摘要
针对粮堆中储粮害虫玉米象检测技术落后,检测结果不可靠等问题,利用电子鼻对玉米象不同虫态及虫态组合进行检测,并采用主成分分析法(PCA)和判别因子分析法(DFA)对检测数据进行分析,结果表明:电子鼻可以对不同密度的玉米象成虫进行有效的识别,但当虫口密度高于20头/瓶时,无法进行区分;使用电子鼻检测玉米象不同虫态时,PCA分析法的重复间数据较分散,区分度不高,而DFA分析法可将各虫态有效区分;电子鼻检测玉米象混合虫态时,DFA分析法可将不同组合有效区分,而PCA分析法无法区分,因此将电子鼻检测结合DFA分析法用于玉米象不同虫态及虫态组合的检测是可行的.
In this study,explore a new method to identify different densities and insect state of maize weevil by electronic nose technology with the principal component analysis(PCA)and the discriminant factor analysis(DFA)for data analysis was explored.The results showed that electronic nose had a good recognition on adults of maize weevil in different densities.However,it was unable to distinguish the adults as the population density was higher than 20 head/the bottle.While different insect state of maize weevil were detected by electronic nose,duplication of data in PCA analysis was scattered with low degree of differentiation,and the DFA analysis could be used to distinguish different insect state.Meanwhile,in detection of hybrid maize weevil,DFA analysis can effectively distinguish different combination of the weevil state,and PCA analysis could not distinguish them.Therefore,the electronic nose with DFA analysis for identification of different density and insect state of maize weevil was feasible.
作者
唐培安
侯晓燕
孔德英
吴学友
宋伟
Tang Peian;Hou Xiaoyan;Kong Deying;Wu Xueyou;Song Wei(College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation and Safety/Key Laboratory of Grains and Oils Quality Control and Processing,Nanjing University of Finance and Economics,Nanjing 210023;Chongqing Entry Exit Inspection and Quarantine Bureau,Chongqing 400020)
出处
《中国粮油学报》
EI
CAS
CSCD
北大核心
2019年第S01期131-136,共6页
Journal of the Chinese Cereals and Oils Association
基金
863计划(2012AA101608)
国家科技支撑计划(2013BAD17B01)
粮食公益性行业科研专项(201413007-2)
江苏高校优势学科建设工程(JSYXK201403).
关键词
电子鼻
玉米象
密度
虫态
electronic nose
maize weevil
density
insect state
