Semi-automated identification of biological control agent using artificial intelligence | |
Liao, Jhih-Rong1; Lee, Hsiao-Chin1; Chiu, Ming-Chih2; Ko, Chiun-Cheng1 | |
Corresponding Author | Chiu, Ming-Chih(mingchih.chiu@gmail.com) ; Ko, Chiun-Cheng(kocc2501@ntu.edu.tw) |
2020-09-03 | |
Source Publication | SCIENTIFIC REPORTS
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ISSN | 2045-2322 |
Volume | 10Issue:1Pages:9 |
Abstract | The accurate identification of biological control agents is necessary for monitoring and preventing contamination in integrated pest management (IPM); however, this is difficult for non-taxonomists to achieve in the field. Many machine learning techniques have been developed for multiple applications (e.g., identification of biological organisms). Some phytoseiids are biological control agents for small pests, such as Neoseiulus barkeri Hughes. To identify a precise biological control agent, a boosting machine learning classification, namely eXtreme Gradient Boosting (XGBoost), was introduced in this study for the semi-automated identification of phytoseiid mites. XGBoost analyses were based on 22 quantitative morphological features among 512 specimens of N. barkeri and related phytoseiid species. These features were extracted manually from photomicrograph of mites and included dorsal and ventrianal shield lengths, setal lengths, and length and width of spermatheca. The results revealed 100% accuracy rating, and seta j4 achieved significant discrimination among specimens. The present study provides a path through which skills and experiences can be transferred between experts and non-experts. This can serve as a foundation for future studies on the automated identification of biological control agents for IPM. |
DOI | 10.1038/s41598-020-71798-x |
Funding Organization | Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan |
Indexed By | SCI ; SCI |
Language | 英语 |
Funding Project | Chinese Academy of Sciences (CAS Taiwan Young Talent Programme)[2017TW2SA0004] ; Ministry of Science and Technology, Taiwan[MOST105-2621-B-002-002-MY3] ; Ministry of Science and Technology, Taiwan[MOST108-2621-B-002-005-MY3] |
WOS Research Area | Science & Technology - Other Topics |
WOS Subject | Multidisciplinary Sciences |
WOS ID | WOS:000571229700124 |
WOS Keyword | AMBLYSEIUS-BARKERI ACARINA ; INTRASPECIFIC VARIATIONS ; SETAL PATTERNS ; DORSAL SHIELD ; MITES ACARI ; PHYTOSEIIDAE ; HUGHES ; THYSANOPTERA ; IMAGE |
Publisher | NATURE RESEARCH |
Funding Organization | Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Chinese Academy of Sciences (CAS Taiwan Young Talent Programme) ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan ; Ministry of Science and Technology, Taiwan |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.ihb.ac.cn/handle/342005/38854 |
Collection | 其他_期刊论文 |
Corresponding Author | Chiu, Ming-Chih; Ko, Chiun-Cheng |
Affiliation | 1.Natl Taiwan Univ, Dept Entomol, Taipei 10617, Taiwan 2.Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China |
Recommended Citation GB/T 7714 | Liao, Jhih-Rong,Lee, Hsiao-Chin,Chiu, Ming-Chih,et al. Semi-automated identification of biological control agent using artificial intelligence[J]. SCIENTIFIC REPORTS,2020,10(1):9. |
APA | Liao, Jhih-Rong,Lee, Hsiao-Chin,Chiu, Ming-Chih,&Ko, Chiun-Cheng.(2020).Semi-automated identification of biological control agent using artificial intelligence.SCIENTIFIC REPORTS,10(1),9. |
MLA | Liao, Jhih-Rong,et al."Semi-automated identification of biological control agent using artificial intelligence".SCIENTIFIC REPORTS 10.1(2020):9. |
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