29D-15 |
Computer model based sensitivity analysis of bologna sausage cooking process |
C. CHEN1, M. Marcotte1, G. Piette1, S. Grabowski1, and H. S. Ramaswamy2. (1) Food Research & Development Centre, Agriculture & Agri-Food Canada, 3600 Casavant Blvd. W., Sainte-Hyacinthe, QC J2S 8E3, Canada, (2) Dept. of Food Science & Agricultural Chemistry, McGill Univ., Macdonald Campus, 21111 Lakeshore Rd., Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada Sensitivity analysis is essential for determining the impact of operating vairables in the range commonly encoutered on the dependent variable and is a key step for process design, control and optimization. The cooking process is one of important and necessary operations in Bologna sausage processing, and is related to the product's safety and quality. The objective of this study was to analyze the sensitivity of main processing variables on the corresponding process responses under constant smokehouse temperature processing conditions. Specifically, it included : 1) Sensitivity analysis of individual factor effects; 2) Development of multiple variable prediction models; 3) Determination of acceptable deviation ranges under the given control assumption. A pre-evaluated computer simulation program was used for the data generation under different processing conditions, and a dimensionless concept was applied for the sensitivity analysis of both input and output variables. The input variables involved: Process time (PT), smokehouse temperature (RT), diameter (D) and height (H), surface heat transfer coefficients (h), product thermal diffusivity (a). The process responses were: product center temperature (Tc), center cook value (Cc), volumetric (bulk) cook value (Cv), energy consumption (En), volumetric quality (Qv), surface quality (Fs). The order of importance of input process variables important were determined to be as follows: 1) for Tc, RT>D>PT>a>h; 2) for Cc, RT > PT >D>a>h>H; 3)for Cv, RT>PT>D>a>h>H; 4) for En, PT>RT>D; 5) for Qv, RT>PT>D> a>h; 6) for Fs, RT>PT>D>h>a. The center cook value (Cc) was the most affected response variable with respect to the processing conditions as compared to other response variables. A multiple regression model was developed for prediction of Cc as related to six major processing conditions and was further used for estimating the acceptable deviation ranges of both individual and multiple input variables to meet given control objectives. The ensitivity analysis study provides useful data for the fundamental undertanding of the process design and for optimization of bologna sausage processes for enhancing saftey and quality.
Session 29D, Food Engineering: Thermal processes
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