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A Remote, Non-consumable, Handheld and Rapid Screening Machine on Orchid Viruses
Orchid virus detection
Because a large gap showed in the location latitude and topography, the diversity of agricultural development, including edible agricultural products and ornamental flowers and plants, in Taiwan have developed proud agricultural achievements. However, diverse environments also resulted in many diseases. For example, the virus troubles of phalaenopsis cause huge losses to the growers. Because the virus has an incubation period, the discrimination of the infection for orchid plants is regularly by the visual experience of the planter, or the time-consuming and laborious biological tests, such as enzyme link immunosorbent assay (ELISA), polymerase chain reaction (PCR), immuno-strip detection kit, magnetic Immunomagnetic reduction (IMR), etc. Based on these technologies, the screening cannot be popularized as the full inspection, and only be as sampling inspection with the missing risks. This technology based on a hand-held optical detection method to illuminate the leaves with LED light, and then receives the fluorescent light with the probe. After receiving the signal, the light wave data is sorted by the spectrometer and the control board, and it is returned to the database with the mobile phone. After all the data profile is smoothed, standardized and pre-processed by PCA for dimensionality reduction, two algorithms, i.e. support Vector Machine (SVM) and extreme gradient boosting (eXtreme Gradient Boosting, XGBoost), were used for classification and analysis. The accuracy and effect of the judgment. Among them, SVC has an accuracy rate of 87% in judging diseased orchids, and XGBoost has an accuracy rate of 91% in judging diseased orchids (whatever visible symptoms or not). In comparison with the time-consuming and labor-intensive mentioned methods, this remote, non-consumable, handheld, rapid screening machine allowed the flower grower to detect the infection results early than the visible symptoms to prevent the cluster infection.
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