An intelligent identification system combining image and DNA sequence methods for fruit flies with economic importance (Diptera: Tephritidae)
文献类型：期刊论文
| 作者 | Wang, Jiangning3; Chen, Yingying2 ; Hou, Xinwen2; Wang, Yong3; Zhou, Libing1; Chen, Xiaolin3
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| 刊名 | PEST MANAGEMENT SCIENCE
 |
| 出版日期 | 2021-04-19 |
| 页码 | 14 |
| 关键词 | fruit fly pests intelligent identification system image deep learning DNA sequence |
| ISSN号 | 1526-498X |
| DOI | 10.1002/ps.6383 |
| 通讯作者 | Chen, Xiaolin(xlchen@ioz.ac.cn) |
| 英文摘要 | BACKGROUND Images and DNA sequences are two important methods for identifying fruit fly species. In addition, the identification of insect species complexes is highly problematic when attempting to utilize automatic identification methods in an actual environment. We integrated the image and DNA sequence identification methods into a single system for the first time and explored an open interactive multi-image comparison function for solving the problem of species complexes. The Automated Fruit Fly Identification System 1.0 (AFIS1.0) was updated to AFIS2.0 by employing different models and developing the system under a novel framework. RESULTS AFIS2.0 was developed using 83 species belonging to eight genera in the Tephritidae, which includes most pests of this family. The system applies the Mask Region Convolutional Neural Network (Mask R-CNN) and discriminative deep metric learning (AlexNet based) methods for image identification, integrates Blast+ for DNA sequence comparison and specific weighting for the fusion result. At the species level, the best classification success rate for wing images (as the Top 1 species in the species list of outcomes) reached 90%, and the average classification success rate for wing, thorax, and abdomen images (as the Top 5 species in the species list of outcomes) was 94%. CONCLUSION AFIS2.0 is more accurate and convenient than AFIS1.0 and can be beneficial for users with or without specific expertise regarding Tephritidae. It also provides a more compact and fluent computer system for fruit fly identification, and can be easily applied in practice. |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19050203] ; National Natural Science Foundation of China[31672325] ; National Natural Science Foundation of China[31501841] ; National Key R&D Program of China[2017YFC1200601] |
| WOS研究方向 | Agriculture ; Entomology |
| 语种 | 英语 |
| WOS记录号 | WOS:000641055400001 |
| 出版者 | JOHN WILEY & SONS LTD |
| 资助机构 | Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Key R&D Program of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44239]  |
| 专题 | 综合信息系统研究中心_脑机融合与认知评估 |
| 通讯作者 | Chen, Xiaolin |
| 作者单位 | 1.Yunnan Entry Exit Inspect & Quarantine Bur, Kunming, Yunnan, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Zool, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Jiangning,Chen, Yingying,Hou, Xinwen,et al. An intelligent identification system combining image and DNA sequence methods for fruit flies with economic importance (Diptera: Tephritidae)[J]. PEST MANAGEMENT SCIENCE,2021:14. |
| APA | Wang, Jiangning,Chen, Yingying,Hou, Xinwen,Wang, Yong,Zhou, Libing,&Chen, Xiaolin.(2021).An intelligent identification system combining image and DNA sequence methods for fruit flies with economic importance (Diptera: Tephritidae).PEST MANAGEMENT SCIENCE,14. |
| MLA | Wang, Jiangning,et al."An intelligent identification system combining image and DNA sequence methods for fruit flies with economic importance (Diptera: Tephritidae)".PEST MANAGEMENT SCIENCE (2021):14. |
入库方式： OAI收割
来源：自动化研究所
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