scholarly journals Determination of Floral Origin Markers of Latvian Honey by Using IRMS, UHPLC-HRMS, and 1H-NMR

Foods ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 42
Author(s):  
Kriss Davids Labsvards ◽  
Vita Rudovica ◽  
Rihards Kluga ◽  
Janis Rusko ◽  
Lauma Busa ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Principal Component ◽  
Isotope Ratio Mass Spectrometry ◽  
Calluna Vulgaris ◽  
Stable Isotope Ratio ◽  
Elevated Concentration ◽  
Economic Significance ◽  
Analysis Methods

The economic significance of honey production is crucial; therefore, modern and efficient methods of authentication are needed. During the last decade, various data processing methods and a combination of several instrumental methods have been increasingly used in food analysis. In this study, the chemical composition of monofloral buckwheat (Fagopyrum esculentum), clover (Trifolium repens), heather (Calluna vulgaris), linden (Tilia cordata), rapeseed (Brassica napus), willow (Salix cinerea), and polyfloral honey samples of Latvian origin were investigated using several instrumental analysis methods. The data from light stable isotope ratio mass spectrometry (IRMS), ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and nuclear magnetic resonance (NMR) analysis methods were used in combination with multivariate analysis to characterize honey samples originating from Latvia. Results were processed using the principal component analysis (PCA) to study the potential possibilities of evaluating the differences between honey of different floral origins. The results indicate the possibility of strong differentiation of heather and buckwheat honeys, and minor differentiation of linden honey from polyfloral honey types. The main indicators include depleted δ15N values for heather honey protein, elevated concentration levels of rutin for buckwheat honey, and qualitative presence of specific biomarkers within NMR for linden honey.

scholarly journals Principal Component Analysis from Mass Spectrometry Data Combined to a Sensory Evaluation as a Suitable Method for Assessing Bitterness of Enzymatic Hydrolysates Produced from Micellar Casein Proteins

Foods ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1354
Author(s):  
Dahlia Daher ◽  
Barbara Deracinois ◽  
Alain Baniel ◽  
Elodie Wattez ◽  
Justine Dantin ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Principal Component Analysis ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Liquid Fraction ◽  
Principal Component ◽  
Component Analysis ◽  
Mass Spectrometry Data ◽  
Sensory Panel ◽  
Enzymatic Hydrolysates

Enzymatic hydrolysis of food proteins generally changes the techno-functional, nutritional, and organoleptic properties of hydrolyzed proteins. As a result, protein hydrolysates have an important interest in the food industries. However, they tend to be characterized by a bitter taste and some off-flavors, which limit their use in the food industry. These tastes and aromas come from peptides, amino acids, and volatile compounds generated during hydrolysis. In this article, sixteen more or less bitter enzymatic hydrolysates produced from a milk protein liquid fraction enriched in micellar caseins using commercially available, food-grade proteases were subjected to a sensory analysis using a trained and validated sensory panel combined to a peptidomics approach based on the peptide characterization by reverse-phase high-performance liquid chromatography, high-resolution mass spectrometry, and bioinformatics software. The comparison between the sensory characteristics and the principal components of the principal component analysis (PCA) of mass spectrometry data reveals that peptidomics constitutes a convenient, valuable, fast, and economic intermediate method to evaluating the bitterness of enzymatic hydrolysates, as a trained sensory panel can do it.

scholarly journals HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling

Foods ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 294 ◽  
Author(s):  
Mariateresa Maldini ◽  
Gilda D’Urso ◽  
Giordana Pagliuca ◽  
Giacomo Luigi Petretto ◽  
Marzia Foddai ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Principal Component ◽  
Arbutus Unedo ◽  
Metabolomics Study ◽  
Layer Chromatography ◽  
Digital Record ◽  
Resolution Mass

A comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC–HRMS), coupled with Principal Component Analysis (PCA) was carried out by performing a combined metabolomics study to discriminate Arbutus unedo (A. unedo) plants. For a rapid digital record of A. unedo extracts (leaves, yellow fruit, and red fruit collected in La Maddalena and Sassari, Sardinia), HPTLC was used. Data were then analysed by PCA with the results of the ability of this technique to discriminate samples. Similarly, extracts were acquired by non-targeted LC–HRMS followed by unsupervised PCA, and then by LC–HRMS (MS) to identify secondary metabolites involved in the differentiation of the samples. As a result, we demonstrated that HPTLC may be applied as a simple and reliable untargeted approach to rapidly discriminate extracts based on tissues and/or geographical origins, while LC–HRMS could be used to identify which metabolites are able to discriminate samples.

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