Modular plant phenotypic analysis technical program - rapid detection and identification of early vegetable diseases

Image analysis techniques such as chlorophyll fluorescence, UV-MCF multispectral fluorescence, infrared thermography, and reflectance spectra represented by the NDVI normalized vegetation index are the most advanced and important non-destructive plant phenotypic detection techniques, especially for plants. Research on the detection, prediction and response mechanism of various biotic and abiotic stresses.
The Sandmann research team at IGZ, Institute of Vegetables and Ornamental Plants, Leibniz, Germany, has conducted research for many years. They used these techniques to test a variety of parameters in an attempt to distinguish between physiologic and unstressed plants in the early stages of vegetable infection. Finally, they used a model plant-pathogen system: the lettuce- Rizoctonia solani system, and hopefully the data obtained through these technologies would achieve this goal.
NDVI imaging and thermal imaging
Because the principles of these technologies are not the same, similar studies often require the use of multiple instruments. The FluorCam multispectral fluorescence imaging system as the most advanced model FluorCam chlorophyll fluorescence imaging system, is the only capable of achieving a complete chlorophyll fluorescence at the same time on a single instrument, UV-MCF multispectral fluorescence, NDVI normalized difference vegetation index and GFP, The imaging analysis function of fluorescent proteins and fluorescent dyes such as YFP, BFP, RFP, CFP, DAPI, and thermal imaging analysis can be performed after the thermal imaging module is installed.
The parameters and analytical data results measured by FluorCam in this paper
Through data analysis, the chlorophyll fluorescence parameters were finally found: the maximum quantum yield Fv/Fm of PSII and the fluorescence decay ratio Rfd were the best, with an error of ≤0.052. Researchers hope to apply this finding to horticultural and agricultural production practices through further work.
In this study, the researchers only measured NDVI in the reflectance spectral vegetation index, but in fact, there are many vegetation indices that can be used for vegetable diseases, such as NDVI, PRI, NDSI, NDGI, SR, MCARI, TCARI, TVI, ZMI. , SRPI and so on dozens of indexes. Different types of diseases may be applied to one or several vegetation indices for identification and identification. Therefore, in this area of ​​research, it is best to have a spectrometer or hyperspectral imager to get as much index information as possible.
Changes in leaf reflectance spectra and corresponding vegetation indices in red leaf spot of almond trees (M López-López, et al. 2016)

Modular plant phenotypic analysis technical solution recommended:

1. Basic plan: FluorCam open multi-spectral fluorescence imaging system + NDVI imaging module + WIC infrared thermal imager
2. Advanced Solution: FluorCam Multispectral Fluorescence Imaging System + WIC Infrared Thermal Imager + Specim IQ Handheld Hyperspectral Imager
3. Advanced Solution: FluorCam Multispectral Fluorescence Imaging System + WIC Infrared Thermal Imager + FX10/FX17 Portable Hyperspectral Imager or SisuCHEMA Hyperspectral Scanning Imaging Analysis System
references:
  • Sandmann M, et al. 2018. The use of features from fluorescence, thermography and NDVI imaging to detect biotic stress in lettuce. Plant Disease, 102(6):1101-1107

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