Journal of Biosystems Engineering

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

DOI QR Code

Nondestructive Classification of Viable and Non-viable Radish (Raphanus sativus L) Seeds using Hyperspectral Reflectance Imaging

초분광 반사광 영상을 이용한 무(Raphanus sativus L) 종자의 발아와 불발아 비파괴 판별

  • Ahn, Chi Kook (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Mo, Chang Yeun (National Academy of Agricultural Science, Rural Development Administration) ;
  • Kang, Jum-Soon (Department of Horticultural Bioscence, Pusan National University) ;
  • Cho, Byoung-Kwan (Department of Biosystems Machinery Engineering, Chungnam National University)
  • 안치국 (충남대학교 바이오시스템기계공학과) ;
  • 모창연 (농촌진흥청 국립농업과학원 농업공학부) ;
  • 강점순 (부산대학교 원예생명과학과) ;
  • 조병관 (충남대학교 바이오시스템기계공학과)
  • Received : 2012.11.16
  • Accepted : 2012.12.05
  • Published : 2012.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

Keywords

References

  1. Ahn, C. K., B. K. Cho, J. S. Kang and K. J. Lee. 2012. Study on non-destructive sorting technique for lettuce (Lactuca sativa L) seed using Fourier transform near-infrared spectrometer. CNU Journal of Agricultural Science 39(1):111-116. (In Korean, with English abstract) https://doi.org/10.7744/cnujas.2012.39.1.111
  2. Anatoly, A. G., C. Buschmann and H. K. Lichtenthaler. 1999. The chlorophyll fluorescence ratio F735/F700 as an accurate measure of the chlorophyll content in plants. Journal of Remote Sensing Environment 69(3): 296-302. https://doi.org/10.1016/S0034-4257(99)00023-1
  3. Cho, B. K., Y. R. Chen and M. S. Kim. 2007. Multispectral detection of organic residues on poultry processing plant equipment based on hyperspectral reflectance imaging technique. Computers and Electronics in Agriculture 57:177-189. https://doi.org/10.1016/j.compag.2007.03.008
  4. Chung, H. I. and H. J. Kim. 2000. Near-infrared spectroscopy: principles. Journal of Korean Analytical Science & Technology 13(1):1A-14A. (In Korean)
  5. Ernst, L., J. Mocak, K. Serdt, B. Balla, T. Wenzl, D. Bandoniene, M. Gfrerer and S. Wagner. 2004. Chemometrical classification of pumpkin seed oils using UV-Vis, NIR and FTIR spectra. Journal of Biochemical and Biophysical Methods 61(1-2):95-106. https://doi.org/10.1016/j.jbbm.2004.04.007
  6. Fassio, A. and D. Cozzolino. 2004. non-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy. Journal of Industrial Crops and Products 20(3):321-329. https://doi.org/10.1016/j.indcrop.2003.11.004
  7. Henk, J., S. Rob Van der, F. Angela, G. Jaap, P. Van and J. B. Raoul. 1998. Chlorophyll fluorescence of brassica oleracea seeds as a non-destructive marker for seed maturity and seed performance. Journal of Seed Science Research 8:437-443.
  8. Kang, J. S., B. G. Son, Y. W. Choi, Y. J. Lee, W. H. Joo, C. S. Lim and Y. H. Park. 2009. Effects of dehydration methods and storage conditions on germinability of pelleted carrot seeds. Journal of Life Science 19(4):526-531. (In Korean, with English abstract) https://doi.org/10.5352/JLS.2009.19.4.526
  9. Kang, J. S. and I. S. Choi. 2006. Leakage of seed reserve nutrient in artificially aged pepper seeds and enhancement of seed vigor by priming. Journal of Life Science 16(2):352-356. (In Korean, with English abstract) https://doi.org/10.5352/JLS.2006.16.2.352
  10. Kang, W. S. 2008. Nondestructive determination of seed viability by optical methods. PhD diss. Daegu University, Department of Natural Resources.
  11. Kim, M. S., Y. R. Chen and P. M. Mehl, 2001, Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Transactions of the ASAE 44(3): 721-729.
  12. Lim, J. G., S. W. Kang, K. J. Lee, C. Y. Mo and J. Y. Son. 2011. Identification of foreign objects in soybeans using near-infrared spectroscopy. Journal of Food Engineering Progress 15(2):136-142. (In Korean, with English abstract)
  13. 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. Journal of Korean Horticultural Science and Technology 44(5):545-548.
  14. Min, T. G. and W. S. Kang. 2008(a). Nondestructive classification of viable and nonviable radish (Raphanus sativus L.) seeds using single near infrared spectroscopy. Journal of Horticulture environment and biotechnology 49(1):42-46.
  15. Min, T. G. and W. S. Kang. 2008(b). Nondestructive classification between normal and artificially aged corn (Zea mays L.) seeds using near infrared spectroscopy. Korean journal of Crop Science 53(3):314-319.
  16. 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(6):451-461. https://doi.org/10.1255/jnirs.966

Cited by

  1. Assessment of seed quality using non-destructive measurement techniques: a review vol.26, pp.04, 2016, https://doi.org/10.1017/S0960258516000234
  2. Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast vol.13, pp.12, 2013, https://doi.org/10.3390/s131013289
  3. Estimating Moisture Content of Cucumber Seedling Using Hyperspectral Imagery vol.41, pp.3, 2016, https://doi.org/10.5307/JBE.2016.41.3.273
  4. Characterization for Seeds of Korean Medicinal Plants Using Non-deductive Measurement Techniques vol.49, pp.5, 2015, https://doi.org/10.14397/jals.2015.49.5.67
  5. Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis vol.18, pp.4, 2018, https://doi.org/10.3390/s18041010