Automatic recognition of quarantine citrus diseases

被引:48
作者
Stegmayer, Georgina [1 ,2 ]
Milone, Diego H. [1 ]
Garran, Sergio
Burdyn, Lourdes
机构
[1] Consejo Nacl Invest Cient & Tecn, FICH UNL, Res Ctr Signals Syst & Computat Intelligence, RA-3000 Santa Fe, Argentina
[2] Consejo Nacl Invest Cient & Tecn, Ctr Invest Ingn Sistemas Informac, RA-3000 Santa Fe, Argentina
关键词
Pattern recognition; Multiclass classification; Neural networks; Citrus diseases; GUIGNARDIA-CITRICARPA; INSPECTION; ENDOPHYTE;
D O I
10.1016/j.eswa.2012.12.059
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them, like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is important to perform strict controls before fruits are exported to avoid the inclusion of citrus affected by them. Nowadays, technical decisions are based on visual diagnosis of human experts, highly dependent on the degree of individual skills. This work presents a model capable of automatic recognize the quarantine diseases. It is based on the combination of a feature selection method and a classifier that has been trained on quarantine illness symptoms. Citrus samples with citrus canker, black spot, scab and other diseases were evaluated. Experimental work was performed on 212 samples of mandarins from a Nova cultivar. The proposed approach achieved a classification rate of quarantine/not-quarantine samples of over 83% for all classes, even when using a small subset (14) of all the available features (90). The results obtained show that the proposed method can be suitable for helping the task of citrus visual diagnosis, in particular, quarantine diseases recognition in fruits. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3512 / 3517
页数:6
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