Integrated HPLC-DAD and multivariate analysis for exploratory prioritisation of candidate marker compounds in <i>Lactuca indica</i>

Lactuca indica L. is a medicinal plant widely used in traditional Vietnamese medicine. A validated HPLC-DAD method was developed for the simultaneous quantification of four selected phenolic compounds, chlorogenic acid, caffeic acid, luteolin-7-O-glucuronide, and luteolin, in 12 batches collected from northern Vietnam. The method showed good linearity (R2 ≥ 0.9999), recoveries of 97.8–102.7%, repeatability of 1.15–1.72% RSD, intermediate precision of 1.73–3.37% RSD, and LOD/LOQ values of 0.02–0.84/0.07–2.79 µg mL−1. DPPH radical scavenging activity showed substantial between-batch variation, with IC50, extract values ranging from 30.40 to 97.91 µg mL−1. Principal component analysis revealed notable variation in phenolic compound profiles, while partial least squares regression explored the relationship between phenolic composition and antioxidant activity. An integrated HPLC–DAD/PLSR analysis identified chlorogenic acid and luteolin-7-O-glucuronide as the variables most closely associated with DPPH radical-scavenging activity (VIP > 1), providing a data-driven basis for their prioritisation as candidate markers for DPPH-oriented quality evaluation of L. indica.

Authors

Institutions

Publication Details

Journal
Natural Product Research
Published
2026-08-03
DOI
https://doi.org/10.1080/14786419.2026.2708284
Primary Topic
Phytochemicals and Antioxidant Activities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrated HPLC-DAD and multivariate analysis for exploratory prioritisation of candidate marker compounds in Lactuca indica

Phương Thiện Thương, Thanh Hiếu Đoàn, Thi Sao Mai Pham, Dang Van Thanh et al.
Natural Product Research
Phytochemicals and Antioxidant Activities
article

Integrated HPLC-DAD and multivariate analysis for exploratory prioritisation of candidate marker compounds in Lactuca indica

Phương Thiện Thương, Thanh Hiếu Đoàn, Thi Sao Mai Pham, Dang Van Thanh, Khac Tung Nguyen, Thi Kieu Anh Nguyen
article en

Abstract

Lactuca indica L. is a medicinal plant widely used in traditional Vietnamese medicine. A validated HPLC-DAD method was developed for the simultaneous quantification of four selected phenolic compounds, chlorogenic acid, caffeic acid, luteolin-7-O-glucuronide, and luteolin, in 12 batches collected from northern Vietnam. The method showed good linearity (R2 ≥ 0.9999), recoveries of 97.8–102.7%, repeatability of 1.15–1.72% RSD, intermediate precision of 1.73–3.37% RSD, and LOD/LOQ values of 0.02–0.84/0.07–2.79 µg mL−1. DPPH radical scavenging activity showed substantial between-batch variation, with IC50, extract values ranging from 30.40 to 97.91 µg mL−1. Principal component analysis revealed notable variation in phenolic compound profiles, while partial least squares regression explored the relationship between phenolic composition and antioxidant activity. An integrated HPLC–DAD/PLSR analysis identified chlorogenic acid and luteolin-7-O-glucuronide as the variables most closely associated with DPPH radical-scavenging activity (VIP > 1), providing a data-driven basis for their prioritisation as candidate markers for DPPH-oriented quality evaluation of L. indica.

Natural Product Research
Thai Nguyen University (VN), Institute for Nuclear Science and Technology (VN), Hanoi University of Pharmacy (VN), Korea Institute of Science and Technology (KR), Vietnam Academy of Science and Technology (VN), International University (KH)
Openalex Percentile: Top 12%
Phytochemicals and Antioxidant Activities
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.