Quantification of Silymarin in Silybi mariani fructus: Challenging the Analytical Performance of Benchtop vs. Handheld NIR Spectrometers on Whole Seeds.

The content of the flavonolignan mixture silymarin and its individual components (silichristin, silidianin, silibinin A, silibinin B, isosilibinin A, and isosilibinin B) in whole and milled milk thistle seeds (Silybi mariani fructus) was analyzed with near-infrared spectroscopy. The analytical performance of one benchtop and two handheld near-infrared spectrometers was compared. Reference analysis was performed with HPLC following a Soxhlet extraction (European Pharmacopoeia) and a more resource-efficient ultrasonic extraction. The reliability of near-infrared spectral analysis determined through partial least squares regression models constructed independently for the spectral datasets obtained by the three spectrometers was as follows. The benchtop device NIRFlex N-500 performed the best both for milled and whole seeds with a root mean square error of CV between 0.01 and 0.17%. The handheld spectrometer MicroNIR 2200 as well as the microPHAZIR provided a similar performance (root mean square error of CV between 0.01 and 0.18% and between 0.01 and 0.23%, respectively). We carried out quantum chemical simulation of near-infrared spectra of silichristin, silidianin, silibinin, and isosilibinin for interpretation of the results of spectral analysis. This provided understanding of the absorption regions meaningful for the calibration. Further, it helped to better separate how the chemical and physical properties of the samples affect the analysis. While the study demonstrated that milling of samples slightly improves the performance, it was deemed to be critical only for the analysis carried out with the microPHAZIR. This study evidenced that rapid and nondestructive quantification of silymarin and individual flavonolignans is possible with miniaturized near-infrared spectroscopy in whole milk thistle seeds.

Challenging handheld NIR spectrometers with moisture analysis in plant matrices: Performance of PLSR vs. GPR vs. ANN modelling.

The global demand for natural products grows rapidly, intensifying the request for the development of high-throughput, fast, non-invasive tools for quality control applicable on-site. Moisture content is one of the most important quality parameters of natural products. It determines their market suitability, stability and shelf life and should preferably be constantly monitored. Miniaturized near-infrared (NIR) spectroscopy is a powerful method for on-site analysis, potentially fulfilling this requirement. Here, a feasibility study for applicability and analytical performance of three miniaturized NIR spectrometers and two benchtop instruments was evaluated in that scenario. The case study involved 192 dried plant extracts composed of five different plants harvested in different countries at various times within two years. The reference analysis by Karl Fischer titration determined the water content in this sample set between 1.36% and 6.47%. For the spectroscopic analysis half of the samples were laced with a drying agent to comply with the industry standard. The performance of various calibration models for NIR analysis was evaluated on the basis of root-mean square error of prediction (RMSEP) determined for an independent test set. Partial least squares regression (PLSR), Gaussian process regression (GPR) and artificial neural network (ANN) models were constructed for the spectral sets from each instrument. GPR and ANN models performed superior for all samples measured by handheld spectrometers and for native ones analyzed by benchtop instruments. Moreover, the accuracy penalty when analyzing native samples was lower for GPR and ANN prediction as well. With GPR or ANN calibration, miniaturized spectrometers offered the prediction performance at the level of the benchtop instruments. Therefore, in this analytical application miniaturized spectrometers can be used on-site with no penalty to the performance vs. laboratory-based NIR analysis.

Near-Infrared Spectroscopy as a Rapid Screening Method for the Determination of Total Anthocyanin Content in Sambucus Fructus.

Elderberry (Sambucus nigra L., fructus) is a very potent herbal drug, deriving from traditional European medicine (TEM). Ripe elderberries are rich in anthocyanins, flavonols, flavonol esters, flavonol glycosides, lectins, essential oils, unsaturated fatty acids and vitamins. Nevertheless, unripe elderflower fruits contain a certain amount of sambunigrin, a toxic cyanogenic glycoside, whose concentration decreases in the ripening process. Therefore, quality assurance must be carried out. The standard method described in literature is the photometric determination (pH-differential method) of the total anthocyanin content (TAC) that is the highest when the berries are ripe. The drawback of the pH-differential method is the extensive sample preparation and the low accuracy of the method. Therefore, the goal of this publication was to develop a fast non invasive near-infrared (NIR) method for the determination of TAC in whole berries. TAC of elderberries was measured using pH-differentiation method where TAC values of 632.87 mg/kg to 4342.01 mg/kg were measured. Additionally, cyanidin-3-O-glucoside, cyanidin-3-O-sambubioside and cyanidin-3-O-sambubioside-5-O-glucoside which represent more than 98% of TAC in elderberry were quantified using ultra high performance liquid chromatography-multiple wavelength detection-ultra high resolution-quadrupole-time of flight-mass spectrometry (UHPLC-MWD-UHR-Q-TOF-MS) and their sum parameter was determined, ranging between 499.43 mg/kg and 8199.07 mg/kg. Using those two methods as reference, whole elderberries were investigated by NIR spectroscopy with the Büchi NIRFlex N-500 benchtop spectrometer. According to the constructed partial least squares regression (PLSR) models the performance was as follows: a relative standard deviation (RSDPLSR) of 13.5% and root mean square error of calibration (RMSECV/RMSEC) of 1.31 for pH-differentiation reference and a RSDPLSR of 12.9% and RMSECV/RMSEC of 1.28 for the HPLC reference method. In this study, we confirm that it is possible to perform a NIR screening for TAC in whole elderberries. Using quantum chemical calculations, we obtained detailed NIR band assignments of the analyzed compounds and interpreted the wavenumber regions established in PLSR models as meaningful for anthocyanin content. The NIR measurement turned out to be a fast and cost-efficient alternative for the determination of TAC compared to pH-differential method and UHPLC-MWD-UHR-Q-TOF-MS. Due to the benefit of no sample preparation and extraction the technology can be considered as sustainable green technology. With the above mentioned inversely proportional ratio of TAC to total amount of toxic cyanogenic glycosides, NIR proves to be a reliable screening method for the ideal harvest time with maximal content of TAC and lowest content of cyanogenic glycosides in elderberry.