1. |
- Kang, Jinho, et al.
(author)
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Application of a 1H nuclear magnetic resonance (NMR) metabolomics approach combined with orthogonal projections to latent structure-discriminant analysis as an efficient tool for discriminating between Korean and Chinese herbal medicines
- 2008
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In: Journal of Agricultural and Food Chemistry. - Washington : American Chemical Society (ACS). - 0021-8561 .- 1520-5118. ; 56:24, s. 11589-11595
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Journal article (peer-reviewed)abstract
- Correct identification of the origins of herbal medical products is becoming increasingly important in tandem with the growing interest in alternative medicine. However, visual inspection of raw material is still the most widely used method, and newer scientific approaches are needed. To develop a more objective and efficient tool for discriminating herbal origins, particularly Korean and Chinese, we employed a nuclear magnetic resonance (NMR)-based metabolomics approach combined with an orthogonal projections to latent structure-discriminant analysis (OPLS-DA) multivariate analysis. We first analyzed the constituent metabolites of Scutellaria baicalensis through NMR studies. Subsequent holistic data analysis with OPLS-DA yielded a statistical model that could cleanly discriminate between the sample groups even in the presence of large structured noise. An analysis of the statistical total correlation spectroscopy (STOCSY) spectrum identified citric acid and arginine as the key discriminating metabolites for Korean and Chinese samples. As a validation of the discrimination model, we performed blind prediction tests of sample origins using an external test set. Our model correctly predicted the origins of all of the 11 test samples, demonstrating its robustness. We tested the wider applicability of the developed method with three additional herbal medicines from Korea and China and obtained very high prediction accuracy. The solid discriminatory power and statistical validity of our method suggest its general applicability for determining the origins of herbal medicines.
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2. |
- Chang, Kuang Yu, et al.
(author)
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Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
- 2021
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 2266-2266
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Journal article (peer-reviewed)abstract
- Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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3. |
- Ichii, Kazuhito, et al.
(author)
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New data-driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression
- 2017
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In: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 122:4, s. 767-795
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Journal article (peer-reviewed)abstract
- The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial CO2 fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated CO2 fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8days are reproduced (e.g., r2=0.73 and 0.42 for 8day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r2=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land CO2 fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land CO2 fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land CO2 fluxes. These data-driven estimates can provide a new opportunity to assess CO2 fluxes in Asia and evaluate and constrain terrestrial ecosystem models.
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4. |
- Knox, Sara H., et al.
(author)
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FLUXNET-CH4 Synthesis Activity : Objectives, Observations, and Future Directions
- 2019
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 100:12, s. 2607-2632
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Journal article (peer-reviewed)abstract
- This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from -0.2 +/- 0.02 g C m(-2) yr(-1) for an upland forest site to 114.9 +/- 13.4 g C m(-2) yr(-1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(-2) yr(-1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average +/- 1.6 g C m(-2) yr(-1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
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