Response Surface Methodology-Driven Optimization of HPLC for the Determination of Caffeine, Chlorogenic Acid, and Caffeic Acid in Coffee

Most studies on coffee bioactive compounds have focused on single targets and relied on trial-and-error optimization. This study aims to develop a high-performance liquid chromatographic (HPLC) method optimized by response surface methodology using a central composite design (RSM-CCD), and a design of experiments (DoE) approach for the simultaneous quantification of caffeine (CAF), chlorogenic acid (CGA), and caffeic acid (CA) in roasted coffee samples. Separation was performed on a Luna C18 (2) column (250 × 4.6 mm; 5 μm). Three factors – methanol ratio, flow rate, and methanol gradient were investigated and optimized through 17 CCD runs, evaluating retention time, peak area, resolution, tailing factor, and theoretical plates. The optimum condition of 31.6% methanol, 0.81 mL/min flow rate, and 1%/min gradient enabled the simultaneous elution and separation of CGA, CAF, and CA at a retention time of 6.325, 7.444, and 9.326 minutes, respectively, and over a 12-minute chromatographic runtime. Validation according to International Council for Harmonization (ICH) Q2 (R1) guidelines confirmed excellent linearity (R² ≥ 0.998), LOD/LOQ (ppm) of 0.1718/0.5207 (CGA), 0.1773/0.5373 (CAF), and 0.0813/0.2464 (CA), with precision below 2% and recovery between 94.05% and 112.42%. Robusta levels (mg/g) were CGA (10.083 ± 0.229), CAF (18.838 ± 0.238), and CA (2.067 ± 0.044) while Arabica levels (mg/g) were CGA (16.641 ± 0.211), CAF (9.916 ± 0.157), and CA (2.178 ± 0.041). The RSM-driven HPLC successfully demonstrated efficient factor interaction modeling and robustness improvement. Consequently, the developed DoE-based method provides a rapid, selective, and reliable method for coffee quality evaluation and authenticity assessment.

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Publication Details

Journal
Tropical Journal of Natural Product Research
Published
2025-12-31
DOI
https://doi.org/10.26538/tjnpr/v9i12.34
Primary Topic
Coffee research and impacts
Type
article
Field-Weighted Citation Impact
0.00

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article

Response Surface Methodology-Driven Optimization of HPLC for the Determination of Caffeine, Chlorogenic Acid, and Caffeic Acid in Coffee

Nina Salamah, Hari Susanti, Muhammad Saputra
Tropical Journal of Natural Product Research
Coffee research and impacts
article

Response Surface Methodology-Driven Optimization of HPLC for the Determination of Caffeine, Chlorogenic Acid, and Caffeic Acid in Coffee

Nina Salamah, Hari Susanti, Muhammad Saputra
article en

Abstract

Most studies on coffee bioactive compounds have focused on single targets and relied on trial-and-error optimization. This study aims to develop a high-performance liquid chromatographic (HPLC) method optimized by response surface methodology using a central composite design (RSM-CCD), and a design of experiments (DoE) approach for the simultaneous quantification of caffeine (CAF), chlorogenic acid (CGA), and caffeic acid (CA) in roasted coffee samples. Separation was performed on a Luna C18 (2) column (250 × 4.6 mm; 5 μm). Three factors – methanol ratio, flow rate, and methanol gradient were investigated and optimized through 17 CCD runs, evaluating retention time, peak area, resolution, tailing factor, and theoretical plates. The optimum condition of 31.6% methanol, 0.81 mL/min flow rate, and 1%/min gradient enabled the simultaneous elution and separation of CGA, CAF, and CA at a retention time of 6.325, 7.444, and 9.326 minutes, respectively, and over a 12-minute chromatographic runtime. Validation according to International Council for Harmonization (ICH) Q2 (R1) guidelines confirmed excellent linearity (R² ≥ 0.998), LOD/LOQ (ppm) of 0.1718/0.5207 (CGA), 0.1773/0.5373 (CAF), and 0.0813/0.2464 (CA), with precision below 2% and recovery between 94.05% and 112.42%. Robusta levels (mg/g) were CGA (10.083 ± 0.229), CAF (18.838 ± 0.238), and CA (2.067 ± 0.044) while Arabica levels (mg/g) were CGA (16.641 ± 0.211), CAF (9.916 ± 0.157), and CA (2.178 ± 0.041). The RSM-driven HPLC successfully demonstrated efficient factor interaction modeling and robustness improvement. Consequently, the developed DoE-based method provides a rapid, selective, and reliable method for coffee quality evaluation and authenticity assessment.

Tropical Journal of Natural Product ResearchVol. 9(12)
Universitas Ahmad Dahlan (ID)
Universitas Ahmad Dahlan
Openalex Percentile: Top 29%
Coffee research and impacts
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