Assessing Agri-Environmental Indicators and Pollution Impacts on Environmental Performance Index and Agri-Economic Indicators in EU and ME countries: A Bayesian Network Based Model

Abstract Agricultural sector has a key role in relation to poverty reduction and improving food security.One of important challenges in the agriculture sector is to feed population that is increasing in the world. Agriculture has significant and negative impacts on the environment and earth ecosystems.The agricultural sector growth has made pollution and pollution has restricted increasing production in agricultural. Climate change has led researchers to pay close attention to environmental performance. Bayesian networks are relatively well recognized to be an advantageous method for different types of environmental model. This study was designed a Bayesian network model to investigate the relation between agri-economic-environmental indicators and Environmental performance Index in the EU countries compared to Middle East countries, in 2018. we showed relations between variables of model based on expert interview and previous researches. The results indicated land productivity is directly affected by node Agriculture area certified organic.We predicted with developing Agriculture area certified organic and conservation agricultural area, and productivity can be increased in EU Countries. Also, our findings showed with decreasing N2O and CH4 emissions indicators, increased Enivironmental performance index in EU countries and decreasesd in Middle East countries.Terefore, EU countries is improved agricultural practices and pesticides and fertilizer, But ME countries have not been successful in improving the environmental performance index and sustainable development objectives. Modelling of agri-environmental indicators can help to policymakers about the changes of agro-ecosystem and can use for international reviews.