the variance, is able to clearly differentiate the distillates according to distillation system and yeast strain. Principal component 1, mainly defined by C6-C12 esters, isoamyl octanoate, and methanol, differentiates L1 from L2 distillates. In turn, principal component 2, mainly defined by linear alcohols, linalool, and 1-hexenol, differentiates alembic from packed column distillates. In addition, an aroma descriptive test reveals that the distillate obtained with a packed column from a pomace fermented with L1 presented the highest positive general impression, which is associated with the highest fruity and smallest solvent aroma scores. Moreover, chemical analysis shows that use of a packed column increases average ethanol recovery by 12%, increases the concentration of C6-C12 esters by 25%, and reduces the concentration of higher alcohols by 21%. In turn, L2 yeast obtained lower scores in the alembic distillates aroma profile. In addition, with L1, 9% higher ethanol yields were achieved, and L2 distillates contained 34%-40% more methanol than L1 distillates.

Predictive controller evaluation including non-stationary high frequency noise and outliers for batch solid substrate fermentation bioreactors

Optimum operation and automatic control of large-scale solid substrate fermentation (SSF) bioreactors is difficult. Though advanced control algorithms can handle most challenges encountered properly, for real-time SSF processes such controllers are expensive and time consuming to design and tune. With these considerations, advanced control algorithm tests using realistic simulations appear more appropriate. We used a phenomenological process model of an SSF pilot bioreactor, coupled with a realistic noise model, to test linear model predictive controllers. We focused on the effect noise has on the performance of the control algorithms, and how to enhance performance using a combination of low-pass (Butterworth) and outlier shaving (Hampel) filters. In simulations undertaken directly with the phenomenological model it was relatively straightforward to achieve good control performance. Nevertheless, control degraded sharply when the output of the phenomenological model was contaminated with noise using our realistic noise model, even with proper signal filtering.