Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

INSTITUTE OF SCIENCE / GM-729 - FOOD ENGINEERING (DOCTORATE DEGREE)

Code: GM-729 Course Title: MODELING AND OPTIMIZATION IN FOOD ENGINEERING Theoretical+Practice: 3+0 ECTS: 6
Year/Semester of Study 1 / Fall Semester
Level of Course 2nd Cycle Degree Programme
Type of Course Optional
Department FOOD ENGINEERING (DOCTORATE DEGREE)
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer FEYZA KIROĞLU ZORLUGENÇ (fkzorlugenc@nevsehir.edu.tr)
Name of Lecturer(s)
Language of Instruction Turkish
Work Placement(s) None
Objectives of the Course
Determination of the factors which are important in food processing as mathematical

Learning Outcomes PO MME
The students who succeeded in this course:
LO-1 To gain knowlede about establishment of experimental design by using softwares PO-1 Has the skills of accessing, evaluating, interpreting and applying the knowledge in the area of engineering
PO-2 Has the skills of designing, applying and evaluating scientific research
PO-4 Has the skills of developing methods in constructing and solving engineering problems
Examination
Performance Project
LO-2 To gain knowledeg establishment of mathematical models PO-1 Has the skills of accessing, evaluating, interpreting and applying the knowledge in the area of engineering
PO-2 Has the skills of designing, applying and evaluating scientific research
PO-3 Integrates knowledge from different disciplines
PO-6 Has extensive knowledge about modern techniques and methods applied in food technology
PO-13 Plays an active role in the solution of the problems of food industry
Examination
Performance Project
PO: Programme Outcomes
MME:Method of measurement & Evaluation

Course Contents
Determination of the factors which are important in food processing as mathematical; Modelling of the independent parameters based on temperature and time; Modelling of obtained data by using softwares; Analysis of obtained equations; Design and optimization of the experiment including more than two factors.
Weekly Course Content
Week Subject Learning Activities and Teaching Methods
1 Description of dependent and independent variables and applications in food industry Lecture, discussion or Distance Learning
2 Determination of the factors which are important in food processing as mathematical Lecture, discussion or Distance Learning
3 Modelling of the dependent varibles based on temperature and time Lecture, discussion or Distance Learning
4 Description of the softwares to be used in modelling purposes Lecture, discussion or Distance Learning
5 Main properties of the softwares Lecture, discussion or Distance Learning
6 Design of the expriment Lecture, discussion or Distance Learning
7 Modelling of the obtained data by using non linear regression models Lecture, discussion or Distance Learning
8 mid-term exam
9 Numerical analysis methods of obtained equations Lecture, discussion or Distance Learning
10 Numerical analysis methods of obtained equations Lecture, discussion or Distance Learning
11 Optimization and design of the experiments including more than two factors Lecture, discussion or Distance Learning
12 Applications Lecture, discussion or Distance Learning
13 Applications Lecture, discussion or Distance Learning
14 Applications Lecture, discussion or Distance Learning
15 Applications Lecture, discussion or Distance Learning
16 final exam
Recommend Course Book / Supplementary Book/Reading
1 İstatistik: Yöntemler ve Uygulamalar. Hüsnü Arıcı. Meteksan, Ankara. 1997.
Required Course instruments and materials

Assessment Methods
Type of Assessment Week Hours Weight(%)
mid-term exam 7 3 40
Other assessment methods
1.Oral Examination
2.Quiz
3.Laboratory exam
4.Presentation
5.Report
6.Workshop
7.Performance Project
8.Term Paper
9.Project
final exam 14 3 60

Student Work Load
Type of Work Weekly Hours Number of Weeks Work Load
Weekly Course Hours (Theoretical+Practice) 3 14 42
Outside Class
       a) Reading 0
       b) Search in internet/Library 0
       c) Performance Project 3 2 6
       d) Prepare a workshop/Presentation/Report 0
       e) Term paper/Project 0
Oral Examination 0
Quiz 0
Laboratory exam 0
Own study for mid-term exam 4 5 20
mid-term exam 10 5 50
Own study for final exam 5 5 25
final exam 10 5 50
0
0
Total work load; 193