Donkey Milk

UNIVERSITY OF PALERMO - SICILY (Italy) Department S.En.Fi.Mi.Zo - Animal production Sector - ANSC 400, CORNELL UNIVERSITY, 05/04/2006 Dr. Cristina Giosuè A System Dynamics application: “How to increase the total donkey milk production in Italy, producing profitability to the farmers?” PhD student in “PRODUZIONI FORAGGERE MEDITERRANEE” XVIII cycle Visiting fellow at Cornell University in the Departmnent of Animal Science

Outline
Introduction to System Dynamics modeling
Examples of System Dynamics application on a donkey milk production model

Introduction to System Dynamics modeling

What is System Dynamics and why it is important?
- The complexity of the systems in which we live is growing (accelerating economic, technological, social, and environmental changes)
- Many of the problems we now face arise as unanticipated side effect of our own past actions
- All too often the policies we implement to solve important problem fail, make the problem worse, or create new problems
CSDNet

System Dynamics is - perspective and set of conceptual tools that enable us to understand the structure and dynamics of complex systems - qualitative modeling method that enables us to build formal computer simulations of complex systems and use them to design more effective policies and organizations - a rigorous way to help thinking, visualizing, sharing, and communication of the future evolution of complex organizations and issues over time for the purpose of solving problems and creating more robust designs, reducing the likelihood of counterintuitive or unintended consequences What is System Dynamics and why it is important? CSDNet

Figure 1-3 in Sterman
Assumes a clear and linear response of results to our decision
Why unintended consequences ?
Event-oriented world view
Every event has a (single) cause
Leads to event-oriented problem solving

System Dynamics involve the use of :
Diagrams, graphs, words, and basic algebra to activate and capture existing knowledge about a particular observed problem situation
Frameworks to help both researchers and practitioners organize, filter and structure that knowledge
Mathematical simulation models and learning environments that help researchers and decision makers to identify more sustainable solutions and further refine their conceptual models
CSDNet

“ All models are wrong, some models are useful”
All models are simplifications and must omit elements of reality
Despite these omissions, “good models” can enhance our thinking and problem solving
All models have “clients”
Clients are people you must influence for your work to have impact
Help clients solve their problem……but also challenge their thinking

Examples of System Dynamics application on a donkey milk production model

The SD Modeling Process Iteration can occur from any step to any other Modeling effort will go through each of these step many times

The SD Modeling Process Iteration can occur from any step to any other Modeling effort will go through each of these step many times Real world Information feedback Mental models of real world Strategy, structure, decision rules Decisions (Organizational Experiments)

The researchable PROBLEM is: How to increase the total donkey milk production in Italy, producing profitability to the farmers?”…….. Problem articulation

… ..and WHY? Problem articulation

General problem (background) Food Allergies a) In the last 20 years the population of developed countries suffering food allergies has increased (from 5 to 10%), the children and the babies are the most affected (www.italiasalute.it) b) FA develop when intestinal immune system doesn’t respond normally to the food proteins or protein fragments which have escaped lumen hydrolysis Problem articulation

General problem (background) Food Allergies The main foods, that frequently cause allergy, are: egg (albumin), peanut, walnut,hazelnut, fish,shellfish, cow milk, chocolate, fruit (strawberry, pineapple, orange, tropical fruit ecc), cheese and vegetable (tomate ecc) ecc. The common symptoms of FA are: nausea, vomiting, abdominal pain, distension, flatulence and diarrhea; sometime skin and respiratory tract may be involved. Occasionally, severe systemic (anaphylactic) reactions are provoked and these reactions may be fatal (Sampson et al., 1996; Kimber et al., 2002). Problem articulation

General problem (background) Cow Milk Protein Allergy (CMPA) Cow milk protein allergy ( CMPA) is the most relevant with higher social implications in developed countries . Prevalence: 2-5% of the children and babies in the developed countries (Pizzin et al., 2003; Villoslada et al., 2005) and 1% in the adults (E. Smith, 1997). Problem articulation

CMPA Most children with CMPA synthesize specific immunoglobulin E to proteinic antigens (Iacono et al., 1992), such as α , β and k caseins, β lactoglobuline, α lactoalbumine and lactoferine (Teschemacher et al., 1997; F. Lara-Villoslada et al., 2005; CMPA in infancy and childhood) General problem (background) Problem articulation

CMPA Actual alternative feeding systems........ - Dietary products for infants derived from several different protein sources (such as bovine casein, bovine whey, bovine or porcine collagen, soy, or mixtures of these) exposed to different procedures of hydrolysis and further processing (heat treatment or ultrafiltration) - Dietary products based on amino acid mixtures (Fiocchi et al., 2003). General problem (background) Problem articulation

CMPA … ..but Some patients with CMAP can also react to these foods ( multiple food allergies) (Iannolino et al., 2005) General problem (background) Problem articulation

Researchable problem The donkey milk and CMPA Since 1990, in Italy, some researches in regard to donkey milk use on children with strong food allergies have started. In some regions of Italy the use of donkey milk to feed the babies is not new (in Sicily until the end of the Second War and in Germany) ( Oftedal et al., 1988). The economical, social changes and the industrial progress have caused an increase in the use of milk substitutes. Iacono et al. (1992) showed good results by the use of donkey milk on 9 babies with multiple food allergies. The donkey milk was well tolerated and no negative reactions were recorded. These results were confirmed by Carroccio et al. (2000) on 18/21 patients. Problem articulation

Milk composition (%) of different species and Energy (KJ/kg) (Polidori 1994) *Salimei et al., 1999; **Salimei et al, 2001; ***Polidori 1994 2855 0.22 6.69 0.40 1.64 3.38 12.43 87.57 Woman 1939*** 0.39 6.88 0.38** 1.72 0.38 8.84 91.16 Donkey* 4846 0.80 4.70 3.84 4.80 7.50 17.8 82.2 Cow buffalo 3399 0.73 4.47 3.10 3.41 4.62 13.23 86.77 Goat 5289 0.92 4.89 4.50 6.17 7.50 19.52 80.48 Sheep 2983 0.78 4.71 2.50 3.43 3.46 12.38 87.62 Cow Casein % Energy KJ/kg Ash % Lactose % Protein % Fat % Total solids % Water % Species

Average nitrogen composition of the milk in some species 14.0 4000 48.0 38.0 86.0 donkey 700 500 trace trace - (Lisozime, ppm) 10 45 45 90 Horse 11.4 5 – 7.43 8.7 – 7.13 4.66 Non proteic nitrogen 58.2 17.0 15.7 16.8 Whey protein (%) 30.4 78.0 75.6 78.5 Casein (%) 88.6 95.0 91.3 95.3 Protein (%) Woman Cow Goat Sheep

Some Milk Proteic Fractions + Jenness, 1980; *Doreau et Boulot, 1989; **Buscemi, 2000;***Ambruzzi, 2003 More investigations are necessary! 30-35 2.5 12 45 28 64 Cow+ 75 3.9 8.1 0 – 5(as1) 12,6(as2) 47 56 Goat+ No 30 60 β lactoglobuline (% of total wheyprotein) High 22 2-15 α lactoalbumine (% of total wheyprotein) no Yes Yes αs casein (% of casein) Yes Yes β casein (% of casein) Woman*** Yes Yes γ casein (% of casein) ? ? K casein (% of casein) Donkey** Horse*

Acidic composition of the donkey milk fat ( Chiofalo 2001) 0.86 Polynsaturated ω 3/ ω 6 8.65 Polyunsaturated ω 6 % 7.45 Polyunsaturated ω 3 % 16.60 Total Polyunsaturated % 15.82 Total Monounsaturated% 0.91 volatile, soluble saturated % 67.58 Total saturated % Average value

Essential Fatty Acids (EFAs) and human health EFAs are long-chain polyunsaturated fatty acids derived from linolenic ( Omega-3 ), linoleic ( Omega-6 ), and oleic acids ( Omega-9 ) (The number following "Omega-" represents the position of the first double bond, counting from the terminal methyl group on the molecule) Omega-9 is "non-essential" because the body can manufacture a modest amount on its own, provided essential EFAs are present EFAs are necessary fats that humans cannot synthesize, and must be obtained through diet and support the cardiovascular, reproductive, immune, and nervous systems by the production of prostaglandines (they are fundamental for growth in fetuses (by mother’s dietary intake) and children, particularly for neural development and maturation of sensory system (www.goodfats.pamrotella.com )

Essential Fatty Acids (EFAs) and human health Corn, safflower, sunflower, soybean, and cottonseed oils are also sources of linoleic acid, but are refined and may be nutrient-deficient as sold in stores. chicken Fish chestnut oil wheat germ oil black currant seed oil soybean oil evening primrose oil canola oil (cold-pressed and unrefined) olive oil, olives, borage oil some dark leafy green vegetables sunflower seeds (raw) Avocados pistachio nuts sesame seeds pine nuts Brazil nuts pumpkin seeds pumpkin seeds Grapeseed oil walnuts hempseed oil and hempseeds hempseed oil and hempseeds Flaxseed oil, flaxseeds and flaxseed meal Flaxseed oil (flaxseed oil has the highest linolenic content of any food), flaxseeds and flaxseed meal Foods that contain omega 6: Foods that contain omega 3:

Conjugated linoleic acids (CLA) and human health Mixture of positional and geometric isomers of linoleic acids with two double bonds, which can be different in the position and orientation ( cis or trans ) located on adjacent carbons. The main source of CLA in human diets: -food products derived from ruminants (meat and dairy products) The CLA are showing impressive range of beneficial health effects in biomedical studies with animal models, like: Anti-carcinogenic Anti-obesity and altered nutrient partitioning Anti-atherogenic and reduces cholesterol Enhance the immune system Enhance bone mineralization (Bauman & Lock, 2006)

Conjugated linoleic acids (CLA) cis -9, trans -11 CLA and trans -10, cis -12 CLA cis -9, trans -11 conjugated linoleic acid is the predominant CLA isomer found in ruminant fat including milk fat. CLA is produced as an intermediate in rumen biohydrogenation of linoleic acid present in the cows diet and a portion of the CLA in milk fat comes from that which has escaped complete biohydrogenation in the rumen. However, the majority is made by the cow herself using the desaturase enzyme and trans -11 18:1 (vaccenic acid), another fatty acid intermediate produced during rumen biohydrogenation. With certain diets the rumen environment is changed and a portion of the biohydrogenation produces, trans -10, cis -12 CLA and trans -10 C18:1 as intermediates. trans -10, cis -12 CLA is present at only trace levels in milk fat (Bauman & Lock, 2006) cis -9, trans -11 CLA

Trans vaccenic and CLA content in milk fat of different species in comparison with human milk fat (Jahreis et al., 1999)

Collaborative Research project : effect of different diet and oxytocin use on donkey milk fat yield and fatty acids composition
INVESTIGATORS:
Cornell University Department of Animal Science (USA) , Istituto Sperimentale Zootecnico per la Sicilia and University of Palermo Department SEn. Fi.Mi.Zo. (Italy)
OBJECTIVES:
To investigate changes in the pattern of donkey milk fatty acids, using two different diets, one of them with an extra virgin olive oil integration.
To investigate changes in donkey milk fat yield and fatty acids composition, using oxytocin

Researchable problem The donkey as livestock animal MILK
Medicine:
- PEDIATRICS - GERIATRICS - CARDIOLOGICS - FOR SOME TUMORS
Cosmetic industry
Problem articulation

Researchable problem The donkey as livestock animal MEAT
- brasato
Stracotto
- Smoked meat
Cold meat and
salami

Researchable problem The EU is showing a particular attention to promote the livestock production in marginal areas , to prevent and to stop the abandon of these rural areas, which can cause very relevant and negative consequences on the environment, the economical and social aspect. The donkey is a breed in extinction in developed countries, and this animal is presented in marginal areas, thanks its high resistance and adaptation capacity Problem articulation

Donkey breeds in Italy 6 main donkey breeds Martina Franca Sardo

Donkey breeds in Italy 6 main donkey breeds Amiata Asinara Romagnolo

Donkey breeds in Italy 6 main donkey breeds Ragusano Pantesco Sicilian

The donkey , which has used in the past to work the land and to transport, now as a livestock animal can be an alternative profitability resource for the marginal areas of the Mediterranean as well as for many agriculture areas of the developing countries, In relationship with the other income by the sale of donkey for meat and by other possible utilizations (trekking, brain gym, pet therapy)

The donkey milk is not included in the DPR 54/97
The sale can be only direct (from the farmer to the consumer) through autorization from the ASL (local sanitary agency) ( Regio Decreto 9 th May 1929 n° 994)
The VETERINARY INSPECTORATE has institued in Sicily a TECHNICAL AND SCIENTIFIC COMMITTEE to investigate more donkey milk production and health aspects, to establish policies and marketing strategies improving this new productive sector
Problem of Donkey milk sale in Italy

Dynamic problem definition
Define a “Reference Mode”
Graphs or other information showing the development of the relevant problem over time
The information about the donkey milk production and donkey milk consume is not registered by the statistical institutions in Italy;
The donkey indeed is not included into animals producing milk but only meat, considering the low incidence of this product and the actual selling and production restrictions.

In Italy, since 1960, donkey number has decreased highly (FAO 2005).

Qualitative reference mode of donkey milk production (liter/month)

Qualitative future reference mode of donkey milk production (liter/month)

It is important to define the relevant time horizon enough of past to show problem development enough into future to show possible delayed effects of potential policies
In this case I have chosen 8 years like time horizon, because I think that this can be enough to evaluate the results of application of different policies and strategies, increasing the milk production and then the milk available for the market
Problem articulation Dynamic problem definition

Dynamic Hypothesis
A proposed explanation for the behavior
Explicit structure that creates behavior
Provisional, subject to revision (working theory)
Endogenous focus
Behavior arising from within the system
Not (just) external shocks
Avoid “narrow” model boundaries

Tools for Dynamic Hypotheses
Model Boundary Chart
What variables included, excluded
What variables exogenous, endogenous
Causal Loop Diagrams (CLD)
Show causal linkages among variables
Focus on feedback structure
Stock-Flow Diagrams (SFD)
Characterize physical stock-flow structure
Dynamic Hypothesis

Population and birth rate loop INCREASE in population increases births, INCREASE in births increases population. This is a POSITIVE feedback loop , which will cause population to grow. Dynamic Hypothesis

Population and death rate loop Population INCREASES death rate, death rate DECREASES population This is a NEGATIVE or BALANCING feedback loop Dynamic Hypothesis

The simple system has two feedback loops These operate together to produce the behavior of the system. Population increases birth rate, birth rate increases population Population increases death rate, death rate decreases population Dynamic Hypothesis

Dynamic Hypothesis

Explicit delineation of stocks and flows
Stocks (states) are accumulations
Material or information
Can be counted at a given time
Change only through flows
Flows (rates) are quantities per some amount of time
Change states
Cannot be measured instantaneously
Can be affected by many other variables
Dynamic Hypothesis

“ State-rate” structure
Rates affect states, states affect rates
Units consistency for variables, equations
Explicit specification of units for each element
Dynamic Hypothesis

Graphical Representation Dynamic Hypothesis

Graphical Representation FBR and AL are Auxiliary Variables (neither stocks nor flows) Population also determines the birth and death rates in this case Dynamic Hypothesis

Stock and flows diagrams AGING CHAIN DONKEYS

Stock and flows diagrams MILK PRODUCTION, MILK DEMAND AND MILK PRICE

Stock and flows diagrams CONSUMER

Stock and flows diagrams FEED RESOURCE

Stock and flows diagrams DONKEY FARM SYSTEM

Stock and flows diagrams REVENUE, COSTS AND NET MARGIN

Mathematics of SD models
System of ordinary differential equations
Solved by numerical integration
S t = ∫(Inflow-Outflow) ds + S 0
Inflow = f(S, other variables)
Outflow = f(S, other variables)
Many software programs available
Vensim® is good for research purposes
Dynamic Hypothesis

Testing (Formulate Simulation Model)
An explicit mathematical representation
helps to :
Identify vague concepts
Resolve contradictions previously unnoticed
Provides a real test of understanding of the problem and its elements
Specification must be complete and consistent
Many softwares available
I’m using Vensim ® from Ventana Systems

Model Evaluation
Begins with first equation
Comparison of behavior in model to real world
Concepts in model should correspond to a meaningful real world concept
Check for
Dimensional consistency
Sensitivity to parameter changes
Response to “extreme conditions”

Policy Design and Evaluation
Modifications to relevant parameters
Creation of entirely new strategies and structures
Modifying the feedback structure
Reducing or eliminating the delays
Changing information flows
Altering decision rules
Assess sensitivity of policy results

And now a little bit of practice!
Milk production model

Thank you !

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Donkey Milk

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