An Optical Smartphone-Based Inspection Platform for Identification of Diseased Orchids
Journal
Biosensors-Basel
Journal Volume
11
Journal Issue
10
Pages
363
Date Issued
2021-10
Author(s)
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
Abstract
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.
Subjects
optical inspection
diseased orchids
artificial intelligence (ai)
internet of things (iot)
Publisher
MDPI
Type
journal article