Journal of Biosystems Engineering

Korean Society for Agricultural Machinery (한국농업기계학회)
권호 표지
DOI QR코드

DOI QR Code

Germination Prediction of Cucumber (cucumis sativus) Seed using Raman Spectroscopy

라만분광을 이용한 오이 종자의 발아예측

  • Mo, Changyeun (National Academy of Agricultural Science, Rural Development Administration) ;
  • Kang, Sukwon (National Academy of Agricultural Science, Rural Development Administration) ;
  • Lee, Kangjin (National Academy of Agricultural Science, Rural Development Administration) ;
  • Kim, Giyoung (National Academy of Agricultural Science, Rural Development Administration) ;
  • Cho, Byoung-Kwan (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Lim, Jong-Guk (National Academy of Agricultural Science, Rural Development Administration) ;
  • Lee, Ho-Sun (National Academy of Agricultural Science, Rural Development Administration) ;
  • Park, Jongryul (National Academy of Agricultural Science, Rural Development Administration)
  • 모창연 (농촌진흥청 국립농업과학원) ;
  • 강석원 (농촌진흥청 국립농업과학원) ;
  • 이강진 (농촌진흥청 국립농업과학원) ;
  • 김기영 (농촌진흥청 국립농업과학원) ;
  • 조병관 (충남대학교 바이오시스템기계공학과) ;
  • 임종국 (농촌진흥청 국립농업과학원) ;
  • 이호선 (농촌진흥청 국립농업과학원) ;
  • 박종률 (농촌진흥청 국립농업과학원)
  • Received : 2012.11.05
  • Accepted : 2012.12.17
  • Published : 2012.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: The objective of this research was to select high quality cucumber (cucumis sativus) seed by classifying into viable or non-viable one using Raman spectroscopy. Method: Both transmission and back-scattering Raman spectra of viable and non-viable seeds in the range from $150cm^{-1}$ to $1890cm^{-1}$ were collected with a laser illumination. Results: The Raman spectra of cucumber seed showed Raman peaks with features of polyunsaturated fatty acids. The partial least squares-discriminant analysis (PLS-DA) to predict viable seeds was developed with measured transmission and backscattering spectra with Raman spectroscopy and germination test results. Various types of spectra pretreatment were investigated to develop the classification models. The results of developed PLS-DA models using the transmission spectra with mean normalization or range normalization, and back-scattering spectra with mean normalization treatment or baseline correction showed 100% discrimination accuracy. Conclusions: These results showed that Raman spectroscopy technologies can be used to select the high quality cucumber seeds.

Keywords

References

  1. Alexandrakis, D., G. Downey and A.G.M. Scannell. 2008. Detection and identification of bacteriain an isolated system with near-infrared spectroscopy and multivariate analysis. Journal of Agricultural and Food Chemistry 56:3431-3437. https://doi.org/10.1021/jf073407x
  2. Chad, A.L. and M.J. Anita. 2003. Automated method for subtraction of fluorescence from biological Raman spectra. Applied Spectroscopy 57:1363-1367. https://doi.org/10.1366/000370203322554518
  3. Da Silva, C.E., P. Vandenabeele, H.G. Edwards and L.F. de Oliveira. 2008. NIR-FT-Raman spectroscopic analytical characterization of the fruits, seeds, and phytotherapeutic oils from rosehips. Analytical and Bioanalytical Chemistry 392(7):1489-1496. https://doi.org/10.1007/s00216-008-2459-0
  4. ISTA. 2008. International rules for seed testing. edition 2008. International Seed Testing Association.
  5. Kim, M., H. Chung, Y. Woo and M. Kemper. 2006. New reliable Raman collection system using the wide area illumination (WAI) scheme combined with the synchronous intensity correction standard for the analysis of pharmaceutical tablets. Analytica Chimica Acta 579:209-216. https://doi.org/10.1016/j.aca.2006.07.036
  6. Koostra, P.T. and J.F. Harrington. 1969. Biochemical Effects of Age on Membranal Lipids of Cucumis-Sativus-D Seed. The International Seed Testing Association 34:329-340.
  7. Min, T.G. and W.S. Kang. 2003. Nondestructive separation of viable and non-viable gourd (Lagenaria siceraria) seeds using single seed near infrared reflectance spectroscopy. Korean Society for Horticultural Science 44:545-548.
  8. Reitzenstein, S., P. Rösch, M.A. Strehle, D. Berg, M. Baranska, H. Schulz, E. Rudloff and J. Popp. 2007. Nondestructive analysis of single rapeseeds by means of Raman spectroscopy. Journal of Raman Spectroscopy 38(3):301-308. https://doi.org/10.1002/jrs.1643
  9. Schulz, H., M. Baranska and R. Baranski. 2005. Potential of NIR-FT-Raman Spectroscopy in Natural Carotenoid Analysis. Biopolymers 77(4):212-221. https://doi.org/10.1002/bip.20215
  10. Shetty, N., T.G. Min, M.H. Olesen and B. Boelt. 2011. Optimal sample size for predicting viability of cabbage and radish seeds based on near infrared spectra of single seeds. Journal of Near Infrared Spectroscopy 19:451-461. https://doi.org/10.1255/jnirs.966
  11. Shin K., H. Chung and C.W. Kwak. 2012. Transmission Raman measurement directly through packed corn kernels to improve sample representation and accuracy of compositional analysis. Analyst 137:3690-3696. https://doi.org/10.1039/c2an35443h

Cited by

  1. Non-Destructive Quality Evaluation of Pepper (Capsicum annuum L.) Seeds Using LED-Induced Hyperspectral Reflectance Imaging vol.14, pp.12, 2014, https://doi.org/10.3390/s140407489
  2. Assessment of seed quality using non-destructive measurement techniques: a review vol.26, pp.04, 2016, https://doi.org/10.1017/S0960258516000234
  3. Near-infrared hyperspectral imaging system coupled with multivariate methods to predict viability and vigor in muskmelon seeds vol.229, 2016, https://doi.org/10.1016/j.snb.2016.02.015