An Optical Smartphone-Based Inspection Platform for Identification of Diseased Orchids

作者：Kuan-Chieh Lee, Yen-Hsiang Wang, Wen-Chun Wei, Ming‐Hsien Chiang, Ting-En Dai, Chung-Cheng Pan, Ting-Yuan Chen, Luo Shi-kai, Po-Kuan Li, Ju-Kai Chen, Shien-Kuei Liaw, Choa-Feng Lin, Chin-Cheng Wu, Jen-Jie Chieh · 发表于：Biosensors · 年份：2021 · DOI：10.3390/bios11100363 · 被引用次数：5 · 研究领域：Plant Virus Research Studies、Biosensors and Analytical Detection、Smart Agriculture and AI

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.