Sudut Pandang Rekayasa Proses Pangan dalam Mempelajari Fenomena Dasar pada Ilmu Pangan

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1 Sudut Pandang Rekayasa Proses Pangan dalam Mempelajari Fenomena Dasar pada Ilmu Pangan Kuantifikasi perubahan selama pengolahan/penyimpanan untuk penarikan kesimpulan. Contoh Kasus : Penentuan Umur Simpan Produk PURWIYATNO HARIYADI phariyadi.staff.ipb.ac.id REKAYASA PROSES PANGAN? Food process engineering is a broad field that is concerned with the application of engineering principles and concepts to the handling, manufacturing, processing and distribution of foods. (R P Singh, R.P. And Heldman, D.R Introduction to Food Engineering. Academic Press) 1

2 REKAYASA PROSES PANGAN? Food process engineering is concerned with feasibility and practicality, that is, will something work and how much will it cost? Food engineers are educated to analyze, synthesize, design, and operate complex systems that manipulate mass, energy, and information to transform material and energy into more useful form Valentas, K.J., Levine, L and Clark, J.P Food Processing Operation & Scale-up. Marcel Dekker Incorporated). REKAYASA PROSES PANGAN? Perkembangan 25 tahun terakhir... better value of foods Efisiensi. - Batch continuous processing - Improving process reliability - Reducing waste products, and - Effective energy utilization MAKE FOOD SAFETY 1970 ~1980 ~1990 ~2000 ~2013 2

3 REKAYASA PROSES PANGAN? Perkembangan 25 tahun terakhir... better value of foods MAKE + Melayani kebutuhan masyarakat; Convinience, food service SERVICE MAKE FOOD SAFETY 1970 ~1980 ~1990 ~2000 ~2013 REKAYASA PROSES PANGAN? Perkembangan 25 tahun terakhir... better value of foods + Care food business : Perawatan kesehatan, kebugaran Perawatan lingkungan Perawatan thd sosial fair trade MAKE SERVICE MAKE CARE SERVICE MAKE FOOD SAFETY 1970 ~1980 ~1990 ~2000 ~2013 3

4 REKAYASA PROSES PANGAN? KEDEPAN? Lebih personal: Perscribed food and Nutrition better value of foods MAKE SERVICE MAKE CARE SERVICE MAKE CARE SERVICE MAKE FOOD SAFETY 1970 ~1980 ~1990 ~2000 ~2013 ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information) 4

5 ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information) - Thinking like an engineer - You don't have to be an engineer to think like one. - Many cases where it is a definite advantage to think like an engineer. ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information) - Thinking like an engineer - You don't have to be an engineer to think like one. - Many cases where it is a definite advantage to think like an engineer. - You have to examine the process(es) involved in the problem to be solved. - You don t only look at the symptoms of a problem but looks at the processes involved to get to the root cause of the problem. 5

6 ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information) - Thinking like an engineer Use proven analysis methods. Find and use a set of methods that have been proven to work in analyzing problems. ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information) - Thinking like an engineer Use proven analysis methods. Find and use a set of methods that have been proven to work in analyzing problems. You have to know how to apply those methods BUT, more importantly, you have to know which methods to apply to a given situation. YOU have to know about and uses appropriate tools to carry those methods out. 6

7 ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information): - - Learns why (not just how) something is done. (If you only know how something is done, you will eventually do it wrong. You need to understand why something is done, to make sure that you are doing it correctly). - Must come up with an answer to the problem. ITP703 Anda sebagai Ahli Pangan - You have to produce (even though with imperfect information): Keep your skills updated. (Applying an out-of-date solution is almost as bad as not providing any solution. You have to constantly looks to see if new, better solutions to a problem exist). You must fully understand the Physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) 7

8 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Quotations of LORD KELVIN (Sir William Thomson) "To measure is to know." "If you can not measure it, you can not improve it." "In physical science the first essential step in the direction of learning any subject is to find principles of numerical reckoning and practicable methods for measuring some quality connected with it. I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of Science, whatever the matter may be." [PLA, vol. 1, "Electrical Units of Measurement", ] 8

9 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) BEWARE: Syndrome the latest version software garbage in garbage out I have one good news and one bad news. The good news is that statistical analysis in now easy to perform. The bad news is that statistical analysis in now easy to perform (Sastroasmoro, 2000) ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Perhatikan: "minimal experimental design" yang diperlukan, dll V o A B V o C D Rule of thumbs: 0,1 K m <[S]<10 K m [S] [S] 9

10 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Perhatikan: "minimal experimental design" yang diperlukan, dll Perhatikan: "Number & frequency of sampling yang diperlukan Obsreved Value T3 T t Storage Time (months) T1 < T2 < T3 T1 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Perhatikan: "minimal experimental design" yang diperlukan, dll Perhatikan: "Number & frequency of sampling yang diperlukan t T25 T30 T35 T40 t 1 t 1 t 1 t 1 t 1 t 2 t 2 t 2 t 2 t 2 t 3 t 3 t 3 t 3 t 3 t 4 t 4 t 4 t 4 t 4 Menghasilkan 1 data: k, T25C 10

11 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Perhatikan: "minimal experimental design" yang diperlukan, dll Perhatikan: "Number & frequency of sampling yang diperlukan Menghasilkan 1 data: k, T25C ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Minimal Experimental Design? Hati-hati dengan well established model : kinetika, reologi, dll 11

12 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Linier? A B ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) 12

13 ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) ITP703 Anda sebagai Ahli Pangan Back to basics: Understand the physical, chemical, biological + engineering phenomena behind the problem you are facing ( object or problem of your study ) Check! Theoretical background Assumptions Your data? Unit and dimensions Mass balance Energy balance Momentum balance ETC 13

14 Case 1. Kinetic of food quality changes during processing and storage - Understanding Shelf Life of Foods Department Food Science & Technology, Faculty of Agricultural Technology and Southeast Asian Food & Agricultural Science & Technology (SEAFAST) Center, Bogor Agricultural University Main References : Labuza,T Lecture Note ( Kilcast, D and Subramaniam, P. (Eds) The stability and shelf-life of food. Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England Hariyadi, P Handouts and Modules of Shelf Life Determination (in Bahasa Indonesia). Seafast Center/Department of Food Science and Technology, Faculty of Agriculture Technology, Bogor Agricultural University. 14

15 What is Shelf life? Everything has a shelf life What is Shelf life? The period between manufacture and retail purchase of a food product during which the product is of satisfactory quality (IFT; 1974). 15

16 What is Shelf life? The time during which the food product will : 1. remain safe; 2. be certain to retain desired sensory, chemical, physical and microbiological characteristics; 3. comply with any label declaration of nutritional data, when stored under the recommended conditions. (IFST Guidelines, 1993) What is Shelf life? Shelf-life as the period during which a food product maintains its microbiological safety and suitability at a specified storage temperature and, where appropriate, specified storage and handling conditions (Codex Alimentarius, CAC/RCP-46; 1999). 16

17 Open shelf-life dating Open Dating? Yahoo/Google? Open shelf-life dating Open dating is the use of dates (means the use of legible terms such as a day, month, and year; NOT a code, or a symbol) on a can or package of food that gives the consumer (including distributors, wholeseller or retailers) an indication of when the food was packaged or by when it should be sold or used. 17

18 Open shelf-life dating Why? 1. Encourages better handling practices by wholesalers, retailers, and consumers by expediting the sale or use of food near the end of shelf life. 2. Increase consumer confidence in the freshness of food purchased. 3. Better handling practices attributed to open dating could minimize nutrient loss. Open shelf-life dating Can be expressed as : 1. date of pack or manufacture, 2. pull date or sell-by date, 3. best-if-used-by date, 4. expiration date or use-by date, or 5. combination of two of the above. 18

19 Open shelf-life dating Expressed as Expiration date Date that indicates that before that date food products is still in satisfactory quality or desired condition (provided that product stored under the recommended conditions) END of shelf life Open shelf-life dating Expressed as Expiration date 19

20 Open shelf-life dating Expressed as Expiration date END of SHELF LIFE? What is satisfactory quality? What is desired? Except in situations in which microbiological safety is an issue, the definition of shelf-life is related to the positioning of the product in the market in terms of quality and customer perceptions of that quality. 20

21 END of SHELF LIFE? What is critical factor for customer perceptions of quality? What is specific quality properties? What is desired quality? What is satisfactory quality? Who determined desired / satisfactory quality? At what condition food product is not in satisfactory quality condition? How satisfactory quality changes during distribution, storage, display??? Kinetic of quality changes What is critical factor for customer perceptions of quality? Kilcast, D and Subramaniam, P. (Eds)

22 What is critical factor for customer perceptions of quality? Kilcast, D and Subramaniam, P. (Eds) What is critical factor for customer perceptions of quality? Kilcast, D and Subramaniam, P. (Eds)

23 What is critical factor for customer perceptions of quality? Kilcast, D and Subramaniam, P. (Eds) What is critical factor Factor for customer perceptions of quality? Which one? a. (Micro)biological factors : bacteria, mold, yeast b. Chemical factors : vit C., thiamin, riboflavin, etc c. Nutritional factors : protein, fats, digestion quality, etc d. Fucntionality factors : enzyme activity, probiotic acitivity, antioxidant activity, etc e. Physical factors: Viscosity, texture, color, emulsion stability, etc f. Organoleptic factor : Appearance quality, odor, taste, etc 23

24 What is critical factor Factor for customer perceptions of quality? Which one? What is critical factor for customer perceptions of quality? FACTORS INFLUENCING SHELF-LIFE OF FOODS A. intrinsic (properties of the final product) : Water activity (aw) (available water). ph value and total acidity; type of acid. Available oxygen. Nutrients. Natural microflora and surviving microbiological counts. Natural biochemistry of the product formulation (enzymes, chemical reactants). Use of preservatives in product formulation (e.g. salt). 24

25 What is critical factor for customer perceptions of quality? FACTORS INFLUENCING SHELF-LIFE OF FOODS B. Extrinsic factors (factors the final product encounters as it moves through the food chain) : Time temperature profile during processing. Temperature. Relative humidity (RH). Exposure to light (UV and IR). Environmental microbial counts. Composition of atmosphere within packaging. Subsequent heat treatment (e.g. Reheating/cooking before consumption). Consumer handling. PRINCIPLES OF SHELF LIFE DETERMINATION Experiments & Analysis Emperical Analysis SHELF LIFE Informations needed : Quality critical factor(s)? Value of critical factor(s) Maximum value (quality at the factory gate) Minimum value of critical factor(s) : minimum quality at the end of shelf-life Kinetic parameters for quality changes (E a, Q 10 ) 25

26 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES A B -da/dt = ka n Measure either loss of A, desirable quality marker, or production of B, undesirable quality marker A = quality t = time k = rate constant n = reaction order PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Zero order (n=0) quality changes -da/dt = ka n 26

27 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Zero order (n=0) quality changes -da/dt = k z or A= A 0 -k z t PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Zero order (n=0) quality changes -da/dt = k z or A= A 0 -k z t If Q s is quality level at the end of shelf life, then A s = A 0 -k z t s or t s = (A 0 -A s )/ k z at which t s is shelf life of the product 27

28 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Just Illustration: Zero order (n=0) quality changes -da/dt = k z or A t = A 0 -k z t A o = 100 units at time zero A = 60 units at 20 weeks What is k z if quality change follow zero order? Remember, k z is a slope Y/ X = (100-60)/(20-0)= 40/20 = 2 units per day Thus 2 units per day x 20 days is loss of 40 units (with 60 units of quality left) PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Quality Value Firts order (n=1) kinetic of quality changes -da/dt = ka 1 -da/dt = k f A Storage Time (months) 28

29 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Firts order (n=1) kinetic of quality changes -da/dt = ka 1 -da/dt = k f A or ln (A/A 0 ) = - kt PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Firts order (n=1) kinetic of quality changes -da/dt = k A 1 or ln (A/A 0 ) = - k f t 29

30 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Firts order (n=1) kinetic of quality changes -da/dt = k A 1 or log (A/A 0 ) = - (k f /2.3)t PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Firts order (n=1) kinetic of quality changes -da/dt = ka or ln (A/A 0 ) = - k f t If A s is A at the end of shelf life, then ln (A s /A 0 ) = - k f t s Or t s = [ln(a 0 /A s )]/k f Or t 1/2 = 0,693/ k f At which t s is shelf life of product 30

31 PRINCIPLES OF SHELF LIFE DETERMINATION KINETIC OF QUALITY CHANGES Firts order (n=1) kinetic of quality changes -da/dt = ka or ln (A/A 0 ) = - k f t Just Illustration : Ao = 100 units at time zero A = 60 units at 20 weeks What is k f if quality changes follows first order? Remember slope is Y/ X but on Ln scale so = (Ln( 60/100))/(20-0) = 0.51/20 = day-1 A= A o e -k f t A= 100 x e x20 = 100 x e = 60 PRINCIPLES OF SHELF LIFE DETERMINATION Examples of kinetic of quality change of slecetd product during storage/processing Zero Order Overall quality of frozen food Non-enzimatic browning First Order Vitamin loss/degradation Mikcorbial inactivation Oxidatif deterioration of color Thermal degradation of texture 31

32 Zero or First Order Kinetics? Quality degradation during storage : Difference between zero and first order kinetics Zero or First Order Kinetics? Quality degradation during storage : Difference between zero and first order kinetics 32

33 Zero or First Order Kinetics? Quality degradation during storage : Difference between zero and first order kinetics Zero or First Order Kinetics? Quality degradation during storage : Difference between zero and first order kinetics 33

34 Zero or First Order Kinetics? Quality degradation during storage : Difference between zero and first order kinetics Zero or First Order Kinetics? Zone of data that may distinguish between zero and first orfer kinetics Quality degradation during storage : Difference between zero and first order kinetics x 34

35 Zero or First Order Kinetics? Published values (27.7 o C) Quality degradation during storage : Difference between zero and first order kinetics To be able to distinguish easily wwther quality changes is following zero or first order; perform experiment until the extent of quality loss is more than 50% Zero or First Order Kinetics? Recommendation (Labuza, T. 2007) If few data points with time and End Quality level is less than 50% change from initial Then KISS : Use zero order 35

36 Case 2: Predicting Shelf life of Food by Accelerated Shelf-life Testing (ASLT) method Using Arrhenius model Department Food Science & Technology, Faculty of Agricultural Technology and Southeast Asian Food & Agricultural Science & Technology (SEAFAST) Center, Bogor Agricultural University Main References : Labuza,T Lecture Note ( Kilcast, D and Subramaniam, P. (Eds) The stability and shelf-life of food. Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England Hariyadi, P Handouts and Modules of Shelf Life Determination (in Bahasa Indonesia). Seafast Center/Department of Food Science and Technology, Faculty of Agriculture Technology, Bogor Agricultural University. 36

37 Accelerated Shelf Life Test Arrhenius Method Principles : accelerate rate of quality loss by increasing temperature of storage Quality loss -da/dt = ka n Rate constant (k) depends on Temperature : k = k 0.exp -Ea/RT k = rate constant k 0 = frequency factor (NOT as function of T) Ea = Activation Energy T = Absolute Temperature (K) R = Gas constant; 1,986 kal/mol (8.314 J/mol.K) Accelerated Shelf Life Test Arrhenius Method k k = k o e - E a R T (1/T) Valeu of k as affected by temperature (T) Arrhenius Plot 37

38 Accelerated Shelf Life Test Arrhenius Method Ln k o Ln k Slope -Ea/R Ln k = Ln k o - (Ea/R)(1/T) (1/T) Arrhenius Plot Accelerated Shelf Life Test Arrhenius Method Know your product WELL! Example : Carbohydrate at amorphous condition may undergoes crystalization at low temperature. Retrogradation Texture hardening Release of water Bread staling 38

39 Accelerated Shelf Life Test Arrhenius Method Know your product WELL! Example : Carbohydrate at amorphous condition may undergoes crystalization at low temperature. Rate of bread staling incease as temperature of storage decrease (4 C - 40 C) Maximum staling rate : 4 C. Accelerated Shelf Life Test Arrhenius Method Know your product WELL! Arrhenius anomali. Effect of temperature on bread staling Negative Ea Ea" = - 9 kcal/mol.. Ln (staling rate) /T x

40 Accelerated Shelf Life Test Arrhenius Method -- in Practices Value of Quality Marker 100 T1 < T2 < T T T3 T Storage Time (months)! Number & frequency of sampling Accelerated Shelf Life Test Arrhenius Method -- in Practices (1a) Do experiment and measurement of quality loss at least- at 3 different temperatures of storage Statistical problems Can t do predictions with one temperature ln k? 1/T 40

41 Accelerated Shelf Life Test Arrhenius Method -- in Practices (1a) Do experiment and measurement of quality loss at least- at 3 different temperatures of storage Statistical problems Can t do predictions with one temperature Two points always give a straight line ln k 1/T Accelerated Shelf Life Test Arrhenius Method -- in Practices (1a) Do experiment and measurement of quality loss at least- at 3 different temperatures of storage Statistical problems Can t do predictions with one temperature Two points always give a straight line Three points give poor statistics ln k 1/T 41

42 Accelerated Shelf Life Test Arrhenius Method -- in Practices (1b) Choose temperature of storage higher that normal T of storage Temperature od storage will not cause changes in mechanism of quality loss Again; know your product WELL hub Arrhenius: ln k Range of ASLT Temperature Range Of Storage Temp Maximum ASLT Temperature A B 1/T Accelerated Shelf Life Test Arrhenius Method -- in Practices (2) So, which three (3) different temperatures of storage? Know your product WELL Type of Product Temperature of ASLT ( C) Control Temperature ( C) Canned foods 30, 35, 40, 45 4 Dried foods 30, 35, 40, Chilled Products 5, 10, 15, 20 0 Frozen products -5, -10, -15 <

43 Accelerated Shelf Life Test Arrhenius Method -- in Practices (3a) Frequency of sampling Know your product WELL Accelerated Shelf Life Test Arrhenius Method -- in Practices (3a) Frequency of sampling Know your product WELL Shelf life at 5 o C= 12 months If Q 10 =2 ASLT (at 25 o C) : 3 months If Q 10 =3 ASLT (at 25 o C) : 1.3 months If Q 10 =4 ASLT (at 25 o C) : 23 days Number of samples? Statistical problems Can t do predictions with one temperature Two points always give a straight line Three points give poor statistics 43

44 Accelerated Shelf Life Test Arrhenius Method -- in Practices (4) Value of k at normal storage condition May be predicted/calculated using Arrhenius Equation : k = k o.exp -Ea/RT ln k = ln k o Ea/R (1/T) k1 k2 And, extrapolate value of k at normal T of storage: Ln k T 1 T 2 T 3 k3 Zone of experiment - accelerated Ta (normal T of storage) 1/T Accelerated Shelf Life Test Arrhenius Method -- in Practices (5) Determinn A s (quality value at end of shelf life). Standard of identity, SNI, etc Sensory properties Shelf life may be predicted using : t s = (A 0 -A s )/k z ; if quality changes follow zero order kinetics t s = [ln(a 0 /A s )]/k f ; if quality changes follow first order kinetics 44

45 Accelerated Shelf Life Test Arrhenius Method -- in Practices (6) Accelerated Shelf Life Test Arrhenius Method -- in Practices (7) 45

46 Accelerated Shelf Life Test Arrhenius Method -- in Practices (8) Accelerated Shelf Life Test Arrhenius Method -- in Practices (9) 46

47 Accelerated Shelf Life Test Arrhenius Method -- in Practices (10) Accelerated Shelf Life Test Arrhenius Method -- in Practices (11) 47

48 Accelerated Shelf Life Test Arrhenius Method -- in Practices (12) Accelerated Shelf Life Test Arrhenius Method -- in Practices (13) Degree of losses of selected vitamin predicted using Arrhenius model as compared to its actual losses Losses (%) after 6 months of storage, 20 o C, RH 75% Vitamin Predicted by Result of Arrhenius Model Analysis Vitamin C (ascorbic acid) 24,0 23,0 Vitamin A 15,0 10,0 Folic Acid 8,1 7,4 Vitamin B12 9,2 7,7 48

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50 Thank you terimakasih 50