133 related articles for article (PubMed ID: 28762322)
1. Optimized Mass Spectrometry-Based Metabolite Extraction and Analysis for the Geographical Discrimination of White Rice (
Lim DK; Long NP; Mo C; Dong Z; Lim J; Kwon SW
J AOAC Int; 2018 Mar; 101(2):498-506. PubMed ID: 28762322
[TBL] [Abstract][Full Text] [Related]
2. The integration of multi-platform MS-based metabolomics and multivariate analysis for the geographical origin discrimination of Oryza sativa L.
Lim DK; Mo C; Lee JH; Long NP; Dong Z; Li J; Lim J; Kwon SW
J Food Drug Anal; 2018 Apr; 26(2):769-777. PubMed ID: 29567248
[TBL] [Abstract][Full Text] [Related]
3. Non-destructive profiling of volatile organic compounds using HS-SPME/GC-MS and its application for the geographical discrimination of white rice.
Lim DK; Mo C; Lee DK; Long NP; Lim J; Kwon SW
J Food Drug Anal; 2018 Jan; 26(1):260-267. PubMed ID: 29389563
[TBL] [Abstract][Full Text] [Related]
4. Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.
Long NP; Lim DK; Mo C; Kim G; Kwon SW
Sci Rep; 2017 Aug; 7(1):8552. PubMed ID: 28819110
[TBL] [Abstract][Full Text] [Related]
5. Discrimination of genotype and geographical origin of black rice grown in Brazil by LC-MS analysis of phenolics.
Dittgen CL; Hoffmann JF; Chaves FC; Rombaldi CV; Filho JMC; Vanier NL
Food Chem; 2019 Aug; 288():297-305. PubMed ID: 30902297
[TBL] [Abstract][Full Text] [Related]
6. Determination of starch lysophospholipids in rice using liquid chromatography-mass spectrometry (LC-MS).
Liu L; Tong C; Bao J; Waters DL; Rose TJ; King GJ
J Agric Food Chem; 2014 Jul; 62(28):6600-7. PubMed ID: 24953871
[TBL] [Abstract][Full Text] [Related]
7. Metabolomic fingerprinting of volatile organic compounds for the geographical discrimination of rice samples from China, Vietnam and India.
Ch R; Chevallier O; McCarron P; McGrath TF; Wu D; Nguyen Doan Duy L; Kapil AP; McBride M; Elliott CT
Food Chem; 2021 Jan; 334():127553. PubMed ID: 32688177
[TBL] [Abstract][Full Text] [Related]
8. Metabolite profiling of the short-term responses of rice leaves (Oryza sativa cv. Ilmi) cultivated under different LED lights and its correlations with antioxidant activities.
Jung ES; Lee S; Lim SH; Ha SH; Liu KH; Lee CH
Plant Sci; 2013 Sep; 210():61-9. PubMed ID: 23849114
[TBL] [Abstract][Full Text] [Related]
9. Simultaneous Profiling of Lysoglycerophospholipids in Rice (Oryza sativa L.) Using Direct Infusion-Tandem Mass Spectrometry with Multiple Reaction Monitoring.
Lim DK; Mo C; Long NP; Kim G; Kwon SW
J Agric Food Chem; 2017 Mar; 65(12):2628-2634. PubMed ID: 28245645
[TBL] [Abstract][Full Text] [Related]
10. Metabolic profiling of Chinese tobacco leaf of different geographical origins by GC-MS.
Zhang L; Wang X; Guo J; Xia Q; Zhao G; Zhou H; Xie F
J Agric Food Chem; 2013 Mar; 61(11):2597-605. PubMed ID: 23441877
[TBL] [Abstract][Full Text] [Related]
11. [Development of a gas chromatography-mass spectrometry method for the metabolomic study of rice (Oryza sativa L.) grain].
Zhou J; Wang S; Chang Y; Zhao Y; Lu X; Zhao C; Xu G
Se Pu; 2012 Oct; 30(10):1037-42. PubMed ID: 23383493
[TBL] [Abstract][Full Text] [Related]
12. Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification.
Yang P; Zhou R; Zhang W; Tang S; Hao Z; Li X; Lu Y; Zeng X
Appl Opt; 2018 Oct; 57(28):8297-8302. PubMed ID: 30461781
[TBL] [Abstract][Full Text] [Related]
13. Compound-specific δ
Chung IM; Kim JK; An YJ; Kwon C; Kim SY; Yang YJ; Yarnes CT; Chi HY; Kim SH
Food Chem; 2019 Jun; 283():305-314. PubMed ID: 30722876
[TBL] [Abstract][Full Text] [Related]
14. Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.
Lim DK; Long NP; Mo C; Dong Z; Cui L; Kim G; Kwon SW
Food Res Int; 2017 Oct; 100(Pt 1):814-821. PubMed ID: 28873754
[TBL] [Abstract][Full Text] [Related]
15. Effects of storage on brown rice (
Wang C; Feng Y; Zhang S; Fu T; Sheng Y; Zhang Y; Jiang Y; Yu M; Zhang L; Zhang D
Food Sci Nutr; 2020 Jun; 8(6):2882-2894. PubMed ID: 32566206
[TBL] [Abstract][Full Text] [Related]
16. Comparing two metabolic profiling approaches (liquid chromatography and gas chromatography coupled to mass spectrometry) for extra-virgin olive oil phenolic compounds analysis: A botanical classification perspective.
Bajoub A; Pacchiarotta T; Hurtado-Fernández E; Olmo-García L; García-Villalba R; Fernández-Gutiérrez A; Mayboroda OA; Carrasco-Pancorbo A
J Chromatogr A; 2016 Jan; 1428():267-79. PubMed ID: 26554295
[TBL] [Abstract][Full Text] [Related]
17. Authenticity of rice (Oryza sativa L.) geographical origin based on analysis of C, N, O and S stable isotope ratios: a preliminary case report in Korea, China and Philippine.
Chung IM; Kim JK; Prabakaran M; Yang JH; Kim SH
J Sci Food Agric; 2016 May; 96(7):2433-9. PubMed ID: 26243037
[TBL] [Abstract][Full Text] [Related]
18. A rapid and reliable method for discriminating rice products from different regions using MCX-based solid-phase extraction and DI-MS/MS-based metabolomics approach.
Lim DK; Mo C; Long NP; Lim J; Kwon SW
J Chromatogr B Analyt Technol Biomed Life Sci; 2017 Sep; 1061-1062():185-192. PubMed ID: 28743095
[TBL] [Abstract][Full Text] [Related]
19. Fingerprinting of Volatile Organic Compounds for the Geographical Discrimination of Rice Samples from Northeast China.
Asimi S; Ren X; Zhang M; Li S; Guan L; Wang Z; Liang S; Wang Z
Foods; 2022 Jun; 11(12):. PubMed ID: 35741894
[TBL] [Abstract][Full Text] [Related]
20. Non-essential element concentrations in brown grain rice: Assessment by advanced data mining techniques.
Villafañe R; Hidalgo M; Piccoli A; Marchevsky E; Pellerano R
Environ Sci Pollut Res Int; 2018 Aug; 25(22):21362-21367. PubMed ID: 28424959
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
