Interpreting the neural networkfor prediction of fermentation of thick juice from sugar beet processing

Evaluation of the fermentation of high gravity thick sugar beet juice worts for efficient bioethanol production

BACKGROUND Sugar beet and intermediates of sugar beet processing are considered to be very attractive feedstock for ethanol production due to their content of fermentable sugars. In particular, the processing of the intermediates into ethanol is considerably facilitated because it does not require pretreatment or enzymatic treatment in contrast to production from starch raw materials. Moreover,...

Ethanol fermentation of sugar beet thick juice diluted with crude cheese whey by the flex yeast Kluyveromyces marxianus KD-15

The fermentation of sugar-beet pulp silage.

Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks

Thermal processing of the key lime juice leads to the inactivation of pectin methylesterase (PME) and the degradation of ascorbic acid (AA). These changes affect directly the cloud stability and color of the juice. In this study, an artificial neural network (ANN) model was applied for designing and developing an intelligent system for prediction of the thermal processing effects on the physico...

Noteworthy Facts about a Methane-Producing Microbial Community Processing Acidic Effluent from Sugar Beet Molasses Fermentation

Anaerobic digestion is a complex process involving hydrolysis, acidogenesis, acetogenesis and methanogenesis. The separation of the hydrogen-yielding (dark fermentation) and methane-yielding steps under controlled conditions permits the production of hydrogen and methane from biomass. The characterization of microbial communities developed in bioreactors is crucial for the understanding and opt...