Development and validation of a UV–Vis spectrophotometric method for the quantification of affinin in ethanolic extracts of Heliopsis longipes and commercial herbal products

Affinin, the main bioactive compound of Heliopsis longipes root, is an alkamide known for its multiple pharmacological effects, including anti-inflammatory, antihypertensive, and analgesic. Accurate quantification of affinin in extracts and commercial products is essential to ensure their quality and efficacy. In this study, a simple, robust, and accessible UV-Vis spectrophotometric method was developed and validated for the quantification of affinin in H. longipes ethanolic extracts and five marketed formulations in Mexico, and its performance was benchmarked against the gold-standard HPLC method. A linear calibration curve was established over 0.5 to 10 µg/mL, and the method was validated by evaluating linearity, accuracy, precision, specificity, and limits of detection (LOD) and quantification (LOQ). The maximum absorbance of affinin was determined at 230 nm in ethanol. Linearity was confirmed over the range of 0.5–10 µg/mL, with a correlation coefficient (R²) of 0.998. Precision, evaluated as intra- and inter-day reproducibility, showed relative standard deviations below 2%. Method accuracy was confirmed by standard addition experiments, with recovery values ranging from 98 to 102%. Specificity was supported by the absence of significant spectral interference in the UV spectra of the extract compared to the affinin standard, with an absorbance of 0.6795 ± 0.0026. The method also demonstrated adequate sensitivity, with LOD and LOQ of 0.298 µg/mL and 0.903 µg/mL, respectively. Affinin quantification in commercial formulations revealed variability in content, highlighting the need for rigorous quality control to ensure consistency among products. In conclusion, the validated UV–Vis method provides a rapid, cost-effective, and reliable tool for the quality control and standardization of H. longipes extracts and commercial products. Moreover, its use of ethanol as a bio-based solvent, low solvent consumption, and minimal waste generation align with green analytical chemistry principles, supporting more sustainable and accessible quality-control practices in the growing herbal product market.

Authors

Institutions

Publication Details

Journal
Journal of Food Measurement & Characterization
Published
2026-03-26
DOI
https://doi.org/10.1007/s11694-026-04182-4
Primary Topic
Herbal Medicine Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and validation of a UV–Vis spectrophotometric method for the quantification of affinin in ethanolic extracts of Heliopsis longipes and commercial herbal products

A Rojas-Molina, Francisco Javier Luna-Vázquez, Dailenys Marrero-Morfa, Josue David Mota-Morales et al.
Journal of Food Measurement & Characterization
Herbal Medicine Research Studies
article

Development and validation of a UV–Vis spectrophotometric method for the quantification of affinin in ethanolic extracts of Heliopsis longipes and commercial herbal products

A Rojas-Molina, Francisco Javier Luna-Vázquez, Dailenys Marrero-Morfa, Josue David Mota-Morales, Luis Alfonso Jiménez-Ortega, Victoria Ruiz-Castillo, Carlos Daniel Martínez-Hernández, César Ibarra-Alvarado
article en

Abstract

Affinin, the main bioactive compound of Heliopsis longipes root, is an alkamide known for its multiple pharmacological effects, including anti-inflammatory, antihypertensive, and analgesic. Accurate quantification of affinin in extracts and commercial products is essential to ensure their quality and efficacy. In this study, a simple, robust, and accessible UV-Vis spectrophotometric method was developed and validated for the quantification of affinin in H. longipes ethanolic extracts and five marketed formulations in Mexico, and its performance was benchmarked against the gold-standard HPLC method. A linear calibration curve was established over 0.5 to 10 µg/mL, and the method was validated by evaluating linearity, accuracy, precision, specificity, and limits of detection (LOD) and quantification (LOQ). The maximum absorbance of affinin was determined at 230 nm in ethanol. Linearity was confirmed over the range of 0.5–10 µg/mL, with a correlation coefficient (R²) of 0.998. Precision, evaluated as intra- and inter-day reproducibility, showed relative standard deviations below 2%. Method accuracy was confirmed by standard addition experiments, with recovery values ranging from 98 to 102%. Specificity was supported by the absence of significant spectral interference in the UV spectra of the extract compared to the affinin standard, with an absorbance of 0.6795 ± 0.0026. The method also demonstrated adequate sensitivity, with LOD and LOQ of 0.298 µg/mL and 0.903 µg/mL, respectively. Affinin quantification in commercial formulations revealed variability in content, highlighting the need for rigorous quality control to ensure consistency among products. In conclusion, the validated UV–Vis method provides a rapid, cost-effective, and reliable tool for the quality control and standardization of H. longipes extracts and commercial products. Moreover, its use of ethanol as a bio-based solvent, low solvent consumption, and minimal waste generation align with green analytical chemistry principles, supporting more sustainable and accessible quality-control practices in the growing herbal product market.

Journal of Food Measurement & Characterization
Autonomous University of Queretaro (MX), Centro de Investigación en Alimentación y Desarrollo (MX), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 7%
Herbal Medicine Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.