A High-Performance Liquid Chromatography with Electrochemical Detection Method Developed for the Sensitive Determination of Ascorbic Acid: Validation, Application, and Comparison with Titration, Spectrophotometric, and High-Performance Liquid Chromatography with Diode-Array Detection Methods
Abstract
:1. Introduction
2. Materials and Methods
2.1. Chemicals and Regents
2.2. Honey and Other Samples
2.3. Titrimetric Determination of VC
2.4. Spectrophotometric Determination of VC
2.5. HPLC-DAD and HPLC-ECD Methods
2.6. Method Validation
2.7. Statistical Analysis
3. Results and Discussion
3.1. Validation of the Analytical Method for VC
3.2. Comparison of HPLC-ECD and Other Three Methods
3.3. Application of the HPLC-ECD Method for VC Quantitation in Different Samples
3.3.1. Evolution of VC Contents in Honey during Storage
3.3.2. VC Contents in Different Varieties of Honey
3.3.3. VC Contents in Different Fruit and Biological Samples
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Methodologies | Linearity | LOD a (μg mL−1) | LOQ a (μg mL−1) | ||
---|---|---|---|---|---|
Regression Equation | R2 | Linear Range (mg mL−1) | |||
BP b | Y = 30.0670x + 2.1160 | 0.9979 | 5.0 × 10−3–4.0 × 10−1 | 2.4167 (A = 0.01) c | / |
HPLC-DAD | Y = 3.0722x + 0.1259 | 0.9990 | 5.0 × 10−3–2.0 × 10−2 | 0.9375 | 3.1250 |
HPLC-ECD | Y = 0.0014x + 0.0423 | 0.9999 | 1.0 × 10−4–2.0 × 10−2 | 0.0043 | 0.0142 |
Methodologies | Accuracy (%) | Recovery (%) | Repeatability (n = 6) | Precision | |||||
---|---|---|---|---|---|---|---|---|---|
Spiked Concentrations (μg mL−1) | Spiked Concentrations (μg mL−1) | RSD (%) | Intra-Day (n = 6) | Inter-Day (n = 3 Replicates × 3 Days) | |||||
1.00 | 2.00 | 4.00 | 10.00 | 2.00 | 4.00 | RSD (%) | RSD (%) | ||
BP | / | / | 94.45 | 96.73 | / | 97.55 | 5.17 | 6.53 | 8.19 |
HPLC-DAD | / | / | 98.17 | 98.15 | 94.90 | 95.63 | 0.88 | 3.18 | 4.49 |
HPLC-ECD | 102.00 | 97.55 | 96.90 | 98.59 | 94.20 | 93.30 | 1.36 | 2.51 | 5.15 |
Code | Samples | 2,6-DCPIP | BP | HPLC-DAD | HPLC-ECD |
---|---|---|---|---|---|
H1 | Multifloral honey | 0.20 ± 0.03 | 0.18 ± 0.01 | 0.19 ± 0.00 | 0.18 ± 0.00 |
H2 | Multifloral honey | 0.20 ± 0.05 | 0.19 ± 0.03 | 0.19 ± 0.00 | 0.19 ± 0.00 |
H3 | Multifloral honey | 0.23 ± 0.05 | 0.22 ± 0.01 | 0.22 ± 0.00 | 0.21 ± 0.00 |
H4 | Medlar honey | 0.12 ± 0.05 | 0.11 ± 0.01 | 0.12 ± 0.00 | 0.12 ± 0.00 |
H5 | Medlar honey | 0.14 ± 0.01 | 0.13 ± 0.01 | 0.13 ± 0.00 | 0.14 ± 0.00 |
H6 | Medlar honey | 0.15 ± 0.05 | 0.15 ± 0.01 | 0.15 ± 0.00 | 0.15 ± 0.00 |
H7 | Acacia honey | ND | ND | ND | 0.01 ± 0.00 |
H8 | Acacia honey | ND | ND | ND | 0.04 ± 0.00 |
H9 | Acacia honey | ND | ND | ND | 0.05 ± 0.00 |
Samples | Geographical Origin | Harvest Date | Mean ± SD | Minimum Value | Maximum Value |
---|---|---|---|---|---|
Honey (mg g−1) | |||||
Multifloral honey (n = 10) | Shaanxi | August 2017 | 0.18 ± 0.03 | 0.13 | 0.23 |
Multifloral honey (n = 10) | Shaanxi | August 2019 | 0.21 ± 0.03 | 0.18 | 0.25 |
Multifloral honey (n = 9) | Shaanxi | September 2020 | 0.23 ± 0.04 | 0.19 | 0.31 |
Medlar honey (n = 10) | Qinghai | November 2017 | 0.13 ± 0.01 | 0.11 | 0.14 |
Medlar honey (n = 4) | Ningxia | November 2017 | 0.13 ± 0.01 | 0.13 | 0.14 |
Medlar honey (n = 7) | Qinghai | November 2019 | 0.15 ± 0.00 | 0.15 | 0.16 |
Acacia honey (n = 9) | Yanan, Shaanxi | April 2017 | 0.02 ± 0.01 | 0.01 | 0.03 |
Acacia honey (n = 9) | Yanan, Shaanxi | May 2019 | 0.04 ± 0.00 | 0.03 | 0.05 |
Acacia honey (n = 9) | Yanan, Shaanxi | April 2020 | 0.05 ± 0.01 | 0.04 | 0.07 |
Fruit (mg g−1) | |||||
Kiwifruit (n = 8) | Meixian, Shaanxi | October 2020 | 1.88 ± 0.13 | 1.75 | 2.05 |
Kiwifruit (n = 8) | Zhouzhi, Shaanxi | October 2020 | 1.14 ± 0.11 | 0.94 | 1.32 |
Durian (n = 5) | Guangdong | July 2020 | 0.11 ± 0.01 | 0.10 | 0.12 |
Durian (n = 5) | Hainan | June 2020 | 0.12 ± 0.01 | 0.10 | 0.13 |
Banana (n = 3) | Guangdong | December 2020 | 0.14 ± 0.00 | 0.14 | 0.14 |
Banana (n = 6) | Guangxi | December 2020 | 0.16 ± 0.01 | 0.15 | 0.18 |
Serum (mg L−1) | |||||
Control (n = 8) | / | / | 4.37 ± 1.22 | 2.43 | 6.65 |
HFD (n = 8) | / | / | 2.42 ± 1.27 | 1.29 | 5.25 |
Liver (mg g−1) | |||||
Control (n = 8) | / | / | 0.12 ± 0.01 | 0.10 | 0.14 |
HFD (n = 8) | / | / | 0.10 ± 0.02 | 0.07 | 0.13 |
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Wu, F.; Xu, F.; Liu, W.; Chen, S.; Luo, H.; Cheng, N.; Zhao, H.; Cao, W. A High-Performance Liquid Chromatography with Electrochemical Detection Method Developed for the Sensitive Determination of Ascorbic Acid: Validation, Application, and Comparison with Titration, Spectrophotometric, and High-Performance Liquid Chromatography with Diode-Array Detection Methods. Foods 2023, 12, 3100. https://doi.org/10.3390/foods12163100
Wu F, Xu F, Liu W, Chen S, Luo H, Cheng N, Zhao H, Cao W. A High-Performance Liquid Chromatography with Electrochemical Detection Method Developed for the Sensitive Determination of Ascorbic Acid: Validation, Application, and Comparison with Titration, Spectrophotometric, and High-Performance Liquid Chromatography with Diode-Array Detection Methods. Foods. 2023; 12(16):3100. https://doi.org/10.3390/foods12163100
Chicago/Turabian StyleWu, Fanhua, Fangrui Xu, Wen Liu, Sinan Chen, Haojie Luo, Ni Cheng, Haoan Zhao, and Wei Cao. 2023. "A High-Performance Liquid Chromatography with Electrochemical Detection Method Developed for the Sensitive Determination of Ascorbic Acid: Validation, Application, and Comparison with Titration, Spectrophotometric, and High-Performance Liquid Chromatography with Diode-Array Detection Methods" Foods 12, no. 16: 3100. https://doi.org/10.3390/foods12163100