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Multicolor Fluorescence Imaging for the Early Detection of Salt Stress in Arabidopsis

Ya Tian, Limin Xie, Mingyang Wu, Biyun Yang, Captoline Ishimwe, Dapeng Ye, Haiyong Weng
Agronomy 2021 v.11 no.12 pp. -
Arabidopsis, agronomy, cameras, computers, fluorescence, light emitting diodes, metabolism, models, phenotype, principal component analysis, salt stress, support vector machines
Salt stress is one of the abiotic factors that causes adverse effects in plants and there is an urgent need to detect salt stress in plants as early as possible. Multicolor fluorescence imaging, as a powerful tool in plant phenotyping, can provide information about primary and secondary metabolism in plants to detect the responses of the plants exposed to stress in the early stage. The purpose of this study was to evaluate the potential of multicolor fluorescence imaging’s application in the early detection of salt stress in plants. In this study, the measurements were conducted on Arabidopsis and the multicolor fluorescence images were acquired at 440, 520, 690, and 740 nm with a self-developed imaging system consisting of a UV light-emitting diode (LED) panel for an excitation at 365 nm, a charge coupled device (CCD) camera, interference filters, and a computer. We developed a classification method using the imaging analysis of multicolor fluorescence based on principal component analysis (PCA) and a support vector machine (SVM). The results showed that the four principal fluorescence feature combinations were the ideal indicators as the inputs of the SVM model, and the classification accuracies of the control and salt-stress treatment at 5 days and 9 days were 92.65% and 98.53%, respectively. The results indicated that multicolor fluorescence imaging combined with PCA and SVM could act as a tool for early detection in salt-stressed plants.