Mohammad Reza Samiei - Department of Information Technology and Computer Engineering,Payame Noor University, Tehran, Iran.
Raheleh Fahimi - Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Fereshteh Agheli - Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Samaneh Noferesti - Department of Computer Engineering, Ferdows higher education institute, Mashhad, Iran

World population growth and increasing demand for food in recent decades led to the use of modern methods of biotechnology in crop production and livestock .The application of genetic engineering and biotechnology to increase the quality and quantity of products on the one hand and on the other hand it is essential to reduce costs and production time. Genetic engineering techniques used in modern biotechnology and a new branch of biotechnology. Producing microorganisms, animals and transgenic plants through genetic engineering is one of the ways that you can get through it targets such as producing more food, production and service life, high maintenance,production of pharmaceutical products and found. Environmental risk assessment (ERA) caused by the deliberate release of genetically modified plants (GMPS) already by human experts, based on their personal experiences and knowledge is carried out. In this article we explain an fuzzy decision system (FDS) for GMPS and ERA consider that the inference is fuzzy. This risk assessment in FDS using an fuzzy inference system (FIS) has been made and will be implemented by an fuzzy logic library. The FDS provides a process through which we can assess the potential effects that may be applied in different ways to identify our transfer to one or more recipients. Human experts are responsible ERA. Credit decisions made by FDS in the outside world. They assess the reliability and accuracy of decisions made by the system confirms the fuzzy.

fuzzy decision-making system, risk assessment of genetically modified plants, Mamdany, fuzzy control language