HighlightA new vegetation index insensitive to adaxial and abaxial leaf surfaces was proposed in this paper to accurately estimate leaf chlorophyll content.
BackgroundLeaf chlorophyll content (LCC) provides valuable information about plant physiology. Most of the published chlorophyll vegetation indices at the leaf level have been based on the spectral characteristics of the adaxial leaf surface, thus, they are not appropriate for estimating LCC when both the adaxial and abaxial leaf surfaces influence the spectral reflectance. We attempted to address this challenge by measuring the spectral reflectance of the adaxial and abaxial leaf surfaces of several plant species at different growth stages using a portable field spectroradiometer. The relationships between more than 30 published reflectance indices with LCC were analyzed to determine which index estimated LCC most effectively. Additionally, since the relationships determined on one set of samples might have poor predictive performances when applied to other samples, a robust wavelength region is required to render the spectral index generally applicable, regardless of the leaf surface or plant species.ResultsThe Modified Datt (MDATT) index, which is the ratio of reflectance difference defined as (Rλ3 − Rλ1)/(Rλ3 − Rλ2), exhibited the strongest correlation (R2 = 0.856, RMSE = 6.872 μg/cm2), with LCC of all the indices tested when all the leaf samples from the adaxial and abaxial surfaces were combined. The optimal wavelength regions, which were derived from the contour maps of R2 between the MDATT index and LCC for the datasets of one side or both leaf surfaces of each plant species and their intersection, indicated that the red-edge to near-infrared wavelength (723–885 nm) was optimal for λ1, while the red-edge region (697–771 nm) was optimal for λ2 and λ3. In these optimal wavelength regions, when the MDATT index was used to estimate LCC, an R2 higher than 0.8 could be obtained. The correlation of the MDATT index with LCC was the same when the positions of λ2 and λ3 were exchanged in the index.ConclusionsMDATT is proposed as an optimal index for the remote estimation of vegetation chlorophyll content across several plant species in different growth stages when reflectance from both leaf surfaces is considered. The red-edge to near-infrared wavelength (723–885 nm) for λ1, as well as the red-edge region (697–771 nm) for λ2 or λ3, are considered to be the most robust for constructing the MDATT index for estimating LCC, regardless of the leaf surface or plant species.Electronic supplementary materialThe online version of this article (10.1186/s13007-018-0281-z) contains supplementary material, which is available to authorized users.
BackgroundThe rapid development of coronavirus disease 2019 (COVID-19) pandemic has become a great threat to global health. Its mortality is associated with inflammation-related airway mucus hypersecretion and dysfunction of expectoration, and the subsequent mucus blockage of the bronchioles at critical stage is attributed to hypoxemia, complications, and even death. Traditional Chinese medicine (TCM) has rich experience in expectorant, including treatment of COVID-19 patients with airway mucus dysfunction, yet little is known about the mechanisms. This study is aiming to explore the potential biological basis of TCM herbal expectorant for treating COVID-19.ObjectiveTo get core herbs with high used frequency applications in the actions of expectoration by using association rule algorithm and to investigate the multitarget mechanisms of core herbs in expectorant formulae for COVID-19 therapies.MethodsForty prescriptions for expectorant were retrieved from TCM Formulae. The ingredient compounds and targets of core herbs were collected from the TCMSP database, Gene-Cards, and NCBI. The protein interaction network (PPI) was constructed by SRING, and the network analysis was done by Cytoscape software. Bioconductor was applied for functional enrichment analysis of targets.ResultsThe core herbs of expectorant could regulate core pathways (MAP kinase activity, cytokine receptor binding, G-protein-coupled receptor binding, etc.) via interactions of ingredients (glycyrol, citromitin, etc.) on mucin family to eliminate phlegm.ConclusionTCM herbal expectorant could regulate MAPK and cytokine-related pathways, thereby modulating Mucin-family to affect mucus generation and clearance and eventually retarding the deterioration of COVID-19 disease.
Highlight:
It was proven that renal injury in Corona Virus Disease 2019 (COVID-19) patients has been a real concern.
There are three possible mechanisms of renal injury in COVID-19 infection: direct viral mediated, prolonged cytokine storm mediated, and drug-induced renal injury.
There is no targeted drug therapy in the treatment of renal injury, while Chinese Herbal Medicine can be a potential solution.
Huang Qi, Fu Ling, Di Huang, Shan Yao and Bai Zhu are the core herbs in Chinese Herbal Medicine to treat renal injury.
Chinese Herbal Medicine may act on PTGS2, PTGS1, IL6 and CASP3, etc., to prevent the pharmacological and non-pharmacological COVID-19 related renal injury.
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