Optimization of Chlorogenic Acid Extraction from Green Coffee Beans Using Response Surface Methodology

Lai Thi Ngoc Ha 1 , Nguyen Viet Phuong 2 , Tran Thi Hoai 1 , Dao Thi Viet Ha 3 and Hoang Hai Ha 1

1Faculty of Food Science and Technology, Vietnam National University of Agriculture, Hanoi 131000, Vietnam
2Biotechnology Centre, Food Industrial Collage, Phu Tho 290000, Vietnam
3Scientific Management and International Cooperation Office, Food Industrial Collage, Phu Tho 290000, Vietnam
Received: Apr 10, 2019 /
Revised: Jul 13, 2021 /
Published: Jun 6, 2019

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Abstract

Chlorogenic acid is a natural antioxidant that is widespread in the plant kingdom and can be found at a high content level in green coffee beans. This secondary metabolite in green coffee beans has potent biological properties including antioxidant, anti-inflammatory, anti-cancer, anti-obesity, anti-hypertension, and anticonvulsant. In this study, the extraction of chlorogenic acid from Vietnamese green coffee beans was optimized using the response surface methodology. A second-order polynomial model with three important variables (liquid-to-solid ratio, temperature, and extraction time) was used. A rotatable central composite design consisting of 21 experimental runs with three replicates at the center point was applied to describe the experimental data. The experimental results properly conformed to the constructed model (R2 = 0.8549). The optimized conditions were as follows: 40% ethanol (v/v), a liquid-to-solid ratio of 11.77, at 85oC for 64 min. Four extractions were performed in parallel using the optimal conditions to validate the model. The experimental values highly agreed with the predicted value (P <0.05).

Keywords: Phenolic compound, ethanolic extraction, HPLC quantification, validated model

Article Details

How to Cite
Ha, L. T. N., Phuong, N. V., Hoai, T. T., Viet Ha, D. T., & Ha, H. H. (2019). Optimization of Chlorogenic Acid Extraction from Green Coffee Beans Using Response Surface Methodology. Vietnam Journal of Agricultural Sciences, 2(1), 332-342. https://doi.org/10.31817/vjas.2019.2.1.04

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