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Knowledge Management of Durum Wheat Processing: From Research to Industry

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. The Need for Knowledge Management. Data on durum wheat-based foods processing and quality are… Numerous Incomplete

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Knowledge Management of Durum Wheat Processing: From Research to Industry

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  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 Problems about data integration and knowledge management  Need of data integration and knowledge representation

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

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

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

  7. 1st task = Data Identification 27 000 documents about processing and organoleptic, nutritional, hygienic characteristics of durum wheat-based foods (publication, review, patent,…) Methods Results References

  8. 2nd task = Data Integration 28 unit operations GRAIN SEMOLINA FOOD 16 nutritional characteristics 20 organoleptic characteristics 10 hygienic characteristics

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

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

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

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

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

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

  15. (2nd 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 x  16 nutritional characteristics

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

  17. (2nd task) Unit Operation Identification.ex = From Wheat to End-products 25 unit operations (+ 3 products characteristics)

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

  19. (2nd task) Impact of Operation on Quality(data integration: 6 parts) 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 Unstructured forms (text files) Structured forms Model forms

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

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

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

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

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

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

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

  28. Conclusions & Perspectives • 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

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

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