Lavender hydrosol analysis using UV spectroscopy data and partial least squares regression.

Sára Preiner, Bálint Levente Tarcsay, Dóra Pethő, Norbert Miskolczi

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Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Sára PreinerResearch Centre for Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem st.10, Veszprém, 8200, Hungary.

Bálint Levente TarcsayResearch Centre for Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem st.10, Veszprém, 8200, Hungary.

Dóra PethőResearch Centre for Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem st.10, Veszprém, 8200, Hungary.

Norbert MiskolcziResearch Centre for Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem st.10, Veszprém, 8200, Hungary.

Funding

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6 · The paper itself

Abstract

The aim of our work was to estimate the composition of hydrosol produced as a byproduct of lavender steam distillation using UV-Vis spectrophotometry in the 200-600 nm wavelength range through a machine learning algorithm. The dissolved components of lavender essential oil (EO) from lavender hydrosol samples were extracted via liquid-liquid extraction, using three different solvents (pentane, heptane and diethyl ether). The UV-Vis absorbance spectra of the extracts were recorded and the composition analyzed using GC-MS. The composition data obtained allowed for the calculation of changes within the quantities of different EO components in the samples. The partial least squares regression technique (PLS) was utilized to establish a connection between changes in the composition of the hydrosol and the changes in the UV-Vis spectra. After optimization the established PLS model showed an

Indexed as

Hydrosol analysisLavenderLavender hydrosol analysis using UV–Vis spectroscopy and partial least squares regressionPartial least squares regressionUV–Vis

Identifiers

PMID40255463

DOI10.1016/j.mex.2025.103304

PMCPMC12008665

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