A new dimensionless number (called Yield Index) was developed to measure the true raw material yield efficiency of a transformation process. To measure the Yield Index, a food processor should measure the actual production yield and compare this with the maximum production yield. However, for many food processors the maximum production yield is unknown because of the lack of knowledge. With a systematic approach and considerable research effort it is possible to build a model that can predict the maximum production yield with respect to raw material parameters, additions and final product specifications. This model can then be used to pinpoint unwanted mass losses in the production process. The thesis describes in a comprehensive way the development of two models to estimate the maximum production yield of French-fries production and poultry-processing (transforming broilers chickens into meat parts). These models were used in practice, to pinpoint unwanted mass losses during processing and based on this knowledge, both processes were improved significantly. Based on these two practical case studies a general system approach was developed to implement production yield analysis (PY A) in other types of food processes.
It was found that often a significant lack of knowledge in the true efficiency of the production processes exists. A PY A makes it possible to calculate the true yield efficiency of the process. This information is needed to convince management about the necessity to reduce unwanted losses. Not only to improve economics but also to improve aspects of modern sustainable food processing.
|Qualification||Doctor of Philosophy|
|Award date||31 Mar 2004|
|Place of Publication||Wageningen|
|Publication status||Published - 2004|
- food processing
- chips (French fries)
- raw materials
- processing losses