1 Knowledge Management of Durum Wheat Processing: From Research to Industry R. Thomopoulos, B Cuq, C. Molla, C Raz & J Abecassis Agro.M - INRA Montpellier.

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Presentation transcript:

1 Knowledge Management of Durum Wheat Processing: From Research to Industry R. Thomopoulos, B Cuq, C. Molla, C Raz & J Abecassis Agro.M - INRA Montpellier - UMR IATE

2 The Need for Knowledge Management Data on durum wheat-based foods processing and quality are… - Numerous - Incomplete - Miscellaneous - Sometimes divergent  Need of data integration and knowledge representation Problems about data integration and knowledge management

3 Objectives and Goals Objectives: Research project of global data integration and knowledge representation in the field of durum wheat based foods Development of a specific computerized Decision-Support – System (DSS) by cereal scientists and software makers Academia & Industry Knowledge about durum wheat based-food processing and qualities

4 Three Successive Actions (1) 1.DATA IDENTIFICATION AND CLASSIFICATION Determination of number & type of the available data about durum wheat based-food (processing & qualities) 2. DATA INTEGRATION 3. KNOWLEDGE MANAGEMENT

5 Three Successive Actions (2) 2. DATA INTEGRATION Development of a specific computerized decision-support- system to integrate all the available data 1. DATA IDENTIFICATION 3. KNOWLEDGE MANAGEMENT

6 Three Successive Actions (3) 3. KNOWLEDGE MANAGEMENT To help several users (breeders, scientists, industry, public institutions) 1. DATA IDENTIFICATON 2. DATA INTEGRATION

7 1 st task = Data Identification documents about processing and organoleptic, nutritional, hygienic characteristics of durum wheat-based foods (publication, review, patent,…) MethodsResultsReferences

8 2 nd task = Data Integration GRAINSEMOLINAFOOD 16 nutritional characteristics 20 organoleptic characteristics 10 hygienic characteristics 28 unit operations

9 X 46 characteristics = 1288 cells GRAINSEMOLINAFOOD 28 unit operations 16 nutritional characteristics 20 organoleptic characteristics 10 hygienic characteristics 2 nd task = Data Integration

10 (2 nd task) Computerized Decision Support System QualitiesUnit operations Qualities Unit operations OUTPUT INPUT INTEGRATION SYSTEM

11 QualitiesImpact of 1 unit operation on 1 quality Unit operations Qualities Unit operations OUTPUT INPUT INTEGRATION SYSTEM (2 nd task) Computerized Decision Support System

12 QualitiesImpact of 1 unit operation on 1 quality Unit operations Foods = Σ units operations Qualities Unit operations Foods OUTPUT INPUT INTEGRATION SYSTEM (2 nd task) Computerized Decision Support System

13 Bibliographic references Scientific documents QualitiesImpact of 1 unit operation on 1 quality Unit operations Foods = Σ units operations Qualities Unit operations Foods OUTPUT INPUT INTEGRATION SYSTEM (2 nd task) Computerized Decision Support System

14 Bibliographic references Scientific documents QualitiesImpact of 1 unit operation on 1 quality Unit operations Foods = Σ units operations Qualities Unit operations Foods OUTPUT Description Integration Modelling INPUT INTEGRATION SYSTEM (2 nd task) Computerized Decision Support System

15 (2 nd task) Quality Identification. ex = Nutritional Characteristics 8 groups of nutritional components - Starch - Mono- & oligo-saccharides -Fibres - Proteins - Lipids - Vitamins - Minerals - Polyphenols 2 nutritional values = Component content + Component property  16 nutritional characteristics x

16 2. Sub-components (and evaluation parameters) 3. Nutritional value (and units) (2 nd task) Quality Identification. ex = Nutritional Characteristics

17 1 st transformation2 nd transformation Wheat grain storage Grain cleaning Tempering Parboiling Debranning Milling Flour storage Ingredient addition Hydration Mixing Kneading Fermentation Agglomeration Oven coking Extrusion (low temperature) Sheeting Drying Extrusion - cooking Cooking in water Steam cooking Expansion Addition of other foods Packaging Thermal treatment Final product storage 25 unit operations (+ 3 products characteristics) (2 nd task) Unit Operation Identification. ex = From Wheat to End-products

18 1.Name and definition of unit operations 2. Unit operation parameters (and units) (2 nd task) Unit Operation Identification. ex = Cooking or Pre-cooking

19 1. Effect of unit operation on nutritional quality 2. Impact of unit operation parameters 3. Interactions with other unit operations 4. Cited literature 5. Experimental data 6. Mathematical model (2 nd task) Impact of Operation on Quality (data integration: 6 parts) Unstructured forms (text files) Structured forms Model forms

20 (2 nd task) Impact of Operation on Quality (Data Integration: Unstructured Form) Example of text form : Effect of unit operation on nutritional quality

21 Experimental data Component name Values (before Unit Op) Values (after Unit Op) % effect of Unit operation Ex : Structured form (2 nd task) Impact of Operation on Quality (Data Integration: Structured Form)

22 Tools and Technologies Necessity of a computerized system in order to :  Allow remote data input  Store the data (structured and weakly structured)  Manage data processing (computing, statistics, prediction)  Present information to users in an ergonomic way  Manage several user profiles (Academia and Industry)  Allow remote consultation

23 Expert who enters the data = CLIENT device Client/Server System Architecture User (Academia or Industry) = CLIENT device PRIVILEGED ACCESS Input / consultation LIMITED ACCESS Consultation only Internet or Intranet SYSTEM

24 Expert who enters the data = CLIENT device Client/server system architecture SERVER device User (Academia or Industry) = CLIENT device Web Server (Apache) Application (PHP Program) Internet or Intranet Structured data (MySQL relational database) Weakly Structured data (XML files) PRIVILEGED ACCESS Input / consultation LIMITED ACCESS Consultation only

25 (2 nd task) OUPUT Knowledge Description and Valorisation Available knowledge Specific Reviews Bibliographic lists Experimental data Models and simulations

26 Impact of 1 unit operation on 1 quality Unit Op Qlty Impact of process (∑ unit op.) on 1 quality Impact of process (∑ unit op.) on several qualities Unit Op Qlty Unit Op Qlty (2 nd task) OUPUT Knowledge Description and Valorisation Impact of 1 unit operation on several qualities Unit Op Qlty

27 Scientific update Ex : Changes in vitamin status during Pasta extrusion Unit operation simulation Ex.: Description of the changes in pasta firmness during cooking (2 nd task) OUPUT Knowledge Description and Valorisation Innovation and formulation Prediction of new ingredients behaviour Identification of critical unit operation in regards with quality loss Simulation of process behaviour for new wheat cultivars Nutritional data bases Integration of positive and negative effects of different unit operations to define and to optimize the best process conditions to produce the best product

28 HIGH POTENTIAL (!!!) HUGE WORK (!!!)  To set up an international scientific network to complete the Knowledge Database  To exploit the data and to improve our knowledge in various directions  To strengthen relationships between academic research and industry Conclusions & Perspectives

29 L’intelligence d’un homme se voit à l’usage qu’il fait de ce qu’il sait C’est un produit à considérer : Savoir x Intelligence = Valeur Paul Valéry