EGU22-7726
https://doi.org/10.5194/egusphere-egu22-7726
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Investigating the links between primary metabolites of medicinal species with leaf hyperspectral reflectance

Ayushi Gupta1, Prashant K Srivastava1, and Karuna Shanker2
Ayushi Gupta et al.
  • 1Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India
  • 2CSIR - Central Institute of Medicinal and Aromatic Plants, Lucknow, India

Recent studies have shown that the turnover in tree species composition across edaphic and elevational gradients is strongly correlated with functional traits. However, our understanding of functional traits has been limited by the lack of detailed studies of foliar chemistry across habitats and the logistical & economic challenges associated with the analysis of plant functional traits at large geographical scales. Advances in remote sensing and spectroscopic approaches that measure spectrally detailed light reflectance and transmittance of plant foliage provides accurate predictions of several functional chemical traits. In this study, Pyracantha crenulata (D. Don) M. Roemer has been used, which is an evergreen thorny shrub species found in open slopes between 1,000 and 2,400 m above mean sea level. P. crenulata is used in the treatment of hepatic, cardiac, stomach, and skin disease. In this study the P. crenulata leaves samples spectra were recorded using an ASD spectroradiometer and following primary metabolites such as chlorophyll, anthocyanin, phenolic, and sterol were analyzed. The spectroradiometer data were preprocessed using filter and then reduced to a few sensitive bands by applying feature selection to the hyperspectral data. The band values were directly correlated with the measured values. The analysis indicates a significant correlation between P. crenulata primary metabolite in the Visible and Infrared region (VISIR). This result suggests that molecules that have important functional attributes could be identified by VISIR spectroscopy, which would save a lot of time and expense as compared to wet laboratory analysis.

How to cite: Gupta, A., Srivastava, P. K., and Shanker, K.: Investigating the links between primary metabolites of medicinal species with leaf hyperspectral reflectance, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7726, https://doi.org/10.5194/egusphere-egu22-7726, 2022.

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