Research Article | OPEN ACCESS
Analysis on Nutrients Change of Fresh Ginger after Storage
1, 2Xingcui Wang, 2Bili Cao, 1Qiqin Xue, 1Yong-guang Liu and 1Ning Qiao
1Weifang University of Science and Technology, China
2State Key Laboratory of Crop Biology, Ministry of Agriculture, Key Laboratory of Horticultural Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, China
Advance Journal of Food Science and Technology 2015 3:171-176
Received: February ‎3, ‎2015 | Accepted: March ‎1, ‎2015 | Published: August 10, 2015
Abstract
In order to determine the composition of ginger and fresh ginger and efficacy differences, this study uses gas chromatography-mass spectrometry to identify the ginger and fresh ginger supercritical CO,sub>2 extract of the chemical composition and relative content. The results showed that the extraction rate of ginger and fresh ginger oleoresin is respectively 5.15±0.12% and 4.67±0.15%, the chemical composition of both contained basically the same, mainly zingiberene α-, β-half times the water Qinene, β-myrrhene, α-farnesene, α-curcumene, 6-gingerol, 6 zingiberene phenol and decomposition zingerone etc., but significant differences relative content. In the aroma of terpene compounds, ginger relative amount of the compound 1, 8-cineole, β- fragrant small chestnut, citral, geraniol, geranyl acetate and α-zingiberene other significant lower than fresh ginger and γ-Selinene and large myrcene D detected only in fresh ginger, ginger and the relative content of α-curcumene significantly higher than fresh ginger. The relative amounts of the total ginger gingerol compounds than fresh ginger high of 7.86%, in particular 6-and 10- zingiberene relative content of phenol phenol zingiberene high 15.49 and 30.51%, respectively, compared with fresh ginger.
Keywords:
Fresh ginger, nutrients change, storage,
References
-
Aly, M., 2005. Survey on multiclass classification methods. Technical Report, Caltech, USA.
-
Bentlin, F.R.S., C.M.M.D. Santos, E.M.M. Flores and D. Pozebon, 2012. Lanthanides determination in red wine using ultrasound assisted extraction, flow injection, aerosol desolvation and ICP-MS. Anal. Chim. Acta, 710: 33-39.
CrossRef PMid:22123109 -
Burin, V.M., L.L.F. Costa, J.P. Rosier and M.T. Bordignon-Luiz, 2011. Cabernet sauvignon wines from twom different clones, characterization and evolution during bottle ageing. LWT-Food Sci. Technol., 44: 1931-1938.
-
Chen, S.J. and C.L. Hwang, 1992. Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin.
CrossRef -
Cruz-Ramiaírez, M., J.C. Fernández, J. Sánchez-Monedero, F. Fernández-Navarro, C. Hervá s-Martínez, P.A. Gutiérrez and M.T. Lamata, 2010. Ensemble determination using the TOPSIS decision support system in multi-objective evolutionary neural network classi?ers. Proceeding of the 10th International Conference on Intelligent Systems Design and Applications. Cario, Egypt, pp: 513-518.
CrossRef -
He, Y., X.L. Li and X.F. Deng, 2007. Discrimination of varieties of tea using near infrared spectroscopy by principal component analysis and BP model. J. Food Eng., 79: 1238-1242.
CrossRef -
Hernanz, D., A.F. Recámales, M.L. González-Miret, M.J. Gómez-Míguez, I.M. Vicario and F.J. Heredia, 2007. Phenolic composition of white wines with a prefermentative maceration at experimental and industrial scale. J. Food Eng., 80(1): 327-335.
CrossRef -
Hwang, C.L. and K. Yoon, 1981. Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin.
CrossRef PMCid:PMC1214490 -
Jiang, L., J. Xue, Y.J. Wang, Q. Lin and L.J. Du, 2008. Application of SNIF-NMR technique (site-specific natural isotope fractionation-nuclear magnetic resonance) in grape wine quality evaluation. Liquor-Making Sci. Technol., 169: 60-62.
-
Jin, W.Q., 2005. Fuzzy classification based on fuzzy association rule mining. Thesis, NC State University, Raleigh.
-
Kavuri, N.C. and M. Kundu, 2011. ART1 network: Application in wine classification. Int. J. Chem. Eng. Appl., 2(3): 189-195.
CrossRef -
Kruzlicova, D., J. Mocak, B. Balla, J. Petka, M. Farkova and J. Havel, 2009. Classification of slovak white wines using artificial neural networks and discriminant techniques. Food Chem., 112(4): 1046-1052.
CrossRef -
Lawless, H.T. and H. Heymann, 1999. Sensory Evaluation of Food: Principles and Practices. Springer-Verlag, Berlin.
CrossRef PMCid:PMC1723178 -
Li, X.X., K.S. Wang, L.W. Liu, J. Xin, H.R. Yang and C.Y. Gao, 2011. Application of the entropy weights and TOPSIS method in safety evaluation of coal mines. Proc. Eng., 26: 2085-2091.
CrossRef -
Osorio, D., J.R. Pérez-Correa, E. Agosin and M. Cabrera, 2008. Soft-sensor for on-line estimation of ethanol concentrations in wine stills. J. Food Eng., 87(4): 571-577.
CrossRef -
Römisch, U., D. Vandev and K. Zur, 2006. Application of interactive regularized discriminant analysis to wine data. Aust. J. Stat., 35(1): 45-55.
-
Shoemaker, P.A., M.J. Carlin and R.L. Shimabukuro, 1991. Back propagation learning with trinary quantization of weights updates. Neural Networks, 4(2): 231-241.
CrossRef -
Sun, Y.F., Z.S. Liang, C.J. Shan, H. Viernstein and F. Unger, 2011. Comprehensive evaluation of natural antioxidants and antioxidant potentials in Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H. F. Chou fruits based on geographical origin by TOPSIS method. Food Chem., 124(4): 1612-1619.
CrossRef -
Xie, Z.H., Y. Zhang and C. Jin, 2012. Prediction of coal spontaneous combustion in goaf based on the BP neural network. Proc. Eng., 43: 88-92.
CrossRef -
Yoon, K.P. and C.L. Hwang, 1995. Multiple Attribute Decision Making. Sage Publication, Thousand Oaks, CA.
-
Zhang, Y.L., X.D. Liu and X.Y. Wang, 2009. A novel weighted fuzzy clustering analysis based on AFS theory. Proceeding of the 9th International Conference on Hybrid Intelligent Systems. Shenyang, China, 3: 346-350.
CrossRef
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
|
ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
|
Information |
|
|
|
Sales & Services |
|
|
|