HPTLC Fingerprinting—Rapid Method for the Differentiation of Honeys of Different Botanical Origin Based on the Composition of the Lipophilic Fractions

Makowicz, Ewa; Jasicka-Misiak, Izabela; Teper, Dariusz; Kafarski, Paweł

doi:10.3390/molecules23071811

Cited by 18 publications

(16 citation statements)

References 32 publications

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“…This technique can be particularly useful as a fast screening method because of its high precision and low time consumption. Moreover, as it was described previously and was confirmed in this study [18] the UAE extraction is probably more suitable for lipophilic fraction profile creation seeing that the extracted compounds are present in higher concentration than in SPE fraction and for screening purposes one cycle of extraction is suitable, so the time and cost are decreasing. Furthermore, the number of steps needed to obtained the fraction ready to analysis is fewer than in case of SPE.…”

Section: Hptlc Analysissupporting

confidence: 78%

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Botanical Origin Authentication of Polish Phacelia Honey Using the Combination of Volatile Fraction Profiling by HS-SPME and Lipophilic Fraction Profiling by HPTLC

et al. 2019

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Eleven samples of Polish Phacelia tanacetifolia Benth., three Brassica napus and one Salix spp. honeys were characterized by melissopalynology and analysis of the compositions of their volatile fractions. Headspace solid-phase microextraction coupled with gas chromatography mass spectrometry (HS-SPME/GC-MS) using PDMS/CAR/DVB fiber was used for the isolation of low-molecular weight compounds which create a volatile fraction. To differentiate and indicate the most representative unifloral samples, chemometric techniques such as principal component analysis (PCA) and hierarchical-tree clustering (HTC) were applied to the dataset of the chromatographic fingerprints. Based on the obtained results, a unique chemical fingerprint of phacelia honey was generated. This study allows us to discriminate the botanical origin of the phacelia honeys based on the GC-MS and HPTLC analysis. In case of the GC-MS analysis trans-linalool oxide, hotrienol, cislinalool oxide and cis-epoxylinalool were identified as a predominant compound. Additionally lipophilic fractions obtained by ultrasound-assisted extraction (UAE) and solid-phase extraction (SPE) were subjected to the HPTLC analysis. It allowed the construction of a barcode-type identifier that could be used to differentiate the honey samples even without identifying the individual components of the obtained fraction.

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Section: Hptlc Analysissupporting

confidence: 78%

“…Ultrasound solvent extraction and solid-phase extraction were performed according to the procedures described previously [17][18][19]. For each honey sample, the extraction was performed in triplicate.…”

Section: Ultrasound-assisted Extraction (Uae) and Solid-phase Extractmentioning

confidence: 99%

Botanical Origin Authentication of Polish Phacelia Honey Using the Combination of Volatile Fraction Profiling by HS-SPME and Lipophilic Fraction Profiling by HPTLC

et al. 2019

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“…The UPLC-MS data was used for chemometric analysis as described in [ 11 ], while UPLC-PDA was used to determine the concentrations of the three standards, following validation of the method using ICH guidelines [ 23 ]. The root extracts were analysed using a Waters Acquity Ultra Performance Liquid Chromatography system equipped with a photodiode array (PDA) detector (Waters, Milford, MA, USA) and interfaced with a Xevo G2QToF MS (Waters, Milford, MA, USA).…”

Section: Methodsmentioning

confidence: 99%

“…Compared to manual TLC, the technique yields better reproducibility, resolution and sensitivity, particularly when combined with improved digital scanning and documentation software, resulting in a more complete extraction of the information. In combination with chemometric data analysis, HPTLC has been reported to be a powerful tool for statistical analysis of the chemical profiles of herbal medicines, and for exploring differences and similarities within individual samples [ 9 , 10 , 11 ]. The development of rTLC software, available as an open-source web package for image processing, presents new opportunities for chemometric analysis of HPTLC chromatograms.…”

Section: Introductionmentioning

confidence: 99%

Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

et al. 2021

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Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-β-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.

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“…It needs to be emphasised that the combination of HPTLC and multivariate analysis is not new, not even in the context of honey analysis [24,[40][41][42]. What is novel about this study is the way, outlined below, how multivariate analysis of HPTLC profiles can be used to derive a dynamic, representative reference standard for quality control purposes.…”

Section: Plos Onementioning

confidence: 99%

Development of an HPTLC-based dynamic reference standard for the analysis of complex natural products using Jarrah honey as test sample

et al. 2021

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In this paper, we describe a novel approach to the development of a reference standard for the quality control of complex natural products, which will assist in the assessment of their authenticity and purity. The proposed method provides a template for the selection of samples, which can be pooled to obtain a reference standard. A shortfall of such an approach is, however, that the pooled sample is static in nature and therefore unable to capture difference in processing conditions or natural variations triggered by geographical or climatic impacts over time. To address this, the paper also outlines the development of a dynamic reference standard, which allows for ongoing adjustments to future variations. The method employs High-Performance Thin Layer Chromatography (HPTLC) derived extract profiles processed by multivariate analysis. The development of the dynamic reference standard is illustrated using honey, a complex natural matrix, as an example.

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HPTLC Fingerprinting—Rapid Method for the Differentiation of Honeys of Different Botanical Origin Based on the Composition of the Lipophilic Fractions

Cited by 18 publications

References 32 publications

Botanical Origin Authentication of Polish Phacelia Honey Using the Combination of Volatile Fraction Profiling by HS-SPME and Lipophilic Fraction Profiling by HPTLC

Botanical Origin Authentication of Polish Phacelia Honey Using the Combination of Volatile Fraction Profiling by HS-SPME and Lipophilic Fraction Profiling by HPTLC

Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

Development of an HPTLC-based dynamic reference standard for the analysis of complex natural products using Jarrah honey as test sample

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