An optical smartphone-based inspection platform for identification of diseased orchids

Kuan Chieh Lee, Yen Hsiang Wang, Wen Chun Wei, Ming Hsien Chiang, Ting En Dai, Chung Cheng Pan, Ting Yuan Chen, Shi Kai Luo, Po Kuan Li, Ju Kai Chen, Shien Kuei Liaw, Choa Feng Lin, Chin Cheng Wu, Jen Jie Chieh*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

Infections of orchids by the Odontoglossum ringspot virus or Cymbidium mosaic virus cause orchid disfiguration and are a substantial source of economic loss for orchid farms. Although immunoassays can identify these infections, immunoassays are expensive, time consuming, and labor consuming and limited to sampling-based testing methods. This study proposes a noncontact inspection platform that uses a spectrometer and Android smartphone. When orchid leaves are illuminated with a handheld optical probe, the Android app based on the Internet of Things and artificial intelligence can display the measured florescence spectrum and determine the infection status within 3 s by using an algorithm hosted on a remote server. The algorithm was trained on optical data and the results of polymerase chain reaction assays. The testing accuracy of the algorithm was 89%. The area under the receiver operating characteristic curve was 91%; thus, the platform with the algorithm was accurate and convenient for infection screening in orchids.

原文英語
文章編號363
期刊Biosensors
11
發行號10
DOIs
出版狀態已發佈 - 2021 十月

ASJC Scopus subject areas

  • 臨床生物化學

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