Characterization of two closely related citrus cultivars using UPLC-ESI-MS/MS-based widely targeted metabolomics

Citrus cultivars are widely spread worldwide, and some of them only differ by specific mutations along the genome. It is difficult to distinguish them by traditional morphological identification. To accurately identify such similar cultivars, the subtle differences between them must be detected. In this study, UPLC-ESI-MS/MS-based widely targeted metabolomics analysis was conducted to study the chemical differences between two closely related citrus cultivars, Citrus reticulata ‘DHP’ and C. reticulata ‘BZH’. Totally 352 metabolites including 11 terpenoids, 35 alkaloids, 80 phenolic acids, 25 coumarins, 7 lignans, 184 flavonoids and 10 other compounds were detected and identified; Among them, 15 metabolites are unique to DHP and 16 metabolites are unique to BZH. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA) can be used to clearly discriminate between DHP and BZH. 93 metabolites including 36 down-regulated and 57 up-regulated are significantly different in DHP and BZH. They are mainly involved in the biosynthesis of flavonoids, flavones, flavonols, and isoflavonoids. In addition, the relative content levels of flavonoids, alkaloids, and terpenoids are much higher in the peel of DHP than that of BZH, the presence of which may correlate with the quality difference of the peels. The results reported herein indicate that metabolite analysis based on UPLC-ESI-MS/MS is an effective means of identifying cultivars with different genotypes, especially those that cannot be distinguished based on traditional identification methods.

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GC-MS and HPLC-ESI-MS-MS Characterization of Sanchezia oblonga (Acanthaceae) Extracts

Journal of Food Research ◽

10.5539/jfr.v9n1p57 ◽

2020 ◽

Vol 9 (1) ◽

pp. 57

Author(s):

Juliana Mourão Ravasi ◽

Giuseppina Negri ◽

Antonio Salatino ◽

Maria Luiza Faria Salatino ◽

Marco Aurelio Sivero Mayworm

Keyword(s):

Sinapic Acid ◽

Principal Component ◽

Hierarchical Cluster ◽

Lilium Longiflorum ◽

Potential Health ◽

Esi Ms ◽

Aerial Parts ◽

Sorghum Grain ◽

New Compounds

The genus Sanchezia (Acanthaceae) comprises neotropical herbs and shrubs with showy flowers. Sanchezia oblonga (syn. S. nobilis) is a shrub of the rainforests of central and south America. The ethanolic extracts of leaves and stems from S. oblonga were analyzed by GC-EI-MS and RPHPLC-DAD-ESI-MS/MS. Fatty acids (free and esterified) and phytosterols were detected by the former method. Benzyl alcohol glycosides (21 and 25), sinapic acid glycoside esters (29 and 31), ethyl rosmarinate (24), sinapic acid-O-glucoside (28), dihydrosinapic acid-O-glucoside (26), catechin-O-arabinoside (36), in addition to flavonols glycosides (23, 32, 33 and 35) and rosmarinic acid-3’-O-glucoside (34) were detected by RPHPLC-DAD-ESI-MS/MS. Three new compounds, detected only in leaves, were tentatively identified as phenylpropane glyceride derivatives 1-O-coumaroyl-2-hydroxy propanal (20) and 1-O-coumaroyl-2-O-glycosyl propanal (22, 30). Compounds 20, 22 and 30 from S. oblonga are similar with phenylpropane glycerides present in red sorghum (Sorghum bicolor L. (Moench) and Lilium longiflorum Thunb. It is noteworthy that S. oblonga could be used in cooking as a complement after more detailed studies. Sorghum grain foods exhibit potential health benefits against chronic diseases related to over-nutrition. Lilium longiflorum possess flower buds and bulbs that are used for both culinary and medicinal purposes in many parts of the world. Studies on chemical composition and biological activity of the genus Sanchezia are scarce. The presence of phytosterols and flavonol glycosides were recently reported in leaves from this species. However, the chemical profile of the extracts analyzed in this work differs from that previously reported for aerial parts of S. nobilis (sin. S. oblonga). Further studies, including statistical methods, such as principal component analysis and hierarchical cluster analysis will be needed to evaluate chemical markers for this species.

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Metabolite Profiling of Sorghum Seeds of Different Colors from Different Sweet Sorghum Cultivars Using a Widely Targeted Metabolomics Approach

International Journal of Genomics ◽

10.1155/2020/6247429 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Yaxing Zhou ◽

Zhenguo Wang ◽

Yan Li ◽

Zhigang Li ◽

Hui Liu ◽

...

Keyword(s):

Sweet Sorghum ◽

Principal Component ◽

Seed Color ◽

Targeted Metabolomics ◽

Phenotypic Differences ◽

Benzoic Acid Derivatives ◽

Orthogonal Signal Correction ◽

Significant Difference ◽

Comprehensive Comparison ◽

Widely Targeted Metabolomics

Sweet sorghum (Sorghum bicolor) is one of the most important cereal crops in the world with colorful seeds. To study the diversity and cultivar-specificity of phytochemicals in sweet sorghum seeds, widely targeted metabolomics was used to analyze the metabolic profiles of the white, red, and purple seeds from three sweet sorghum cultivars Z6, Z27, and HC4. We identified 651 metabolites that were divided into 24 categories, including fatty acids, glycerolipids, flavonoids, benzoic acid derivatives, anthocyanins, and nucleotides and its derivatives. Among them, 217 metabolites were selected as significantly differential metabolites which could be related to the seed color by clustering analysis, principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA). A significant difference was shown between the red seed and purple seed samples, Z27 and HC4, in which 106 were downregulated and 111 were upregulated. The result indicated that 240 metabolites were significantly different, which could be related to the purple color with 58 metabolites downregulated and 182 metabolites upregulated. And 199 metabolites might be involved in the red phenotype with 54 downregulated and 135 upregulated. There were 45 metabolites that were common to all three cultivars, while cyanidin O-malonyl-malonyl hexoside, cyanidin O-acetylhexoside, and cyanidin 3-O-glucosyl-malonylglucoside were significantly upregulated red seeds, which could be the basis for the variety of seed colors. Generally, our findings provide a comprehensive comparison of the metabolites between the three phenotypes of S. bicolor and an interpretation of phenotypic differences from the point of metabolomics.

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A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽

10.3390/foods10061411 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1411

Author(s):

José Luis P. Calle ◽

Marta Ferreiro-González ◽

Ana Ruiz-Rodríguez ◽

Gerardo F. Barbero ◽

José Á. Álvarez ◽

...

Keyword(s):

Random Forest ◽

Raw Materials ◽

Principal Component ◽

Hierarchical Cluster ◽

Raw Material ◽

Support Vector ◽

Protected Designation Of Origin ◽

Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

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Analysis of Flavonoid Metabolites in Buckwheat Leaves Using UPLC-ESI-MS/MS

Molecules ◽

10.3390/molecules24071310 ◽

2019 ◽

Vol 24 (7) ◽

pp. 1310 ◽

Cited By ~ 11

Author(s):

Jing Li ◽

Pu Yang ◽

Qinghua Yang ◽

Xiangwei Gong ◽

Hongchi Ma ◽

...

Keyword(s):

Clustering Analysis ◽

Principal Component ◽

Ultra Performance Liquid Chromatography ◽

Tartary Buckwheat ◽

Biological Functions ◽

Common Buckwheat ◽

Flavonoid Content ◽

Esi Ms ◽

Orthogonal Signal Correction ◽

Signal Correction

Flavonoids from plants are particularly important in our diet. Buckwheat is a special crop that is rich in flavonoids. In this study, four important buckwheat varieties, including one tartary buckwheat and three common buckwheat varieties, were selected as experimental materials. The total flavonoid content of leaves from red-flowered common buckwheat was the highest, followed by tartary buckwheat leaves. A total of 182 flavonoid metabolites (including 53 flavone, 37 flavonol, 32 flavone C-glycosides, 24 flavanone, 18 anthocyanins, 7 isoflavone, 6 flavonolignan, and 5 proanthocyanidins) were identified based on Ultra Performance Liquid Chromatography–Electrospray Ionization–Tandem Mass Spectrometry (UPLC-ESI-MS/MS) system. Through clustering analysis, principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA), different samples were clearly separated. Considerable differences were observed in the flavonoid metabolites between tartary buckwheat leaves and common buckwheat leaves, and both displayed unique metabolites with important biological functions. This study provides new insights into the differences of flavonoid metabolites between tartary buckwheat and common buckwheat leaves and provides theoretical basis for the sufficient utilization of buckwheat.

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Characterization of Physical and Chemical Evaluation on Six Apple Varieties

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.807-809.1954 ◽

2013 ◽

Vol 807-809 ◽

pp. 1954-1959

Author(s):

Li Yan Gong ◽

Bin Li ◽

Jin Feng Bi ◽

Sha Sha Bai ◽

Xian Jun Meng

Keyword(s):

Chemical Properties ◽

Chemical Characterization ◽

Principal Component ◽

Hierarchical Cluster ◽

Soluble Solids ◽

Physical And Chemical Properties ◽

Apple Varieties ◽

Physical And Chemical ◽

And Chemical Properties

Physical and chemical characterization of 6 apple varieties (Early Golden Delicious, Jonagold, Hanfu, Ralls, Rainier and Fuji) from China was performed using pattern recognition tools. Measurements were taken on 12 parameters including weigh, colour, fruit firmness, crude fiber, total soluble solids, titration acid, water, Vitamin C, edible rate and juice yield .The results showed that physical and chemical properties existed different variance in apple varieties. The coefficient of variance of 12 properties was from 2.15% to 69.04%. The different apple varieties were investigated by principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA revealed that the first four components represented 95.13% of the total variability in properties and different apple groups. HCA classified samples into three groups on the basis of the physical and chemical properties.

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Fruit characterization of 36 cape gooseberry hybrids for identification of potential industrial or fresh consumption uses

Revista Colombiana de Ciencias Hortícolas ◽

10.17584/rcch.2021v15i2.12526 ◽

2021 ◽

Vol 15 (2) ◽

Author(s):

Tulio César Lagos-Burbano ◽

Diego Fernando Mejía-España ◽

Oscar Arango-Bedoya ◽

Zulma Yizeth Villaquirán-Samboni ◽

Liz Katherine Lagos-Santander ◽

...

Keyword(s):

Nutritional Quality ◽

Genetic Improvement ◽

Agricultural Research ◽

Principal Component ◽

Hierarchical Cluster ◽

Seed Content ◽

Total Variability ◽

Cape Gooseberry ◽

Transformation Processes

The cape gooseberry is the second most exported fruit in Colombia. There are, however, little information available on genetic improvement processes and limited research on the fruit components. The objective of this study was to characterize the fruits of 36 hybrids, obtained from double haploid cape gooseberry lines from the Tibaitatá Research Center of the Colombian Corporation for Agricultural Research. Hybrids with potential uses in transformation processes or for fresh consumption were identified using Hierarchical Cluster (HC) and Principal Component Analysis (PCA) with 20 physical, physicochemical, compositional, and physiological fruit descriptors, obtained from four trials in the Andean region of southern Colombia. According to the PCA, three components represented 73.6% of the total variability: postharvest (37.5%), sensory and nutritional quality (21.3%) and cracking percentage (14.8%). Six conglomerates were identified. Groups two, four, and six had aptitude for fresh consumption because of the size of the berry, high vitamin C content, maturity index and low cracking levels. Group one showed aptitude for processing and fresh consumption. Groups three and five registered a high seed content, low maturity rates, and a high cracking percentage.

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Chemometric approach to quality characterization of milk-based kombucha beverages

Mljekarstvo ◽

10.15567/mljekarstvo.2021.0201 ◽

2021 ◽

Vol 71 (2) ◽

pp. 83-94

Author(s):

Jasmina Vitas ◽

Keyword(s):

Fatty Acids ◽

Milk Fat ◽

Unsaturated Fatty Acids ◽

Principal Component ◽

Unknown Origin ◽

Hierarchical Cluster ◽

Monounsaturated Fatty Acids ◽

Data Set ◽

Linear Discriminant

Milk-based kombucha beverages were obtained conducting kombucha lead fermentation of milk. In order to discriminate the analysed samples and to detect similarities or dissimilarities among them in the space of experimentally determined variables, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied. Linear discriminant analysis (LDA) was conducted on the raw data set in order to find a rule for allocating a new sample of unknown origin to the correct group of samples. In the space of the variables analysed by HCA, the dominant discriminating factor for the studied samples of kombucha beverages is the milk fat (MF) content, followed by total unsaturated fatty acids content (TUFA), monounsaturated fatty acids content (MUFA) and polyunsaturated fatty acids content (PUFA). The samples with 0.8 and 1.6% milk fat belong to the same cluster in the space of the analysed variables due to similarities in their AADPPH. It was determined by LDA that there was the biggest difference in quality between the groups of products with winter savoury and stinging nettle, while the highest similarity is between groups of products with wild thyme and peppermint regarding their pH values and antioxidant activity expressed as AADPPH.

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Comprehensive Investigation of Moringa oleifera from Different Regions by Simultaneous Determination of 11 Polyphenols Using UPLC-ESI-MS/MS

Molecules ◽

10.3390/molecules25030676 ◽

2020 ◽

Vol 25 (3) ◽

pp. 676 ◽

Cited By ~ 1

Author(s):

Yanqin Zhu ◽

Qinhong Yin ◽

Yaling Yang

Keyword(s):

Moringa Oleifera ◽

Principal Component ◽

Hierarchical Cluster ◽

Ultra Performance Liquid Chromatography ◽

Soil Environment ◽

Cultivation Conditions ◽

Esi Ms ◽

Analysis Methodology ◽

Polyphenol Profile

In this study, we develop and validate a simultaneous quantification of polyphenols method based on an ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) to adequately understand how different habitats influence the quality and profile of Moringa oleifera polyphenol. Furthermore, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to compare and discriminate 25 samples collected from different areas. A significant correlation was found between the polyphenol profile and the collection area. Significant differences in the polyphenol content of Moringa oleifera from different regions indicate that the genetic diversity of Moringa oleifera was relatively rich, possibly due to differences in cultivation conditions, climate, or soil environment resulting in the accumulation of different polyphenols. These observations provide a theoretical basis for subsequent Moringa oleifera germplasm selection and development research. Furthermore, the quantitative analysis methodology used to characterize the polyphenols may be used toward developing quality assessment and future pharmacodynamic investigations of Moringa oleifera.

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UPLC-ESI-MS/MS-Based Widely Targeted Metabolomics Analysis of Wood Metabolites in Teak (Tectona grandis)

Molecules ◽

10.3390/molecules25092189 ◽

2020 ◽

Vol 25 (9) ◽

pp. 2189 ◽

Cited By ~ 3

Author(s):

Guang Yang ◽

Kunnan Liang ◽

Zaizhi Zhou ◽

Xiyang Wang ◽

Guihua Huang

Keyword(s):

Secondary Metabolites ◽

Principal Component ◽

Tectona Grandis ◽

Chemical Components ◽

Heartwood Formation ◽

Primary Metabolites ◽

Esi Ms ◽

Teak Wood ◽

Widely Targeted Metabolomics ◽

Ultrahigh Performance Liquid Chromatography

The properties of teak wood, such as natural durability and beautiful color, are closely associated with wood extractives. In order to further understand the performance differences between teak heartwood and sapwood, we analyzed the chemical components of extractives from 12 wood samples using an ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS)-based metabolomics approach. In total, 691 metabolites were identified, and these were classified into 17 different categories. Clustering analysis and principal component analysis of metabolites showed that heartwood samples could be clearly separated from sapwood samples. Differential metabolite analysis revealed that the levels of primary metabolites, including carbohydrates, amino acids, lipids, and nucleotides, were significantly lower in the heartwood than in the sapwood. Conversely, many secondary metabolites, including flavonoids, phenylpropanoids, and quinones, had higher levels in the heartwood than in the sapwood. In addition, we detected 16 specifically expressed secondary metabolites in the heartwood, the presence of which may correlate with the durability and color of teak heartwood. Our study improves the understanding of differential metabolites between sapwood and heartwood of teak, and provides a reference for the study of heartwood formation.

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A Multi-Level Strategy Based on Metabolic and Molecular Genetic Approaches for the Characterization of Different Coptis Medicines Using HPLC-UV and RAD-seq Techniques

Molecules ◽

10.3390/molecules23123090 ◽

2018 ◽

Vol 23 (12) ◽

pp. 3090 ◽

Cited By ~ 3

Author(s):

Furong Zhong ◽

Chan Shen ◽

Luming Qi ◽

Yuntong Ma

Keyword(s):

High Performance ◽

Molecular Genetic ◽

Principal Component ◽

Hierarchical Cluster ◽

Chinese History ◽

Nucleotide Polymorphisms ◽

Additional Information ◽

Multi Level ◽

Coptis Herbs

Coptis plants (Ranunculaceae) to have played an important role in the prevention and treatment human diseases in Chinese history. In this study, a multi-level strategy based on metabolic and molecular genetic methods was performed for the characterization of four Coptis herbs (C. chinensis, C. deltoidea, C. omeiensis and C. teeta) using high performance liquid chromatography-ultraviolet (HPLC-UV) and restriction site-associated DNA sequencing (RAD-seq) techniques. Protoberberine alkaloids including berberine, palmatine, coptisine, epiberberine, columbamine, jatrorrhizine, magnoflorine and groenlandicine in rhizomes were identified and determined based on the HPLC-UV method. Among them, berberine was demonstrated as the most abundant compound in these plants. RAD-seq was applied to discover single nucleotide polymorphisms (SNPs) data. A total of 44,747,016 reads were generated and 2,443,407 SNPs were identified in regarding to four plants. Additionally, with respect to complicated metabolic and SNP data, multivariable statistical methods of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were successively applied to interpret the structure characteristics. The metabolic variation and genetic relationship among different Coptis plants were successfully illustrated based on data visualization. Summarily, this comprehensive strategy has been proven as a reliable and effective approach to characterize Coptis plants, which can provide additional information for their quality assessment.

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