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ENVIRONMENTAL RISK
ASSESSMENT OF
GENETICALLY MODIFIED
ORGANISMS
F. Camastra, A. Ciaramella, V. Giovannelli, M.
Lener, V. Rastelli, A. Staiano, G. Staiano, A.
Starace
WIRN 2013 - XXIII Italian Workshop on Neural Networks
Vietri sul Mare, Salerno, ItalyMay 23rd 2013
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, Italy
Contents
 Introduction
 Environmental Risk Assessment (ERA)
 Fuzzy Decision Support System
 System Validation
 Conclusions and Future Works
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Introduction
 Genetically Modified Organism (GMO)
 organism altered using genetic engineering
techniques
 ADVANTAGES
 GM Crop plant
 resistant to herbicide, pests, diseases or
environmental conditions
 with improved nutritional or pharmaceutical properties
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
BUT …
 Risks that might impact on:
 Consumers
 Man, Animals (e.g., butterflies)
 Natural environment
 Natural habitats, Soil
 European directives assess and manage GMO
risks
 The notifier, i.e., the person who requests the
GMO release, must perform an ERA
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Environmental Risk
Assessment (ERA)
1. Preliminary identification of risks
 available scientific database and literature
2. Effects on non-target species
 BT toxin and butterflies
3. Effects on natural environment
 Compatible wild plants
4. Management of the risk
 mitigation measures
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
The Conceptual Model
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Overview of ERA process
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
System architecture
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
The Electronic Questionnaire
 As a web application
 Different kinds of questions:
 Textual
 Numerical
 Date
 Linguistic
 Multiple choice
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Textual question
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Numerical question
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Date question
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Linguistic question
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Multiple choice question
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
The Fuzzy Decision Support
System
(FDSS)
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Fuzzifier
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Fuzzy rule base
IF vegetative cycle duration IS
High
AND cultural cycle duration IS
Low
THEN phenological risk IS Low
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Inference engine
IF vegetative cycle duration IS
High
AND cultural cycle duration IS
Low
THEN phenological risk IS Low
IF vegetative cycle duration IS
High
AND cultural cycle duration IS
High
THEN phenological risk IS High
…
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Defuzzifier
IF vegetative cycle duration IS
High
AND cultural cycle duration IS
Low
THEN phenological risk IS Low
IF vegetative cycle duration IS
High
AND cultural cycle duration IS
High
THEN phenological risk IS High
…
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Report
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
 Open source library
 http://jfuzzylogic.sourceforge.net/html/index.html
 Fuzzy Control Language (FCL)
specification
 Aggregation, Activation and Accumulation
methods
 Supports continue, discrete or custom
membership functions
 Flexible and extensible FDSS
jFuzzyLogic
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
System validation
 The Fuzzy Decision Support System has been
tested
 by producing about 150 ERAs
 by submitting the produced inferences to a pool of
ISPRA experts
 not involved in the rule definition
 to assess the consistency and completeness of
the system
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Scenario 1
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Scenario 2
May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013
Conclusions and Future Works
 Fuzzy Decision Support System
 identify potential impacts that can achieve one
or more receptors through a set of migration
paths
 validated on Bt-maize1 and Brassica napus2
by the human experts of ISPRA
 Future works
 Machine learning algorithms to learn the
FDSS knowledge base1 GM maize
2 GM colza

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Wirn2013

  • 1. ENVIRONMENTAL RISK ASSESSMENT OF GENETICALLY MODIFIED ORGANISMS F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace WIRN 2013 - XXIII Italian Workshop on Neural Networks Vietri sul Mare, Salerno, ItalyMay 23rd 2013
  • 2. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, Italy Contents  Introduction  Environmental Risk Assessment (ERA)  Fuzzy Decision Support System  System Validation  Conclusions and Future Works
  • 3. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Introduction  Genetically Modified Organism (GMO)  organism altered using genetic engineering techniques  ADVANTAGES  GM Crop plant  resistant to herbicide, pests, diseases or environmental conditions  with improved nutritional or pharmaceutical properties
  • 4. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 BUT …  Risks that might impact on:  Consumers  Man, Animals (e.g., butterflies)  Natural environment  Natural habitats, Soil  European directives assess and manage GMO risks  The notifier, i.e., the person who requests the GMO release, must perform an ERA
  • 5. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Environmental Risk Assessment (ERA) 1. Preliminary identification of risks  available scientific database and literature 2. Effects on non-target species  BT toxin and butterflies 3. Effects on natural environment  Compatible wild plants 4. Management of the risk  mitigation measures
  • 6. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 The Conceptual Model
  • 7. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Overview of ERA process
  • 8. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 System architecture
  • 9. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 The Electronic Questionnaire  As a web application  Different kinds of questions:  Textual  Numerical  Date  Linguistic  Multiple choice
  • 10. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Textual question
  • 11. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Numerical question
  • 12. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Date question
  • 13. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Linguistic question
  • 14. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Multiple choice question
  • 15. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 The Fuzzy Decision Support System (FDSS)
  • 16. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Fuzzifier
  • 17. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Fuzzy rule base IF vegetative cycle duration IS High AND cultural cycle duration IS Low THEN phenological risk IS Low
  • 18. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Inference engine IF vegetative cycle duration IS High AND cultural cycle duration IS Low THEN phenological risk IS Low IF vegetative cycle duration IS High AND cultural cycle duration IS High THEN phenological risk IS High …
  • 19. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Defuzzifier IF vegetative cycle duration IS High AND cultural cycle duration IS Low THEN phenological risk IS Low IF vegetative cycle duration IS High AND cultural cycle duration IS High THEN phenological risk IS High …
  • 20. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Report
  • 21. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013  Open source library  http://jfuzzylogic.sourceforge.net/html/index.html  Fuzzy Control Language (FCL) specification  Aggregation, Activation and Accumulation methods  Supports continue, discrete or custom membership functions  Flexible and extensible FDSS jFuzzyLogic
  • 22. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 System validation  The Fuzzy Decision Support System has been tested  by producing about 150 ERAs  by submitting the produced inferences to a pool of ISPRA experts  not involved in the rule definition  to assess the consistency and completeness of the system
  • 23. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Scenario 1
  • 24. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Scenario 2
  • 25. May 23rd 2013 WIRN 2013 – Vietri sul Mare, Salerno, ItalyMay 23rd 2013 Conclusions and Future Works  Fuzzy Decision Support System  identify potential impacts that can achieve one or more receptors through a set of migration paths  validated on Bt-maize1 and Brassica napus2 by the human experts of ISPRA  Future works  Machine learning algorithms to learn the FDSS knowledge base1 GM maize 2 GM colza

Editor's Notes

  1. Good morning. I’m Alfredo Starace and I’m going to present a joint research project performed by University of Naples Parthenope and ISPRA that is InstitutoSuperiore per la Protezione e la ricerca ambientale which is the part of Ministero dell’ambiente devoted to the control of Genetically modified organism.The research project was develop within the European community life program.
  2. We will firstly take a short introduction to the problem highlighting the motivationsof the research.Later, we will describe the Environmental Risk Assessment processand our Fuzzy Decision Support System to facilitate this task.After we’ll show the results obtained with the supervision of field experts.And Finally, we’ll drowsome conclusions