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Hyperspectral imaging based on diffused laser light for prediction of astaxanthin coating concentration

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Abstract

We present a study on predicting the concentration level of synthetic astaxanthin in fish feed pellet coating using multi- and hyperspectral image analysis. This was done in parallel using two different vision systems. A new instrument for hyperspectral imaging, the SuperK setup, using a super-continuum laser as the light source was introduced. Furthermore, a parallel study with the commercially available multispectral VideometerLab imaging system was performed. The SuperK setup used 113 spectral bands (455–1,015 nm), and the VideometerLab used 20 spectral bands (385–1,050 nm). To predict the astaxanthin concentration from the spectral image data, the synthetic astaxanthin content in the pellets was measured with the established standard technique; high-pressure liquid chromatography (HPLC). Regression analysis was done using partial least squares regression (PLSR) and the sparse regression method elastic net (EN). The ratio of standard error of prediction (RPD) is the ratio between the standard deviation of the reference values and the prediction error, and for both PLSR and EN both devices gave RPD values between 4 and 24, and with mean prediction error of 1.4–8.0 parts per million of astaxanthin concentration. The results show that it is possible to predict the synthetic astaxanthin concentration in the coating well enough for quality control using both multi- and hyperspectral image analysis, while the SuperK setup performs with higher accuracy than the VideometerLab device for this particular problem. The spectral resolution made it possible to identify the most significant spectral regions for detection of astaxanthin. The results also imply that the presented methods can be used in general for quality inspection of various coating substances using similar coating methods.

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Acknowledgments

The work presented has received funding from BioMar A/S and the EU under the Seventh Framework Programme FP7/2007-2013 under grant agreement number 214505.10. This work was in part financed by the Centre for Imaging Food Quality project which is funded by the Danish Council for Strategic Research (contract no 09-067039) within the Programme Commission on Health, Food and Welfare. The expert technical assistance of Heidi Olander Petersen is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Informatics and Mathematical Modelling, Technical University of Denmark, Kgs. Lyngby, Denmark

    Martin Georg Ljungqvist, Otto Højager Attermann Nielsen, Line Harder Clemmensen & Bjarne Kjær Ersbøll

  2. Division of Industrial Food Research, National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark

    Stina Frosch & Michael Engelbrecht Nielsen

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  1. Martin Georg Ljungqvist
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Correspondence to Martin Georg Ljungqvist.

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Ljungqvist, M.G., Nielsen, O.H.A., Frosch, S. et al. Hyperspectral imaging based on diffused laser light for prediction of astaxanthin coating concentration. Machine Vision and Applications 25, 327–343 (2014). https://doi.org/10.1007/s00138-013-0512-2

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