Quality of protein declaration on prepackaged food products modelled in fuzzy logic
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Date
JUNE 2019
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Abstract
Food labelling laws aim to protect consumers from deception. This study was to
determine the accuracy of food protein labelling in prepackaged food products on the
Ghanaian market and to identify the need for the establishment of a national tolerance
criterion. Twenty-six (26) food products from Accra and Kumasi were grouped into
Dairy, Cereals, Fish, Peas and Confectionery products. Their protein contents were
determined using Kjeldahl with 5.7 Jones factor for Cereals and 6.25 for other samples.
Fuzzy logic and modelling (MATLAB toolbox) was used to analyze the two input
variables (product category and net weight) of the products and their output variable
(Confidence quotient). The term confidence quotient, which was used to describe the
degree of accuracy, was defined in the study as the difference between the declared and
the mean laboratory analyzed protein values. The accuracy of the declared protein was
considered “low” or “high” according to the confidence interval; 90%, 95%, and 99%,
used and the principal protein tolerance acceptance criterion (≥80%). The results from
the distribution and fuzzy model demonstrated significant variations at which most
protein contents were misrepresented in the products. It was revealed that the categories
and net weight of the products appeared to have contributed to this variation. The results
offer a prediction tool to understand the likelihood of inaccuracy of declared nutrient
contents on prepackaged food products using protein as a test factor in establishing a
national tolerance criterion.
Description
A thesis submitted to the Department of Food Science and Technology, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement to the award of Msc. Degree in Food Quality Management
Keywords
Prepackaged food products, Market