Estimation of the food product quality using fuzzy sets

Author

Perrot, Nathalie ; Bonazzi, Catherine ; Trystram, Gilles ; Guely, François

Author_Institution

Cemagref, Aubiere, France

fYear

1999

fDate

36342

Firstpage

487

Lastpage

491

Abstract

The estimation of food product quality using fuzzy sets is discussed in this paper through two specific examples: (i) prediction of the luminance of biscuits during a baking process, and (ii) prediction of wet-milling quality of maize during a drying process. Two fuzzy approaches are validated: a black-box approach and a knowledge-based approach to modeling. The results are good and coherent in both cases and the models are robust. Nevertheless, the fuzzy knowledge-based modeling approach is particularly pertinent and adaptable to food process engineering research

Keywords

brightness; drying; engineering computing; food processing industry; fuzzy logic; fuzzy set theory; knowledge based systems; modelling; quality control; uncertainty handling; baking process; biscuit luminance prediction; black-box modeling approach; drying process; food process engineering research; food product quality estimation; fuzzy knowledge-based modeling approach; fuzzy sets; maize wet-milling quality prediction; robust models; Design for experiments; Equations; Food products; Fuzzy logic; Fuzzy sets; Knowledge engineering; Productivity; Robustness; State estimation; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American

Conference_Location

New York, NY

Print_ISBN

0-7803-5211-4

Type

conf

DOI

10.1109/NAFIPS.1999.781741

Filename

781741