The invention relates to the technical field of
plant living body nondestructive testing, and discloses a
plant living body flavonol imaging detection method based on a multi-excitation light
chlorophyll fluorescence imaging technology, which comprises the following steps: on the basis of the multi-excitation light
chlorophyll fluorescence imaging technology, using a multi-excitation light
chlorophyll fluorescence hyperspectral imaging function of a FluorTron multifunctional
hyperspectral imaging system to carry out multi-excitation light
chlorophyll fluorescence hyperspectral imaging on the basis of the multi-excitation light
chlorophyll fluorescence imaging technology; collecting
chlorophyll fluorescence spectrum images of the
ginkgo leaves in a non-invasive and high-
throughput manner; then, carrying out de-noising
processing and fluorescence
spectrum analysis on the
spectral image by using FluorVision hyperspectral fluorescence
imaging analysis software; and finally, analyzing Flav indexes of the flavonol model by using FluorVision hyperspectral fluorescence
imaging analysis software, and making a graph. Compared with a traditional flavonol detection method, the method has the advantages of high
throughput, non-contact, non-damage,
digitization,
visualization, in-vivo imaging detection and the like, in addition, a multi-excitation chlorophyll fluorescence
spectrum imaging technology is adopted, the
chlorophyll content, the
anthocyanin content, the
plant N element state and the like can be detected and analyzed at the same time, and the method is suitable for large-scale popularization and application. Therefore, the method has important application value and prospect in the fields of plant flavonol and
anthocyanin high-
throughput in-vivo detection, medicinal plant
phenotype analysis,
secondary metabolite imaging analysis, non-destructive
rapid detection of traditional Chinese medicinal materials, in-vivo detection of functional components of
fruits and vegetables,
postharvest biology,
remote sensing and the like.