Chemical fingerprint analysis for quality assessment and control of Curcuma longa L. rhizomes from Vietnam using a high-performance liquid chromatography-diode array detector (HPLC-DAD)

Author:

Do Chau Minh Vinh ThoORCID,Nguyen Thanh SilORCID,Nguyen Thanh Ngan,Le Kim Tham,Huynh Huynh Anh ThiORCID,Le Thi Truc Giang,Nguyen Thi Hong Mai

Abstract

Turmeric, extensively cultivated across Southeast Asia, especially in Vietnam, harbors active polyphenols, primarily curcumin (2–5%), renowned for its diverse health benefits. Pharmacopoeias recognize turmeric, yet it lacks standardized quality assessments and encounters challenges in extraction and identification due to natural variations and adulteration. This analytical method is vital for verifying the authenticity, purity, and quality of turmeric products in both the pharmaceutical and nutraceutical industries. This study successfully developed an efficient extraction process for curcumin (CUR), demethoxycurcumin (DMC), and bisdemethoxycurcumin (BDMC) from Curcuma longa L. rhizomes. The herbal powder was extracted with methanol (1:30, w/v) by the ultrasound-assisted method for 10 minutes, and this process was repeated three times. A high-performance liquid chromatography-diode array detector (HPLC-DAD) method was validated for the simultaneous quantification of three analytes, following the AOAC guideline and achieving a correlation coefficient (R2) value greater than 0.9950. Utilizing the HPLC-DAD method, the study developed a chemical fingerprint analysis for three analytes to identify the characteristic chemical components distinguishing turmeric from each region. Nineteen samples collected from various provinces across Vietnam were subjected to analysis. In all analyzed samples, the concentrations of CUR, DMC, and BDMC ranged from 0.77–10.30%, 0.33–6.92%, and 0.03–3.23%, respectively. CUR was determined to be the dominant compound in most samples, while BDMC consistently exhibited the lowest levels of content. Utilizing the findings derived from the analysis of RRT and RPA metrics, the research assessed variances across sample batches. It is suggested that this newly established approach can be applied to construct and develop raw material areas to serve the needs of each field.

Publisher

Pensoft Publishers

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3