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; et al. (Biosensors, 2021)
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.