AUTHOR=Olivaro Cristina , Núñez Nerea , Basile Patricia , Mederos América , Reyno Rafael , Saurina Javier , Núñez Oscar 

TITLE=LC-HRMS fingerprinting and chemometrics for the characterization and classification of Lotus cultivars from Uruguay: a study on phenolic composition

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2025.1646758

DOI=10.3389/fmolb.2025.1646758

ISSN=2296-889X

ABSTRACT=IntroductionThe Lotus genus, part of the legume family, comprises over 180 species distributed across diverse ecosystems worldwide. Its broad genetic diversity enables adaptation to various environmental conditions and represents a valuable resource for breeding programs targeting key agronomic traits. One of the most attractive features of Lotus species is the presence of condensed tannins in the forage, which, in ruminants, help prevent bloat, exhibit antiparasitic properties, enhance the absorption of non-ammonia nitrogen compounds, and reduce greenhouse gas emissions.Aims and methodsThis study aimed to develop a UHPLC-HRMS method for classifying ten Lotus cultivars produced in Uruguay using a non-targeted metabolomic fingerprinting approach. Five cultivars belong to Lotus corniculatus, three to Lotus uliginosus, and two are interspecific hybrids. The analysis focused on phenolic compound-rich fingerprints. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used for data exploration and classification, and to identify key phenolic compounds with high discriminant potential. Finally, cultivar-specific polyphenolic compounds were tentatively identified based on chromatographic and high-resolution mass spectrometry (HRMS/MS) data obtained from all cultivars.ResultsWhen defining four classes (L. uliginosus, L. corniculatus, and the two hybrids), the optimal PLS-DA model required six latent variables and achieved 100% classification accuracy, with both sensitivity and specificity reaching 100%. Additional PLS-DA models were developed to assess intra-species discrimination among the 3 L. uliginosus and 5 L. corniculatus cultivars, with varying degrees of separation observed. In each PLS-DA model, VIP loadings scores allowed the selection of the most discriminant phenolic compounds for each class under study. A total of 105 compounds, including phenolic acids, flavonols, flavan-3-ols, proanthocyanidins, and organic acids, were tentatively identified by analyzing all cultivars.