Saponins are tensioactive secondary metabolites produced by plants, valued in the pharmaceutical and food industries for their emulsifying and stabilizing properties. Quantifying them, however, has long been an analytical headache: these molecules lack chromophores in their structure, which restricts their detection under ultraviolet light.
Researchers at the National University of Costa Rica, the University of Costa Rica, and Houdek in Brookings, United States, have now reported an alternative. In a study published in Frontiers in Natural Products, they describe the development of a high-performance thin-layer chromatography (HPTLC) method for detecting and determining soyasaponins in six different soy-derived samples, combined with chemometric fingerprint analysis to improve the interpretation of closely migrating chromatographic signals.
The workflow is deliberately simple in its hardware. Samples were applied onto precoated silica gel 60 F254 plates, developed using an optimized mobile phase, and then derivatized with anisaldehyde/H₂SO₄ to render the saponins visible.
A key finding of the study concerns the detection wavelength. Scanning the plates at 366 nanometers produced higher chromatographic responses and more similar calibration behavior among the three target soyasaponins, Aa, Ba, and Bb, than scanning at 550 nanometers. The residual error of the pooled calibration fell dramatically, from 52.76 percent at 550 nm to 12.06 percent at 366 nm. According to the authors, this improvement supports the use of a simplified calibration approach under the selected conditions, reducing the burden of preparing separate calibration curves for each analyte.
The method’s quantitative performance was also assessed. It showed an experimental detection limit of 20.3 nanograms and good intraday repeatability, with relative standard deviation values below 1 percent for retention factor (Rf) and below 10 percent for peak area.
Beyond conventional peak-area analysis, the team introduced a chemometric layer that extends what the chromatographic plate can reveal. Chromatographic fingerprints were processed using a reference-guided strategy in which the experimental Rf values of soyasaponins Aa, Ba, and Bb were used to define reference-associated regions. The complete chromatographic profiles were then converted into regional descriptors and evaluated by hierarchical cluster analysis.
This chemometric treatment allowed similarities and differences among sample fingerprints to be visualized and helped identify the chromatographic regions that contributed most strongly to sample differentiation.
The practical implication is that laboratories equipped only with an HPTLC setup can obtain both targeted quantification of known soyasaponins and a global comparative view of complex soy-derived samples, without needing mass spectrometry or evaporative light-scattering detectors.
The chemometric component, the researchers emphasize, extends the information obtained from conventional HPTLC by facilitating comparison of complex samples and highlighting chromatographic regions for subsequent targeted characterization. In other words, the fingerprinting step does not replace confirmatory analysis; rather, it acts as a triage tool that points analysts toward the most informative parts of the chromatogram for further, more detailed study.
Subject of Research: Development of an HPTLC method with chemometric fingerprinting for identifying and quantifying soyasaponins in soy-derived samples
Article Title: Development of a high-performance thin-layer chromatography (HPTLC) method coupled with chemometric fingerprinting analysis for rapid identification and quantification of soyasaponins
Article References: Chavarría-Montero, G., Sibaja-Salazar, A., Nates, S., Álvarez-Valverde, V., & Jiménez-Bonilla, P. (2026). Development of a high-performance thin-layer chromatography (HPTLC) method coupled with chemometric fingerprinting analysis for rapid identification and quantification of soyasaponins. Frontiers in Natural Products, 5, 1985816. https://doi.org/10.3389/fntpr.2026.1985816
Image Credits: AI Generated
DOI: 10.3389/fntpr.2026.1985816
Keywords: HPTLC, soyasaponins, chemometric fingerprinting, hierarchical cluster analysis, saponins, thin-layer chromatography, analytical chemistry, natural product analysis, soy-derived samples, densitometry, Development, high-performance
News Source: Bethany Barker. (October 29, 2026). HPTLC Method with Chemometric Fingerprinting Speeds Up Soyasaponin Analysis. Scienmag.
