Skip to main content
Log in

Separating clods and stones from potato tubers based on color and shape

  • Original Paper
  • Published:
Journal of Food Measurement and Characterization Aims and scope Submit manuscript

Abstract

The separation of clods and stones from the harvested potato tuber has always been a prevalent problem in the world. However, the precision of sorting was restricted by the potato tubers covered with mud on the surface. This paper studied methods of separating clods and stones from potato tubers based on shape and color. An image acquisition system consisted of a light source, a camera, a computer was built for this experiment. The color features were extracted from the components of RGB and HSV images by the two-dimensional Haar Wavelet Transform and put into SVM (support vector machine) to classify the object after principal component analysis. The shape features which contained the original contour and corrected contour described by the mathematical statistical methods was extracted and used for separation by SVM. The experimental result showed that it was effective to separate clods and stones from potato tubers based on the extracted color and shape features, respectively. The combination of color and shape features could increase the accuracy rate of classification, especially for potato tubers and clods. The overall accuracy rate was 97.8% in 2016 and 98.1% in 2017. It was evident that the color features dominate in the classification model. Shape features based on the correcting image showed positive effect in classification. It turned out that the combination of shape and color features can obviously improve classification performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. G.M. Rauscher, C.D. Smart, I. Simko, M. Bonierbale, H. Mayton, A. Greenland, W.E. Fry, Theor. Appl. Genet. 112, 674 (2006)

    Article  CAS  PubMed  Google Scholar 

  2. M. Urooj, U. Arif, A. Intikhab, World J. Biol. Biotechnol. 1, 33 (2016)

    Article  Google Scholar 

  3. A. Bojanowski, T.J. Avis, S. Pelletier, R.J. Tweddell, Postharvest Biol. Technol. 84, 99 (2013)

    Article  CAS  Google Scholar 

  4. A. Hosainpour, M.H. Komarizade, A. Mahmoudi, M.G. Shayesteh, Expert. Syst. Appl. 38, 12101 (2011)

    Article  Google Scholar 

  5. Y. Gao, J. Geng, X. Rao, Y. Ying, Sensors 16, 1734 (2016)

    Article  Google Scholar 

  6. D.J. Campbell, J. Agric. Eng. Res. 27, 373 (1982)

    Article  Google Scholar 

  7. M.B. Mcgechan, J. Agric. Eng. Res. 22, 229 (1977)

    Article  Google Scholar 

  8. M.B. Mcgechan, J. Agric. Eng. Res. 25, 345 (1980)

    Article  Google Scholar 

  9. D.C. Mcrae, J. Agric. Eng. Res. 31, 115 (1985)

    Article  Google Scholar 

  10. R. Feller, E. Margolin, A. Zacharin, H. Pasternak, Trans. ASABE 28, 1019 (1985)

    Article  Google Scholar 

  11. S. Ganmor, A. Zacharin, N. Galili, R. Feller, E. Margolin, Trans. ASABE 29, 1526 (1986)

    Article  Google Scholar 

  12. M. Shyam, V. Singh, R. Singh, AMA Agric. Mech. Asia Africa Latin Am. 15, 885 (1990)

    Google Scholar 

  13. S. Riyadi, A.A.A. Rahni, M.M. Mustafa, in Conference on Research & Development (2008), p. 1

  14. A. Peirs, N. Scheerlinck, K. Touchant, B.M. Nicolaı̈, Bioprocess Eng. 81, 305 (2002)

    Google Scholar 

  15. N. Berardo, V. Pisacane, P. Battilani, A. Scandolara, A. Pietri, A. Marocco, J. Agric. Food Chem. 53, 8128 (2005)

    Article  CAS  PubMed  Google Scholar 

  16. H. Cen, Y. He, Trends Food Sci. Technol. 18, 72 (2007)

    Article  CAS  Google Scholar 

  17. K.H. Choi, J.A. Abbott, B. Park, C.H. Choi, K.J. Lee, Trans. ASABE 46, 1721 (2003)

    Article  Google Scholar 

  18. A.G. Story, G.S.V. Raghavan, Trans. ASAE 16, 0304 (1976)

    Article  Google Scholar 

  19. S. Gogineni, J.G. White, J.A. Thomasson, P.G. Thompson, J.R. Wooten, M. Shankle, Trans. ASABE (2002). https://doi.org/10.13031/2013.10586

    Article  Google Scholar 

  20. A. Almallahi, T. Kataoka, H. Okamoto, Bioprocess Eng. 100, 329 (2008)

    Google Scholar 

  21. A.A. Al-Mallahi, T. Kataoka, O. Hiroshi, Trans. ASABE (2008). https://doi.org/10.13031/2013.24841

    Article  Google Scholar 

  22. A. Almallahi, T. Kataoka, H. Okamoto, Y. Shibata, Bioprocess Eng. 105, 257 (2010)

    Google Scholar 

  23. J. Wu, Z. Li, Y. Xu, C. Ji, Y. Li, X. Xing, in IEEE International Conference on Dependable, Autonomic and Secure Computing (2014), p. 338

  24. H.B. Kekr, S. Natu, T. Sarode, in Proceedings of the International Conference on Signal, Networks, Computing, and Systems (2017)

  25. G. Kumar, P.K. Bhatia, IEEE Computer Society (2014). https://doi.org/10.1109/ACCT.2014.74

    Article  Google Scholar 

  26. M. Yang, K. Kpalma, J. Ronsin, Intell. Syst. Ref. Libr. 29, 255 (2012)

    Article  Google Scholar 

  27. G. ElMasry, S. Cubero, E. Moltó, J. Blasco, J. Food Eng. 112, 60 (2012)

    Article  Google Scholar 

  28. H. Lujia, Y. Qiaojuan, L. Xiangyang, H. Jinyou, Trans. Chin. Soc. Agric. Eng. 28, 143 (2012)

    Google Scholar 

  29. H. Wang, J. Xiong, Z. Li, J. Deng, X. Zou, Trans. Chin. Soc. Agric. Eng. 32, 272 (2016)

    Google Scholar 

  30. J. Hernandez, F. Prieto, T. Redarce, Electron. Robot. Automot. Mech. Conf. IEEE 2, 9 (2006)

    Article  Google Scholar 

  31. G. Storvik, IEEE Trans. Pattern Anal. Mach. Intell. 16, 976 (1994)

    Article  Google Scholar 

  32. M.A. Chahooki, Z. Charkari, N. Moghadam, Mach. Vis. Appl. 24, 33 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the financial support of National key R&D plan “intelligent agricultural equipment” of China (Grant No. 2016YFD0701600). We all appreciate the experimental equipment support provided by Key Laboratory of on Site Processing Equipment for Agricultural Products, Ministry of Agriculture, P.R. China.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiuqin Rao.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human or animal subjects.

Informed consent

Not applicable.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Geng, J., Xiao, L., Gao, Y. et al. Separating clods and stones from potato tubers based on color and shape. Food Measure 13, 287–295 (2019). https://doi.org/10.1007/s11694-018-9943-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11694-018-9943-9

Keywords

Navigation