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[국내논문] Discrimination of Floral Scents and Metabolites in Cut Flowers of Peony (Paeonia lactiflora Pall.) Cultivars 원문보기

韓國資源植物學會誌 = Korean journal of plant resources, v.31 no.6, 2018년, pp.641 - 651  

Ahn, Myung Suk (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Park, Pue Hee (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Kwon, Young Nam (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Mekapogu, Manjulatha (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Kim, Suk Weon (Biological Resources Center, Korea Research Institute of Bioscience and Biotechnology) ,  Jie, Eun Yee (Biological Resources Center, Korea Research Institute of Bioscience and Biotechnology) ,  Jeong, Jae Ah (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Park, Jong Taek (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA) ,  Kwon, Oh Keun (Floriculture Research Division, National Institute of Horticultural and Herbal Science, RDA)

Abstract AI-Helper 아이콘AI-Helper

Floral scents and metabolites from cut flowers of 14 peony cultivars (Paeonia lactiflora Pall.) were analyzed to discriminate different cultivars and to compare the Korean cultivar with the other cut peonies imported to Korea using electronic nose (E-nose) and Fourier transform infrared (FT-IR) spec...

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표/그림 (7)

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제안 방법

  • The major objectives of this study are to provide the basic analysis of floral scent and metabolic profiles of herbaceous peony cut flowers for cosmetics material industry and to analyze the relationship between Korean cultivar ‘Taebaek’ and imported commercial cut peony to provide preliminary data for peony breeding.
  • An Alpha MOS FOX-2000 E-nose (Alpha MOS, Toulouse, France) equipped with 6 metal oxide sensors (Alpha MOS, Toulouse, France) was used to analyze floral scent. Based on sensor coating materials, the metal oxide sensors of Alpha MOS FOX-2000 were the P and T sensors as n-type semiconductors.
  • org). After a data preprocessing, spectral data was then subjected to multivariate analysis.
  • , 2016). Euclidean distances between centroid of three replicates of flower sample and the control were extracted using Alpha Soft (Version 12.45.) and was used to compare the relative intensities among the floral scents of 14 different peony cultivars. The distance analysis showed that all cultivars have a different relative intensity of scent according to the sensory evaluation (Fig.
  • The interpretation of the data from the E-nose was accomplished using multivariate statistical technique, including PCA and DFA. Also, hierarchical clustering analysis (HCA) was performed to statistically analyze the comprehensive relationship contained in PCA and DFA score data from each sample.

대상 데이터

  • Cut flowers of different peony cultivars used in this study were collected from the open field of World Flower Company farm, Jincheon, Korea (36°54'23.7"N 127°28'23.4"E) in May 2018.

데이터처리

  • To find more significant FT-IR variables for metabolic variation among the 14 cut peony cultivars, PCA loading values were also examined. Also, HCA dendrogram was performed to statistically analyze the comprehensive relationship contained in PCA and PLSDA score data from each sample using R program.

이론/모형

  • 1). PCA was conducted according to the non-linear iterative partial least squares (NIPALS) algorithm (Wold, 1966). PLS-DA was also conducted using R program for more discrete clustering of metabolic variation in flowers of different peony cultivars according to a supervised pattern recognition method maximizing the separation among samples.
  • , 2016). The interpretation of the data from the E-nose was accomplished using multivariate statistical technique, including PCA and DFA. Also, hierarchical clustering analysis (HCA) was performed to statistically analyze the comprehensive relationship contained in PCA and DFA score data from each sample.
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참고문헌 (20)

  1. Ali, A., Y.M. Choi, D.Y. Hyun, S. Lee, J.H. Kim, S. Oh and M.C. Lee. 2017. Development of EST-SSRs and assessment of genetic diversity in little millet (Panicum sumatrense) germplasm. Korean J. Plant Res. 30(3):287-297. 

  2. Abbey, M. 2015. Paeonia spp. production and future developments. The University of Minnesota Digital Conservancy 1-23. University of Minnesota, Minnesota, USA. 

  3. Ahn, M.S., S.R. Min, E.Y. Jie, E.J. So, S.Y. Choi, B.C. Moon, Y.M. Kang, S.Y. Park and S.W. Kim. 2015. Rapid comparison of metabolic equivalence of standard medicinal parts from medicinal plants and their in vitro-generated adventitious roots using FT-IR spectroscopy. J. Plant Biotechnol. 42:257-264 (in Korean). 

  4. Alpha, M.O.S. 1998. Intelligent electronic nose. FOX User Manual. 2nd ed. SA, France. 1:25-31. 

  5. Carvalho, L.C., C.L.M. Morais, K.M.G. Lima, G.W.P. Leite, G.S. Oliveira, I.P. Casagrande, J.P.S. Neto and G.H.A. Teixeira. 2017. Using intact nuts and near infrared spectroscopy to classify macadamia cultivars. Food Anal. Methods 11(7):1857-1866. 

  6. He, D.Y. and S.M. Dai. 2011. Anti-inflammatory and immunomodulatory effects of Paeonia Lactiflora Pall., a traditional Chinese herbal medicine. Front Pharmacol. 2(10):1-5. 

  7. Kong, J. and Y.U. Shaoning. 2007. Fourier transform infrared spectroscopic analysis of protein secondary structures. Acta Bioch. Bioph. Sin. 39(8):549-559. 

  8. Kamenetsky, R. and J. Dole. 2012. Herbaceous peony (paeonia): genetics, physiology and cut flower production. Floricultural Research Organization 6:62-77. 

  9. Kim, S.Y., H.R. An, P.M. Park, Y.S. Baek, O.K. Kwon, S.Y. Park and P.H. Park. 2016. Analysis of floral scent patterns in flowering stages and floral organs of Maxillaria using and electronic nose. Flower Res. J. 24(3):171-180. 

  10. Kim, S.J., S.K. Lee and K.S. Kim. 2012. Current research trend of postharvest technology for chrysanthemum. Korean J. Plant Res. 25(1):156-168 (in Korean). 

  11. Kong, W., C. Zhang, F. Liu, P. Nie and Y. He. 2013. Rice seed cultivar identification using near-infrared hyperspectral imaging and multivariate data analysis. Sensors 13:8916-8927. 

  12. Lee, B., Y.W. Shin, E.A. Bae, S.J. Han, J.S. Kim, S.S. Kang and D.H. Kim. 2008. Antiallergic effect of the root of Paeonia lactiflora and its constituents paeoniflorin and paeonol. Arch. Pharm. Res. 31:445-450. 

  13. Ministry of Agriculture, Food and Rural Affairs (MAFRA). 2017. Production Performance of Industrial Crops. MAFRA press, Sejong, Korea. pp. 7-18 (in Korean). 

  14. Myung, N.Y. 2018. The improving effect of Paeoniae Radix on dextran sulfate sodium-induced colitis in mice. Korean J. Plant Res. 31(4):275-282. 

  15. Parker, F.S. 1983. Applications of Infrared, Raman and Resonance Raman Spectroscopy in Biochemistry. Plenum Press, New York, NY (USA). p. 527 

  16. Surewicz, W.K. and H.H. Mantsch. 1988. New insight into protein secondary structure from resolution-enhanced infrared spectra. Biochim. Biophys. Acta. 952:115-130. 

  17. Wold, H. 1966. Estimation of principal components and related models by iterative least squares: In Krishnaiah, K.R. (ed.), Multivariate Analysis, Academic Press, New York, NY (USA). pp. 391-420. 

  18. Xia, L.L., Q.J. Zhu and Y.G. Wu. 2017. Hepatoprotective effect of peony total glucosides and the underlying mechanisms in diabetic rats. Pharm. Biol. 55(1):2178-2187. 

  19. Zheng, Y.Q., W. Wei, L. Zhu and J.X. Liu. 2007. Effects and mechanisms of paeoniflorin, a bioactive glucoside from paeony root, on adjuvant arthritis in rats. Inflamm. Res. 56:182-188. 

  20. Zimmermann, B. and A. Kohler. 2014. Infrared spectroscopy of pollen identifies plant species and genus as well as environmental conditions. PLoS One 9(4):e95417. 

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