Corresponding Author Bayesian Network and Pest Management: A case study of trap plants on locust population

Abstract

ABSTRACT Bayesian network approach has been effectively used in different experimental fields such as ecological decision making. There is also now growing instance of its usage and effectiveness in pest management. The fundamental principle to optimizing outcomes of agricultural products for pest management is the consideration of all chemical methods, physical methods, mechanical methods, transgenic plants, and trap plants. Some of methods have harmful environmental effects while some others are both environmental friendly and effective. Among them the use of trap plants can be one of the major approaches for pest control. The Locust is one of the most destructive pests and has unpredictable damages on agricultural products especially in poor countries where the volume of product has critical and crucial influence of human life. This research provides a case study on using Bayesian networks on the effect of a number of trap plants have on locust population, and considerations to predict and prevent the pests' harmful effects. According to the findings, the probability methods such as Bayesian networks can contribute effectively on pest management studies particularly trap plants to enhance decision making procedure in national and international perspective