FNSFood and Nutrition Sciences2157-944XScientific Research Publishing10.4236/fns.2012.36112FNS-20048ArticlesBiomedical&Life Sciences Characterization of Feed Properties for Conceptual Process Design Involving Complex Mixtures, Such as Natural Extracts anPablo Josch1SimonBoth1JochenStrube1*Institute for Separation and Process Technology, Clausthal University of Technology, Clausthal-Zellerfeld, Germany.* E-mail:strube@itv.tu-clausthal.de(JS);200620120306836850March 15th, 2012May 3rd, 2012 May 11th, 2012© Copyright 2014 by authors and Scientific Research Publishing Inc. 2014This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

The number of products used as agro-chemicals, food additives, flavors, aromas, pharmaceuticals and nutraceuticals which are made by fermentation or extraction from plants has increased significantly. Despite this growth, initial predictions for a potential product purification process for these complex mixtures remains entirely experimentally based. The present work represents an initial study to demonstrate the benefits of a systematic approach. For process development of chemically well-studied systems model based process design methods are already available. Therefore the proposed approach focuses on a method for the efficient characterization of the physical properties of the key components. Once this is adequately defined, unit operations and their potential to separate the feed components can be modeled. The current state of research is discussed. Based on this evaluation the most efficient method for conceptual process development has been identified and further developed. The resulting methodology consists of model-based cost accounting accompanied by experimental model-parameter determination. The latter is carried out at in miniaturized laboratory-scale measurement cells for each unit operation using the complete original feed. The model-based modelparameter determination from these experiments is accompanied by a comprehensive error analysis. The experimental plan currently includes the determination of thermodynamic equilibrium conditions in the mixture directly from the raw material mixture. Transport kinetics and fluid dynamic parameters are first estimated from known correlations or preexisting knowledge. Later on these parameters are determined exactly in mini-plant experiments. Furthermore, biological and botanical-based guidelines are developed to identify thermodynamically favored basic operations. Finally, the developed approaches are successfully validated using two plant extracts. Firstly, it could be proven that the botanical pre-selection can reduce the experimental plan significantly. Secondly, it was shown that the experimental equilibrium data of the kinetics and fluid dynamics can have a significant impact on the separation costs. Therefore, detailed rigorous modeling approaches have to be chosen instead of short-cut methods in order to make any valid process development conclusions or to further optimize the system.

Complex Mixtures; Process Synthesis; Conceptual Process Design; Modeling; Plant-Based Extracts1. Introduction

Usually the design and development of a separation process passes through multiple phases e.g. product development, basic and then detailed engineering. At the end of each phase a cost-driven decision to either continue or to abort the project must be made [1].

The amount and accuracy of information about the processes and systems under these considerations increases exponentially with development time. Simultaneously, the possibility of cost effective improvements in process management which can be developed with increasing knowledge, decreases (see Figure 1). Thus, over 70% of the manufacturing costs are already defined in the conceptual process design (CPD) and therefore the first development of the first flow-sheet set-up [2]. The fundamental limitation which has to be taken into account is the limited availability of feedstock, usually of the order of a few liters. At this stage of the project, when the probability of project failure is high, there is also limited analytical and experimental resource to be exploited.

Figure 1 shows that only improvements which are introduced in the product development or early basic engineering stages can reduce costs significantly. But these potential improvements require additional investment in detailed research and development at an early process

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