The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
In vitro antioxidant activity of Kyoho grape extracts in DPPH and ABTS assays: Estimation methods for EC50 using advanced statistical programs
Abstract
The antioxidant capacities of Kyoho skin, seed, and flesh extracts were determined using DPPH and ABTS assays and a suitable statistical program was tested for the prediction of EC50 values of Kyoho skin, seed, and flesh extracts obtained by DPPH and ABTS assays. Statistical programs: OriginPro® version 8, GraphPad Prism® version 7, GraphPad Prism® version 7 five-parameter (5P) logistic model, SigmaPlot® version 14.0, Microsoft Excel® version 2016, interpolation log, and direct interpolation methods were employed to estimate the EC50 values. Linear regression and direct interpolation results showed deviations for non-linear models in the prediction of EC50 values of grape extracts. The correlation results of grape flesh extracts demonstrated a positive correlation (r = ≥ 0.95) between EC50 values of antioxidant assays. Therefore, non-linear methods were appropriate for EC50 calculations. These findings have significant implications for selecting an efficient statistical tool to calculate EC50 values for DPPH and ABTS assays.
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Baliyan, S., Mukherjee, R., Priyadarshini, A., Vibhuti, A., Gupta, A., Pandey, R. P., & Chang, C.-M. (2022) · Molecules · doi:10.3390/molecules27041326 · Cited by 1,485
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Metadata
- Authors
- Sridhar, K., & Charles, A. L.
- Venue
- Food Chemistry
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 275
- Pages
- 41-49
- ISSN
- 0308-8146 (ISSN-L)
- OpenAlex
- W2889940709
- Cited by
- 409
- References
- 23
- FWCI
- 16.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
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- Sridhar, K., & Charles, A. L. (2019). In vitro antioxidant activity of Kyoho grape extracts in DPPH and ABTS assays: Estimation methods for EC50 using advanced statistical programs. Food Chemistry. https://doi.org/10.1016/j.foodchem.2018.09.040
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