Isolation and Identification of Metabolites in Chinese Northeast Potato (Solanum tuberosum L.) Tubers Using Gas Chromatography-Mass Spectrometry

Zhang, Liyuan; Yu, Yingbo; Wang, Changyuan; Zhang, Dongjie

doi:10.1007/s12161-018-1336-5

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…| (2020) 10:17990 | https://doi.org/10.1038/s41598-020-73041-z www.nature.com/scientificreports/ resolution. For example, Zhang et al 6 employed gas chromatography-mass spectrometry (GC-MS) to isolate and identify metabolites of potato tubers in northeastern China. Feng et al 7 studied rice metabolites from different regions of the same province by using GC/MS technology.…”

Section: Scientific Reportsmentioning

confidence: 99%

“…Extraction and derivatization of maize metabolites. The extraction and derivatization were performed according to the method reported by Zhang et al 6 . Maize was crushed under the action of liquid nitrogen, sieved by a 100-mesh sieve, and stored at -80 °C for analysis.…”

Section: Apparatusmentioning

confidence: 99%

“…The dry residue was completely dissolved in 30 μL of 20 mg/mL -1 methoxyamine hydrochloride in pyridine and incubated for 60 min at 37 °C, and 30 μL BSTFA was subsequently added to react for 60 min at 70 °C. After derivatization, the resulting solution was analysed within 24 h. Please refer to 6 for sample processing methods.…”

Section: Apparatusmentioning

confidence: 99%

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Analysis of metabolites and metabolic pathways in three maize (Zea mays L.) varieties from the same origin using GC–MS

Zhang

2020

Sci Rep

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Metabolites of the Jinyu 88, Huanong 18, and Demeiya 9 maize varieties from the same origin were isolated and identified by GC–MS, and the specific metabolites and metabolic mechanisms of these three varieties of maize were preliminarily analysed and discussed. The metabolites were extracted with 80% methanol and derived with N,O-bis(trimethylsilyl)trifluoroacetamide. A total of 59 metabolites were identified. The specific metabolites of these three varieties of maize were identified. Four possible unknown-structure metabolites were hypothesized. The results showed that the specific metabolites of JY88 were only involved in fatty acid metabolism. The specific metabolites of HN18 were determined to be involved in fatty acid metabolism, glucose metabolism, and phytosterol metabolism. The specific metabolites of DM9 were observed to participate in glucose metabolism and fatty acid metabolism. The disease resistance of HN18 was higher than that of DM9, and its grain bulk density was higher than that of DM9. JY88 was determined to be significantly different from the other two varieties, and its appearance and disease resistance were worse than those of the other two varieties. The variety with the highest nutritional value was determined to be HN18, and the variety with the lowest nutritional value was JY88. This finding indicated that different maize varieties from the same origin had different metabolites and different metabolic mechanisms, which caused the three maize varieties to exhibit different characteristics and qualities.

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Section: Scientific Reportsmentioning

confidence: 99%

Section: Apparatusmentioning

confidence: 99%

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Analysis of metabolites and metabolic pathways in three maize (Zea mays L.) varieties from the same origin using GC–MS

Zhang

2020

Sci Rep

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“…Metabolomics, an important part of systems biology after genomics, transcriptomics, and proteomics, is based on high-throughput detection technology and multivariate data processing to reveal the changes in endogenous metabolites and their changes in organisms by studying the changes in small molecule metabolites (Li et al, 2021;Zhang et al, 2019Zhang et al, , 2020. The application of metabolomics in food is mainly to study the metabolic components of food.…”

Section: Introductionmentioning

confidence: 99%

Exploring the mechanism of browning of Rosa roxburghii juice based on nontargeted metabolomics

Zhu

et al. 2023

Journal of Food Science

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To explore the mechanism of Rosa roxburghii juice browning, this experiment was based on nontargeted metabolomics to study the effects of browning on the nutrition, flavor, metabolites, and metabolic pathways of R. roxburghii juice before and after storage. The results showed that the total soluble solids, superoxide dismutase (SOD), vitamin C (VC), total phenol, and total flavonoid of R. roxburghii juice decreased significantly before and after storage. The color difference value ∆E, browning index, and flavor and taste of R. roxburghii juice changed significantly (p < 0.05). A total of 541 metabolites were detected before and after browning of R. roxburghii juice by nontargeted metabolomics, including 435 differential metabolites, of which 221 were upregulated, and 214 were downregulated. The differential metabolites were mainly amino acids and peptides, carbohydrates, and carbohydrate conjugates. There were a total of 76 metabolic pathways enriched by differential metabolites, involving mainly galactose metabolism; alanine, aspartate and glutamate metabolism; and pantothenate and CoA biosynthesis. The experimental results showed that after browning of R. roxburghii juice, VC, total phenol, total flavonoid, and SOD activity were seriously lost, and the flavor deteriorated. The contribution of differential metabolites and metabolic pathways to the browning of R. roxburghii juice was sugar metabolism > amino acid metabolism > ascorbate and aldarate metabolism > phenols.

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Effects of storage on brown rice (Oryza sativa L.) metabolites, analyzed using gas chromatography and mass spectrometry

Wang

Feng

Zhang

et al. 2020

Food Science & Nutrition

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Metabolomic studies were carried out using gas chromatography and mass spectrometry (GC‐MS) on Daohuaxiang variety rice (Oryza sativa L.) from the Wuchang Geographical Indication Rice Protection Area in Heilongjiang Province, to investigate the effects of storage on brown rice metabolism. The data were subjected to principal component analysis (PCA), orthogonal partial least squares‐discriminant analysis (OPLS‐DA), and cluster analysis using software such as SIMCA. Analysis of the samples led to the identification of a total of 160 metabolites. No significant differences were found in the amount of metabolites before and after storage. A total of 31 differential metabolites were screened, and the changes in metabolite content showed a “reverse change” overall. Storage significantly changed the content of various metabolites in rice, with fatty acids impacted most significantly. Metabolic pathway analysis revealed that fatty acid biosynthesis is a key metabolic pathway in rice storage. The degradation of brown rice quality caused by storage is closely related to the composition and content of its metabolites, and that change in lipid content significantly affects brown rice quality during storage.

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Isolation and Identification of Metabolites in Chinese Northeast Potato (Solanum tuberosum L.) Tubers Using Gas Chromatography-Mass Spectrometry

Cited by 5 publications

References 17 publications

Analysis of metabolites and metabolic pathways in three maize (Zea mays L.) varieties from the same origin using GC–MS

Analysis of metabolites and metabolic pathways in three maize (Zea mays L.) varieties from the same origin using GC–MS

Exploring the mechanism of browning of Rosa roxburghii juice based on nontargeted metabolomics

Effects of storage on brown rice (Oryza sativa L.) metabolites, analyzed using gas chromatography and mass spectrometry

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