Integrated product and process design approach for rationalization of food products. Almeida-Rivera, C., Jain, P., Bruin, S., & Bongers, P. Volume 24 of Computer Aided Chemical Engineering, Elsevier, 2007. Website abstract bibtex To quantify rationalization of ingredients and to realize its opportunity during process synthesis, in this contribution we propose an integrated product and process design approach for foods. According to this methodology, once the product concept and geographical market are decided, product attributes that drive consumer liking are identified and quantified. The product attributes are either of sensorial or analytical nature. The identification and quantification of this relationship is obtained by means of data mining techniques. Relevant sensorial and analytical attributes are used, afterwards, to create alternatives for possible microstructures and ingredients. Subsequently, the ingredients are used as inputs for process synthesis to find optimal process to deliver required analytical/sensorial attributes through desired microstructures. The ingredients are related to analytical and sensorial attributes through mathematical process and ingredients models, respectively. We integrate this methodology with a modified Douglas' methodology for food products. By putting together mathematical relationships between consumer liking attributes, product attributes and ingredients and processes, a quantitative rationalization can be achieved. An oil-in-water mayonnaise-like emulsion was used as case study.
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abstract = {To quantify rationalization of ingredients and to realize its opportunity during process synthesis, in this contribution we propose an integrated product and process design approach for foods. According to this methodology, once the product concept and geographical market are decided, product attributes that drive consumer liking are identified and quantified. The product attributes are either of sensorial or analytical nature. The identification and quantification of this relationship is obtained by means of data mining techniques. Relevant sensorial and analytical attributes are used, afterwards, to create alternatives for possible microstructures and ingredients. Subsequently, the ingredients are used as inputs for process synthesis to find optimal process to deliver required analytical/sensorial attributes through desired microstructures. The ingredients are related to analytical and sensorial attributes through mathematical process and ingredients models, respectively. We integrate this methodology with a modified Douglas' methodology for food products. By putting together mathematical relationships between consumer liking attributes, product attributes and ingredients and processes, a quantitative rationalization can be achieved. An oil-in-water mayonnaise-like emulsion was used as case study.},
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author = {Almeida-Rivera, Cristhian and Jain, Puneet and Bruin, Solke and Bongers, Peter}
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