Computational Intelligence for Food Processing Systems:
Computational intelligence is a phrase coined by Professor Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta. We use it in a slightly different sense to describe the integration of advanced information processing technologies such as fuzzy sets and statistics in computer-based systems for process control and decision support. These techniques are complementary in terms of information content. Multivariate statistical tools are used to analyse quantitative data and to identify sources of variation and correlation between process variables and product quality. Fuzzy techniques are useful for representing linguistic information and for processing integrated data (i.e. numeric and non-numeric) for decision making.
The current area of application is forced-air drying operations. Drying is a common food processing operation that has substantial impact on food product quality (e.g. biological activity, rehydration characteristics). Control strategies must consider quality as well as economic factors such as productivity and energy costs. Our application to corn drying is relevant to food processing in Ontario but the general strategy can be extended to a number of other applications (e.g. high-value botanicals). The objective is to design a drying control system that preserves quality at user-defined levels and also achieves the highest moisture removal rates, given quality set points. The control system will be developed and tested on laboratory-scale equipment.
Microbial Risk Assessment:
The assessment of bacterial risks to food safety is becoming increasingly important to consumers, food processors and policy developers. It is a significant issue in Canadian manufacturing operations as well as international trade. A multi-disciplinary team of researchers from the University of Guelph, Brock University, Agriculture and Agri-Food Canada, Health Canada and the Ontario Ministry of Agriculture and Food, are working together to systematically collect and integrate data from laboratory experiments as well as primary production and secondary processing operations to develop mathematical tools that model spoilage and disease-causing behaviour of bacteria along the food chain.
One of the objectives is to develop qualitative modelling approaches that can serve as first steps in hierarchical assessment processes as well as components of Q2RA (qualitative and quantitative risk assessment) models. A completely qualitative approach will be developed for early-stage assessments when only minimal data and/or expert opinions are available. As data and parameter estimates for a system become available, the risk assessment model would move to a mixture of qualitative and quantitative elements. Hence data and information structures for the qualitative methods need to be compatible with quantitative model structures.
As they are developed, qualitative models will be tested with data for specific food systems (e.g. Campylobacter jejuni in poultry products, E.coli O157:H7 in ground beef).
Conrad, K. "Light degradation of juices packaged in polyester bottles",
M.Sc. thesis, Department of Food Science, University of Guelph, December,
Co-advisors: I.J. Britt and V.J. Davidson
Apple and orange juice packaged in bottles made of polyethylene terephthalate (PET), PET blended with 0.25, 1 and 4% polyethylene naphthalate (PEN), and PET blended with 0.25% PEN and 2% Amosorb were stored in dark, commercial fluorescent and UV light conditions for seven months. UV storage of apple juice in PET bottles resulted in ascorbic acid (AA) degradation rates over three times higher than in dark and commercial fluorescent storage. In UV, apple juice in PET bottles had an average degradation rate of 4.4 mg/L day, while bottles blended with 0.25,1, and 4% PEN gave rates of 2.67, 2.42, and 2.10 mg/L day, respectively. AA degradation rates in orage juice were 1.15, 1.10, 1.00, and 0.98 mg/L day for 0.25, 1, and 4% PEN, respectively. Juices stored in dark and commercial fluorescent lighting conditions darkened over time, while UV caused bleaching reactions. Colour loss was reduced in juices packaged in bottles containing PEN.