1977
DOI: 10.1128/aem.34.6.725-732.1977
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Dialysis Continuous Process for Ammonium-Lactate Fermentation of Whey: Mathematical Model and Computer Simulation

Abstract: A mathematical model was developed to describe a dialysis process for the continuous fermentation of whey lactose to lactic acid, with neutralization to a constant pH by ammonia. In the process, whey of a relatively high concentration is fed into the fermentor circuit at a relatively low rate so that the residual concentration of lactose is low. The fernentor effluent contains ammonium lactate, bacterial cells, and residual whey solids and could be used as a nitrogenenriched feedstuff for ruminant animals. Onl… Show more

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Cited by 23 publications
(9 citation statements)
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“…Altogether, the results demonstrated the validity of the mathematical model, which then was used to guide experimental tests for the ammonium-lactate fermentation of deproteinized whey. The improved model predicted the same effects of changes in the various parameters on the process and the same regions for experimental tests as did the previous model (4).…”
Section: Computer Simulations Previous Experimental Results With Wholmentioning
confidence: 65%
See 3 more Smart Citations
“…Altogether, the results demonstrated the validity of the mathematical model, which then was used to guide experimental tests for the ammonium-lactate fermentation of deproteinized whey. The improved model predicted the same effects of changes in the various parameters on the process and the same regions for experimental tests as did the previous model (4).…”
Section: Computer Simulations Previous Experimental Results With Wholmentioning
confidence: 65%
“…Thus, by 4 weeks into the fermentation, the permeability factor decreased by 50%. Coulman et al (4) showed that a fl of 2.0 should be used for the process to obtain suitable relief from product inhibition.…”
Section: X~)mentioning
confidence: 99%
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“…This work aims to demonstrate that Artificial Neural Networks (ANNs) are adequate to this task, due to their features of massive parallel computing and representation, ability to learn, adaptability and generalization [4]. ANNs, and in particular Multilayer Perceptrons (MLPs) used in this case, are mainly characterized by the topology of connections between neurons, the training algorithm and the activation function [3,2]. The choice of which ANN will be used to represent a process depends on the characteristics of the problem in question [7].…”
Section: Introductionmentioning
confidence: 99%