Abstract

This study examined the applicability of near-infrared (NIR) spectroscopy coupled with multivariate data analysis (MVA) to determine the ideal harvest time of Verbena officinalis. NIR analyses were performed non-invasively on the fresh plant material based on the quantification of the key constituents verbenalin and verbascoside. Vibrational spectroscopic measurements were performed applying a conventional NIR benchtop device as well as a laboratory independent handheld NIR spectrometer. A novel high performance liquid chromatography (HPLC) method was applied as a reference method. For both instruments partial least squares (PLS) regression models were established performing cross validations (CV) and test-set validations (TSV). Quality parameters obtained for the benchtop device revealed that the newly established NIR method enabled reliable quantifications of the main compounds verbenalin and verbascoside related to the dried and fresh plant material. The results of the miniaturised spectrometer revealed that accurate quantitative calibration models could be developed for verbascoside achieving a comparable prediction power to the benchtop device. PLS models for verbenalin were less precise suggesting the application of portable devices including a different spectral range and resolution. The work demonstrated the feasibility of NIR vibrational spectroscopy performing direct measurements on pharmaceutically relevant fresh plant material enabling a quick and simple determination of the ideal harvest time of Verbena officinalis.

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