Hyperspectral imaging technique for offal quantification in minced meat


  • M Kamruzzaman Department of Food Technology and Rural Industries, Bangladesh Agricultural University, Mymensingh-2202
  • ME Haque Department of Computer Science & Mathematics, Bangladesh Agricultural University, Mymensingh-2202
  • MR Ali Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh-2202


Adulteration, Hyperspectral imaging, Wavelength Selection, Minced meat, Offal, PLSR


Spectral imaging is a new technique that combines conventional imaging and spectroscopy in a single system to obtain both spatial and spectral information simultaneously from an object. In this study, potential of hyperspectral imaging in the spectral range of 910-1700 nm was investigated for detecting adulteration in minced lamb meat. Spectral data were extracted to develop a partial least squares regression (PLSR) model to predict the level of adulteration in minced lamb. Good prediction model was obtained using the whole spectral range with a coefficient of determination (R2 CV) of 0.97 and root-mean-square errors estimated by cross validation (RMSECV) of 1.80%. Successive projection algorithm (SPA) was employed for optimal waveband selection. The PLSR model using only 7 optimum wavelengths (930, 1067, 1396, 1460, 1658, 1668, and 1702 nm) resulted in a coefficient of determination (R2 CV) of 0.97 and RMSECV of 1.84%. The study demonstrated the ability of the hyperspectral imaging as a rapid and alternative to the time-consuming and conventional methods to detect adulteration in minced lamb meat.

DOI: http://dx.doi.org/10.3329/jbau.v12i1.21411

J. Bangladesh Agril. Univ. 12(1): 189-194, June 2014


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How to Cite

Kamruzzaman, M., Haque, M., & Ali, M. (2014). Hyperspectral imaging technique for offal quantification in minced meat. Journal of the Bangladesh Agricultural University, 12(1), 189–194. Retrieved from https://www.banglajol.info/index.php/JBAU/article/view/21411



Agricultural Engineering