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  • Course Description

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Semester 4

Semester IV


Food Processing Technology
5 credits
Prerequisite(s): Food Commodity Science, Introduction to Food Technology
This course is a comprehension of food processing principles through application of chemistry, microbiology and food engineering. The course covers basic preservation methods (thermal processing, drying, low temperature preservation, and canning) and processing of agricultural sources such as sugar and wheat, tea, coffe, chocolate, and oil. The course also covers discussion of meat products (sausage, corned beef, ham, meat balls, curing, etc);  poultry produtcs (dried and frozen egg); milk products (butter, cheese, ice cream, condensed milk, and dried milk); and seafood products (surimi, kamaboko, canned fish, etc).


Food Processing Technology Lab.
2 credits
Prerequisite(s): Food Commodity Science, Introduction to Food Technology
The laboratory work is designed to improve analytical skills of the students. The topics include jam and jelly manufacture, noodle making, soybean products and bread making. The laboratory work also includes meat curing, production of ice cream, meat ball, sausages, surimi and kamaboko, as well as some fermented product, such as cider, yoghurt, etc.


Food Legislation
2 credits
Prerequisite(s): none
Food legislation covers the understanding of food legislation and regulation applied nationally and internationally.
 

Nutrition
4 credits
Prerequisite(s): Food Biochemistry
This subject provides the basic understanding of nutrient, function and role of nutrient (carbohydrate, lipids, protein, vitamin, and mineral), digestion, absorption and metabolism system, nutrient requirement factors involved in nutritional food selection, the role of nutrient in health care and evaluation of nutritional status.


Statistics
4 credits
Prerequisite(s): Mathematics
This course is a comprehension of basic concepts in statistic and their application, data types in statistic, control of tendencies and variance, five parameters of data, advantages and disadvantages of statistic, the testing of statistical software to make statistic descriptive. The course also includes applied statistics used in research including data collection, sampling method and data analysis (Regression and Correlation Analysis, Analysis of Variance, Non-parametric test). The subject will also discuss various experimental design such as single, two or more factors (Factorial Design, Complete Randomized Design, Complete Randomized Block Design, etc).


Ethics
3 credits
Prerequisite(s): none