scholarly journals Discovery of Quality Markers of Nucleobases, Nucleosides, Nucleotides and Amino Acids for Chrysanthemi Flos From Different Geographical Origins Using UPLC–MS/MS Combined With Multivariate Statistical Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiangwei Chang ◽  
Zhenyu Zhang ◽  
Hui Yan ◽  
Shulan Su ◽  
Dandan Wei ◽  
...  
Keyword(s):  
Amino Acids ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Ion Trap ◽  
Ultra Performance Liquid Chromatography ◽  
Support Vector ◽  
Multivariate Statistical ◽  
Quality Markers ◽  
Chrysanthemi Flos

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC–MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC–MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2′-deoxyadenosine, guanosine, adenosine 3′,5′-cyclic phosphate (cAMP), guanosine 3′,5′-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.

scholarly journals Metabolomic-Based Comparison of Traditional and Industrial Doenjang Samples with Antioxidative Activities

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1377
Author(s):  
Song-Hui Soung ◽  
Sunmin Lee ◽  
Seung-Hwa Lee ◽  
Hae-Jin Kim ◽  
Na-Rae Lee ◽  
...  
Keyword(s):  
Amino Acids ◽  
Statistical Analysis ◽  
Organic Acids ◽  
Biogenic Amines ◽  
Multivariate Statistical Analysis ◽  
Metabolite Profiling ◽  
New Products ◽  
Multivariate Statistical ◽  
Fermentation Processes

Numerous varieties of doenjang are manufactured by many food companies using different ingredients and fermentation processes, and thus, the qualities such as taste and flavor are very different. Therefore, in this study, we compared many products, specifically, 19 traditional doenjang (TD) and 17 industrial doenjang (ID). Subsequently, we performed non-targeted metabolite profiling, and multivariate statistical analysis to discover distinct metabolites in two types of doenjang. Amino acids, organic acids, isoflavone aglycones, non-DDMP (2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran-4- one) soyasaponins, hydroxyisoflavones, and biogenic amines were relatively abundant in TD. On the contrary, contents of dipeptides, lysophospholipids, isoflavone glucosides and DDMP-conjugated soyasaponin, precursors of the above-mentioned metabolites, were comparatively higher in ID. We also observed relatively higher antioxidant, protease, and β-glucosidase activities in TD. Our results may provide valuable information on doenjang to consumers and manufacturers, which can be used while selecting and developing new products.

scholarly journals Investigating the Impact of Anthropogenic and Natural Sources of Pollution on Quality of Water in Upper Indus Basin (UIB) by Using Multivariate Statistical Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Mansoor A. Baluch ◽  
Hashim Nisar Hashmi
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Quality Parameters ◽  
Anthropogenic Source ◽  
Indus River ◽  
Multivariate Statistical ◽  
Quality Of Water ◽  
The Impact

Water quality of the Indus River around the upper basin and the main river was evaluated with the help of statistical analysis. In order to analyze the similarities and dissimilarities for identifying the spatial variations in water quality of the Indus River and sources of contamination, multivariate statistical analysis, i.e., principle component analysis (PCA), cluster analysis, and descriptive analysis, was done. Data of 8 physicochemical quality parameters from 64 sampling stations belonging to 6 regions (labeled as M1, M2, M3, M4, M5, and M6) were used for analysis. The parameters used for assessing the water quality were pH, dissolved oxygen (DO), oxygen reducing potential (ORP), electrical conductivity (EC), total dissolved solids (TDS), salinity (%), and concentration of arsenic (As) and lead (Pb), respectively. PCA assisted in extracting and recognizing the responsible variation factors of water quality over the region, and the results showed three underlying factors including anthropogenic source pollution along with runoff due to rain and soil erosion were responsible for explaining the 93.87% of total variance. The parameters which were significantly influenced by anthropogenic impact are DO, EC, TDS (negative), and concentration of Pb (positive), while the concentration of As, % salinity, and ORP are affected by erosion and runoff due to rain. The worst pollution situation for regions M1 and M6 was due to the concentration of As which was approximately 400 μg/l (i.e., 40 times higher than minimum WHO recommendation). Furthermore, the results also indicated that, in the Indus River, three monitoring stations and five quality parameters are sufficient to have a reasonable confidence about the quality of water in this most important reserve of Pakistan.

scholarly journals UPLC-Q-TOF/MS Coupled with Multivariate Statistical Analysis as a Powerful Technique for Rapidly Exploring Potential Chemical Markers to Differentiate between Radix Paeoniae Alba and Radix Paeoniae Rubra

2013 ◽  
Vol 8 (4) ◽  
pp. 1934578X1300800 ◽  
Author(s):  
Nian-cui Luo ◽  
Wen Ding ◽  
Jing Wu ◽  
Da-wei Qian ◽  
Zhen-hao Li ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Ultra Performance Liquid Chromatography ◽  
Uv Spectra ◽  
Chemical Markers ◽  
Multivariate Statistical ◽  
Flight Mass Spectrometry ◽  
The Difference ◽  
Radix Paeoniae Alba ◽  
Tof Ms

To explore rapidly the potential chemical markers for differentiating Radix Paeoniae Alba and Radix Paeoniae Rubra, a method is proposed based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) coupled with multivariate statistical analysis. Batches of commercial samples were analyzed by UPLC-Q-TOF/MS. The datasets of tR-m/z pair, ion intensities and sample codes were further processed with orthogonal partial least squared discriminant analysis (OPLS-DA) to compare holistically the difference between these two kinds of samples. Then statistics were used to generate an S-plot, in which the variables (tR-m/z pair) contributing most to the difference were clearly depicted as points at the two ends of “S”, and the components correlated to these ions should be regarded as the chemical markers. The identities of the most changed markers can be identified by comparing the mass/UV spectra and retention times with those of reference compounds and/or tentatively assigned by matching empirical molecular formulae with those of known compounds published in the literature. Using this proposed approach, albflorin, paeoniflorin, oxypaeoniflorin, benzoylpaeoniflorin, galloylalbiflorin and paeoniflorigenone were found to be the differentiating components for discrimination of Radix Paeoniae Alba and Radix Paeoniae Rubra. Moreover, paeoniflorin sulfonate and its isomer, isomaltopaeoniflorin sulfonate, were found to be the characteristic markers for all Radix Paeoniae Alba samples that were processed by sulfurdioxide gas fumigation. The results suggested that this newly established approach could be used to explore rapidly the potential chemical markers for herbs with similar chemical characteristics.

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