基于决策树算法的蔬菜农药残留的数据挖掘与分析  

Data mining and analysis of pesticide residue in vegetables based on Decision Tree algorithm

作　　者：方永美[1] 孙凌洁[1] 廖鉴康 杨振刚[1] 

机构地区：[1]华南农业大学信息学院,广东广州510642

出　　处：《广东农业科学》2014年第3期194-197,共4页Guangdong Agricultural Sciences

基　　金：2012教育部人文社会科学研究青年基金(12YJCZH252)

摘　　要：蔬菜是人们日常消费的必需品,影响蔬菜质量安全的一个重要因素就是农药残留问题.利用决策树算法的数据挖掘技术,对蔬菜的检测信息进行挖掘,得到品种为韭菜、黄瓜的农药残留高;新桥市场、烟大市场和大世界市场的蔬菜农药残留水平较低;而7～9月的蔬菜农药残留高.结果具有一定的可信度,为蔬菜消费者和安全监管者提供一定的决策依据.Vegetables are daily necessities of people. Pesticide residue is one of important factors affecting quality and safety of vegetables. Decision Tree algorithm is used to excavate the detection information of vegetables. The results show that there is high pesticide residue in leeks and cucumbers, there is lower level of pesticide residue of vegetables in Xinqiao, Yanda and Dashijie markets, there is high level pesticide residue from July to September. The result is certain credible, can provide some security decisions for consumers and regulators.

关 键 词：决策树 数据挖掘 农药残留 蔬菜 

分 类 号：X56[环境科学与工程—环境工程]