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Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region

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Abstract

The objective of this research is to develop a non-destructive method for predicting cooked beef tenderness using optical scattering of light on fresh beef muscle tissue. A hyperspectral imaging system (λ = 496–1,036 nm) that consists of a CCD camera and an imaging spectrograph, was used to acquire beef steak images. The hyperspectral image consisted of 120 bands with spectral intervals of 4.54 nm. Sixty-one fresh beef steaks, including 44 strip loin and 17 tenderloin cuts, were collected. After imaging, the steaks were cooked and Warner-Bratzler shear (WBS) force values were collected as tenderness references. The optical scattering profiles were derived from the hyperspectral images and fitted to the modified Lorentzian function. Parameters, such as the peak height, full scattering width at half maximum (FWHM), and the slope around the FWHM were determined at each wavelength. Stepwise regression was used to identify 7 key wavelengths and parameters. The parameters were then used to predict the WBS scores. The model was able to predict WBS scores with an R = 0.67. Optical scattering implemented with hyperspectral imaging shows limited success for predicting current status of tenderness in beef steak.

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References

  1. K.L. Huffman, M.F. Miller, L.C. Hoover, C.K. Wu, H.C. Brittin, C.B. Ramsey, J Animal Sci 74, 91 (1996)

    CAS  Google Scholar 

  2. P.V. Tarrant, Meat Sci. 49, S1 (1998)

    Article  Google Scholar 

  3. M.F. Miller, M.A. Carr, C.B. Ramsey, K.L. Crockett, L.C. Hoover, J. Animal Sci. 79, 3062 (2001)

    CAS  Google Scholar 

  4. J.L. Lusk, J.A. Fox, T.C. Schroeder, J. Mintert, M. Koohmaraie, Am. J. Agric. Econ. 83, 539 (2001)

    Article  Google Scholar 

  5. T.L. Wheeler, L.V. Cundiff, R.M. Koch, J. Animal Sci. 72, 3145 (1994)

    CAS  Google Scholar 

  6. S.D. Shackelford, T.L. Wheeler, M.K. Meade, J.O. Reagan, B.L. Byrnes, M. Koohmaraie, J. Animal Sci. 79, 2605 (2001)

    CAS  Google Scholar 

  7. D.M. Feuz, W.J. Umberger, C.R. Calkins, B. Sitz, J. Ag. and Resource Economics 29, 501 (2004)

    Google Scholar 

  8. K.I. Hildrum, B.N. Nilsen, M. Mielnik, T. Naes, Meat Sci. 38, 67 (1994)

    Article  Google Scholar 

  9. C.E. Byrne, G. Downey, D.J. Troy, D.J. Buckley, Meat Sci. 49, 399 (1998)

    Article  Google Scholar 

  10. B. Park, Y.R. Chen, W.R. Hruschka, S.D. Shackelford, M. Koohmaraie, J. Animal Sci. 76, 2115 (1998)

    CAS  Google Scholar 

  11. Y. Liu, B.G. Lyon, W.R. Windham, et al., Meat Sci. 65, 1107 (2003)

    Article  Google Scholar 

  12. M. Wyle, D.J. Vote, D.L. Roeber, et al., J. Animal Sci. 81, 441 (2003)

    CAS  Google Scholar 

  13. D.J. Vote, K.E. Belk, J.D. Tatum, J.A. Scanga, G.C. Smith, J. Animal Sci 81, 457 (2003)

    CAS  Google Scholar 

  14. G. Konda Naganathan, L. M. Grimes, J. Subbiah, C. R. Calkins, ASABE Annual International Meeting, Paper No: 063036 (2006)

  15. J. Xia, A. Weaver, D.E. Gerrard, G. Yao, Journal of Biomedical Optics 11, 040504 (2006)

    Article  Google Scholar 

  16. J. Ranasinghesagara, G. Yao, Opt. Express 15, 3998 (2007)

    Article  Google Scholar 

  17. C. Maltin, D. Balcerzak, R. Tilley, M. Delday, Proc. Nutr. Soc. 62, 337 (2003)

    Article  Google Scholar 

  18. T.L. Wheeler, S.D. Shackelford, M. Koohmaraie, J. Animal Sci. 78, 958 (2000)

    CAS  Google Scholar 

  19. R. Lu, Y. Peng, Biosyst. Eng. 93, 161 (2006)

    Article  Google Scholar 

  20. Y. Peng, R. Lu, Postharvest Biol. Technol. (In Press)

  21. J.J. Xia, E.P. Berg, J.W. Lee, G. Yao, Meat Sci. 75, 78 (2007)

    Article  CAS  Google Scholar 

  22. AMSA, American Meat Science Association and National Live Stock and Meat Board, Chicago, IL (1995)

  23. K.C. Lawrence, B. Park, W.R. Windham, C. Mao, TRANS. ASAE. 46, 513 (2003)

    Google Scholar 

  24. Y. Peng, R. Lu, Trans. ASAE. 49, 259 (2006)

    Google Scholar 

  25. Y. Peng, R. Lu, Trans. ASAE. 49, 269 (2006)

    Google Scholar 

  26. Mathworks, MATLAB R2006a Mathworks Inc. Natic, MA. 8−22 (2006)

  27. Johnson (Duxbury Press, New York, NY, 1998)

  28. K.L. Voges, C.L. Mason, J.C. Brooks, et al., Meat Sci. 77, 357 (2007)

    Article  Google Scholar 

  29. R. Lu, Sens. Instrumen. Food Qual. 1, 19 (2007)

    Article  Google Scholar 

  30. Y. Peng, R. Lu, ASABE Annual International Meeting, Paper Number: 066234 (2006)

  31. J. Li, J. Tan, P. Shatadal, Meat Sci. 57, 341 (2001)

    Article  Google Scholar 

  32. C. Zheng, D.W. Sun, L. Zheng, TRANS. ASAE. 49, 1447 (2006)

    Google Scholar 

  33. D.M. Wulf, S.F. O’Connor, J.D. Tatum, G.C. Smith, J. Animal Sci. 75, 684 (1997)

    CAS  Google Scholar 

Download references

Acknowledgments

We acknowledge the technical support of Mr. Benjamin Bailey, Engineering Technician, and Dr. Matthew E. Doumit, of the Michigan State University Food Science and Human Nutrition, for helping in freezing and vacuum packaging the samples.

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Authors and Affiliations

  1. Biological Systems Engineering, University of Nebraska, 212 L.W. Chase Hall, Lincoln, NE, 68583-0726, USA

    Kim Cluff, Govindarajan Konda Naganathan & Jeyamkondan Subbiah

  2. U.S. Department of Agriculture Agricultural Research Service, 224 Farrall Hall, East Lansing, MI, 48824, USA

    Renfu Lu

  3. A213 Animal Sciences, University of Nebraska, Lincoln, NE, 68583-0908, USA

    Chris R. Calkins

  4. Computer Science and Engineering, University of Nebraska, 361 Avery Hall, Lincoln, NE, 68588-0115, USA

    Ashok Samal

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  1. Kim Cluff
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  2. Govindarajan Konda Naganathan
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  3. Jeyamkondan Subbiah
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  4. Renfu Lu
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  5. Chris R. Calkins
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  6. Ashok Samal
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Correspondence to Jeyamkondan Subbiah.

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Cluff, K., Konda Naganathan, G., Subbiah, J. et al. Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region. Sens. & Instrumen. Food Qual. 2, 189–196 (2008). https://doi.org/10.1007/s11694-008-9052-2

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  • DOI: https://doi.org/10.1007/s11694-008-9052-2

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