scholarly journals 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 ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3090 ◽  
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.

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

Foods ◽  
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.

scholarly journals Discrimination of the Geographical Origin of the Lateral Roots of Aconitum carmichaelii Using the Fingerprint, Multicomponent Quantification, and Chemometric Methods

Molecules ◽  
2019 ◽  
Vol 24 (22) ◽  
pp. 4124 ◽  
Author(s):  
Lu-Lin Miao ◽  
Qin-Mei Zhou ◽  
Cheng Peng ◽  
Chun-Wang Meng ◽  
Xiao-Ya Wang ◽  
...  
Keyword(s):  
High Performance ◽  
Geographical Origin ◽  
Lateral Roots ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Similarity Analysis ◽  
Diterpenoid Alkaloids ◽  
Linear Discriminant ◽  
Hplc Fingerprint ◽  
Aconitum Carmichaelii

Fuzi is a well-known traditional Chinese medicine developed from the lateral roots of Aconitum carmichaelii Debx. It is rich in alkaloids that display a wide variety of bioactivities, and it has a strong cardiotoxicity and neurotoxicity. In order to discriminate the geographical origin and evaluate the quality of this medicine, a method based on high-performance liquid chromatography (HPLC) was developed for multicomponent quantification and chemical fingerprint analysis. The measured results of 32 batches of Fuzi from three different regions were evaluated by chemometric analysis, including similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), and linear discriminant analysis (LDA). The content of six representative alkaloids of Fuzi (benzoylmesaconine, benzoylhypaconine, benzoylaconine, mesaconitine, hypaconitine, and aconitine) were varied by geographical origin, and the content ratios of the benzoylmesaconine/mesaconitine and diester-type/monoester-type diterpenoid alkaloids may be potential traits for classifying the geographical origin of the medicine. In the HPLC fingerprint similarity analysis, the Fuzi from Jiangyou, Sichuan, was distinguished from the Fuzi from Butuo, Sichuan, and the Fuzi from Yunnan. Based on the HCA and PCA analyses of the content of the six representative alkaloids, all of the batches were classified into two categories, which were closely related to the plants’ geographical origins. The Fuzi samples from Jiangyou were placed into one category, while the Fuzi samples from Butuo and Yunnan were put into another category. The LDA analysis provided an efficient and satisfactory prediction model for differentiating the Fuzi samples from the above-mentioned three geographical origins. Thus, the content of the six representative alkaloids and the fingerprint similarity values were useful markers for differentiating the geographical origin of the Fuzi samples.

scholarly journals Determination and Chemometrics-Assisted Comparative Analysis of Active Components in Different Tissue of Rana chensinensis

Separations ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 164
Author(s):  
Jianqiu Zhang ◽  
Zhongyao Wang ◽  
Shihan Wang ◽  
Changli Zhang ◽  
Nan Li ◽  
...  
Keyword(s):  
High Performance ◽  
Rana Temporaria ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Comparative Approach ◽  
Active Components ◽  
Rana Chensinensis ◽  
Development And Utilization ◽  
Further Development ◽  
Different Tissues

In this study, the chemical composition of different tissues of Rana temporaria chensinensis David derived from the same individual was analyzed by comparative approach. First, pre-column derivatization combined with high performance liquid chromatography (HPLC) was established to determine the content of 1-methyl hydantoin in samples, which used S1–S5 samples. The results indicated that 1-methyl hydantoin was determined in Oviductus Ranae (OR), Rana chensinensis ovum (RCO), Rana chensinensis meat (RCM), and Rana chensinensis skin (RCS), except for Rana chensinensis bone (RCB). Moreover, the content of it in RCS was the highest. In addition, the contents of six polyunsaturated fatty acids (PUFAs) in different tissues of Rana chensinensis were measured by HPLC, including eicosapentaenoic acid (EPA), α-linolenic acid (ALA), docosahexaenoic acid (DHA), arachidonic acid (ARA), linoleic acid (LA) and oleic acid (OA). The results indicated that OR, RCO, RCM, RCS, and RCB all contained the above six PUFAs. With the aid of chemometrics methods, the results of principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) combined with the sequencing results of the total PUFAs content of each sample, showed that different tissues of Rana chensinensis could be divided into four categories, and the RCO sample was divided into one category because of the highest PUFAs content, which was a good source of PUFA. For comparison, OR and other tissue from the perspective of PUFAs, we also established OPLS-DA models of them. It could be found that the RCM was the most similar to the OR in the diversity and content of PUFAs. This study provided a theoretical basis for the further development and utilization of RCO, RCM, RCS, and RCB as by-products of OR.

scholarly journals Evaluation of the Influence of Sulfur-FumigatedPaeoniae Radix Albaon the Quality of Si Wu Tang by Chromatographic and Chemometric Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Ke Pei ◽  
Hao Cai ◽  
Yu Duan ◽  
Feng-Xian Qiao ◽  
Si-Cong Tu ◽  
...  
Keyword(s):  
High Performance ◽  
Chemical Constituents ◽  
Great Influence ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
High Performance Liquid Chromatographic ◽  
Chromatographic Fingerprint ◽  
Paeoniae Radix ◽  
Liquid Chromatographic

An accurate and reliable method of high-performance liquid chromatographic fingerprint combining with multi-ingredient determination was developed and validated to evaluate the influence of sulfur-fumigatedPaeoniae Radix Albaon the quality and chemical constituents of Si Wu Tang. Multivariate data analysis including hierarchical cluster analysis and principal component analysis, which integrated with high-performance liquid chromatographic fingerprint and multi-ingredient determination, was employed to evaluate Si Wu Tang in a more objective and scientific way. Interestingly, in this paper, a total of 37 and 36 peaks were marked as common peaks in ten batches of Si Wu Tang containing sun-driedPaeoniae Radix Albaand ten batches of Si Wu Tang containing sulfur-fumigatedPaeoniae Radix Alba, respectively, which indicated the changed fingerprint profile of Si Wu Tang when containing sulfur-fumigated herb. Furthermore, the results of simultaneous determination for multiple ingredients showed that the contents of albiflorin and paeoniflorin decreased significantly (P<0.01) and the contents of gallic acid andZ-ligustilide decreased to some extent at the same time when Si Wu Tang contained sulfur-fumigatedPaeoniae Radix Alba. Therefore, sulfur-fumigation processing may have great influence on the quality of Chinese herbal prescription.

Characterization of Physical and Chemical Evaluation on Six Apple Varieties

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.

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

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.

scholarly journals Chemometric approach to quality characterization of milk-based kombucha beverages

Mljekarstvo ◽  
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.

scholarly journals Volatile Characterization of Major Apricot Cultivars of Southern Xinjiang Region of China

2015 ◽  
Vol 140 (5) ◽  
pp. 466-471 ◽  
Author(s):  
Jian-rong Feng ◽  
Wan-peng Xi ◽  
Wen-hui Li ◽  
Hai-nan Liu ◽  
Xiao-fang Liu ◽  
...  
Keyword(s):  
High Performance ◽  
Solid Phase ◽  
Principal Component ◽  
Prunus Armeniaca ◽  
Least Squares Regression ◽  
Aroma Characteristics ◽  
Pca Method ◽  
Gas Chromatography Mass Spectroscopy ◽  
High Level

The characterization of aroma of the 14 main apricot (Prunus armeniaca L.) cultivars in Xinjiang was evaluated using high-performance solid-phase microextraction (HP-SPME) with gas chromatography-mass spectroscopy (GC-MS). A total of 208 volatiles that include 80 esters, 25 aldehydes, 15 terpenes, 21 ketones, 39 alcohols, 27 olefins, and 1 acid were identified from these cultivars. The compounds propyl acetate, 3-methyl-1-butanol acetate, (Z)-3-hexen-1-ol acetate, d-limonene, β-linalool, hexanal, hexyl acetate, butyl acetate, β-myrcene, ethyl butanoate, and β-cis-ocimene were the major compounds responsible for aroma in these cultivars. GC-MS results showed that Kuchexiaobaixing, Guoxiyuluke, and seven other cultivars were characterized by a high level of esters and were considered to be fruity apricot aroma. ‘Luotuohuang’ and ‘Heiyexing’ accumulate high levels of terpenes and exhibited an outstanding floral aroma. Higher levels of alcohols and aldehydes were observed in ‘Danxing’, ‘Sumaiti’, and ‘Kumaiti’. The latter are considered green aroma cultivars. These three types of cultivars with different aroma characteristics can be significantly differentiated by using the principal component analysis (PCA) method. The contributions of volatiles to the apricot aroma were assessed by using the partial least squares regression (PLSR) model. Esters, terpenes, and C6 components were shown to be responsible for the fruity, floral, and green character of fresh apricots, respectively.

scholarly journals Phytochemical Profiling and Fingerprint Analysis of Chinese Jujube (Ziziphus jujuba Mill.) Leaves of 66 Cultivars from Xinjiang Province

Molecules ◽  
2019 ◽  
Vol 24 (24) ◽  
pp. 4528 ◽  
Author(s):  
Lijun Song ◽  
Jie Zheng ◽  
Li Zhang ◽  
Shijuan Yan ◽  
Wenjie Huang ◽  
...  
Keyword(s):  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Dry Weight ◽  
Chinese Jujube ◽  
Uv Detector ◽  
Ziziphus Jujuba ◽  
The Difference ◽  
Phytochemical Profiles

Foliage of jujube (Ziziphus jujuba Mill.) as a byproduct of agriculture, is a traditional nutraceutical material in China. Previous studies have shown that it is a rich resource of polyphenols. However, information on its complete phenolic profile and the difference between cultivars is still limited. This study investigated and compared phytochemical profiles of leaves of 66 Chinese jujube cultivars. Forty-two compounds, including 22 flavonols, two flavanols, one flavanone, 13 derivatives of phenolic acids, three simple acids, and one unknown hexoside were identified/tentatively identified using high-performance liquid chromatography (HPLC) coupled with high-resolution mass spectrometry. Eight major flavonols were quantified by HPLC coupled with an ultraviolet (UV) detector. The contents of total flavonoids ranged from 2.6–25.1 mg/g dry weight (DW). Differences between cultivars were analyzed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). This study presents a systematic study on the phenolic compounds in Chinese jujube leaves of different cultivars.

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