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Prediction of Egg Freshness and Albumen Quality Using Visible/Near Infrared Spectroscopy

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Abstract

Important changes occur in egg during storage leading to loss of quality. Prediction of these changes is critical in order to monitor egg quality and freshness. The aim of this research was to evaluate application of visible (VIS) and near infrared (NIR) spectroscopy as a rapid and non-destructive technique for egg quality assessment. Three hundred and sixty intact white-shelled eggs freshly laid by the same flock of hens fed with a standard feed were obtained. They were put under controlled conditions of temperature and humidity (T = 18 °C and RH = 55%) for 16 days of storage. Forty eggs were analyzed at day 0, 2, 4, 6, 8, 10, 12, 14, and 16. Transmission spectral data was obtained in the range from 350 to 2,500 nm. The non-destructive spectral data was compared to egg sample’s Haugh unit (HU) and albumen pH in terms of quality and to the number of storage days in terms of freshness. A partial least squares predictive model was developed and used to link the destructive assessment methods and the number of storage days with the spectral data. The correlation coefficient between the measured and predicted values of HU, albumen pH, and number of storage days were up to 0.94, R 2 was up to 0.90 and the root mean square error values for the validation were 5.05, 0.06, and 1.65, respectively. These results showed that VIS/NIR transmission spectroscopy is a good tool for assessment of egg freshness and albumen pH and can be used as a non-destructive method for the prediction of HU, albumen pH, and number of storage days. In addition, the relevant information about these parameters was in the VIS and NIR ranging from 411 to 1,729 nm.

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References

  • Abdel-Nour, N., Ngadi, M., Prasher, S., & Karimi, Y. (2009). Combined Maximum R2 and partial least squares method for wavelengths selection and analysis of spectroscopic data. International Journal of Poultry Science, 8(2), 170–178.

    Article  CAS  Google Scholar 

  • Berardinelli, A., Giunchi, A., Guarnieri, A., Pezzi, F., & Ragni, L. (2005). Shell egg albumen height assessment by FT-NIR Spectroscopy. Transactions of the ASAE, 48(4), 1423–1428.

    CAS  Google Scholar 

  • Birth, G. S., Dull, G. G., Renfore, W. T., & Kays, S. J. (1985). Non-destructive spectrometric determination of dry matter in onions. Journal of the American Society for Horticultural Science, 110(2), 297–303.

    Google Scholar 

  • Du, Y. P., Ljiang, Y. Z., Jiang, J. H., Berry, R. J., & Ozaki, Y. (2004). Spectral regions selection to improve prediction ability models by changeable size moving window partial least squares and searching combination moving window partial least squares. Analytica Chimica Acta, 501, 183–191.

    Article  CAS  Google Scholar 

  • Dutta, R., Hines, E. L., Gardner, J. W., Udrea, D. D., & Boilot, P. (2003). Non-destructive egg freshness determination: An electronic nose based approach. Measurement Science and Technology, 14, 190–198.

    Article  CAS  Google Scholar 

  • Fila, G., Bellochi, A., Acutis, M., & Donatelli, M. (2003). IRENE: A software to evaluate model performance. European Journal of Agronomy, 18, 269–372.

    Article  Google Scholar 

  • Gómez, A. H., He, Y., & Pereira, A. G. (2006). Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using VIS/NIR-spectroscopy techniques. Journal of Food Engineering, 77, 313–319.

    Article  Google Scholar 

  • Haugh, R. R. (1937). The haugh unit for measuring egg quality. US Egg Poultry Magazine, 43, 552–555.

    CAS  Google Scholar 

  • IRENE (2003) Integrated resources for evaluating numerical estimates. Ver. beta 1.00. Bologna, Italy.

  • Karoui, R., Kemps, B., Bamelis, F., De Katelaere, B., Decuypere, E., & De Baerdemaeker, J. (2006). Methods to evaluate egg freshness in research and industry: A review. European Food Research Technology, 222, 727–732.

    Article  CAS  Google Scholar 

  • Karoui, R., Nicolaï, B., & De Baerdemaeker, J. (2008). Monitoring the egg freshness during storage under modified atmosphere by fluorescence spectroscopy. Food and Bioprocess Technology, 1, 346–356.

    Article  Google Scholar 

  • Kemps, B. J., Bamelis, F., De Katelaere, B., Mertens, K., Tona, K., Decuypere, E. M., et al. (2006). Visible transmission spectroscopy for the assessment of egg freshness. Journal of the Science of Food and Agriculture, 86, 1399–1406.

    Article  CAS  Google Scholar 

  • Kemps, B. J., De Katelaere, B., Bamelis, F., Mertens, K., Tona, K., Decuypere, E. M., et al. (2007). Albumen freshness assessment by combining visible near-infrared transmission and low-resolution proton nuclear magnetic resonance spectroscopy. Journal of Poultry Science, 86, 752–759.

    CAS  Google Scholar 

  • Lapao, C., Gamma, L. T., & Caveiro Soares, M. (1999). Effects of broiler breeder age and length of egg storage on albumen characteristics and hatchability. Journal of Poultry Science, 78, 640–645.

    CAS  Google Scholar 

  • Liu, Y., Ying, Y., Ouyang, A., Ouyang, A., & Li, Y. (2007). Measurement of internal quality in chicken eggs using visible transmittance spectroscopy technology. Food Control, 18, 18–22.

    Article  Google Scholar 

  • McGlone, V. A., Jordan, R. B., & Martinson, P. J. (2002). Vis/NIR estimation at harvest of pre- and post-storage quality indices for ‘Royal Gala’ apple. Postharvest Biology and Technology., 25, 135–44.

    Article  CAS  Google Scholar 

  • Robinson, D. S., & Monsey, J. B. (1972). Changes in the composition of ovomucin during liquefaction of thick white. Journal of the Science of Food and Agriculture, 23, 29–38.

    Article  CAS  Google Scholar 

  • SAS (2003) SAS User’s guide: statistics. Ver. 8.2. Cary: SAS Institute, Inc.

  • Shao Y, Bao Y, & He Y (2009) Visible/near-infrared spectra for linear and nonlinear calibrations: a case to predict soluble solids contents and pH value in peach. Food and Bioprocess Technology, doi:10.1007/s11947-009-0227-6.

  • Slaughter, D. C., & Crisosto, C. H. (1998). Non-destructive internal quality assessment of kiwifruit using near-infrared spectroscopy. Seminars in Food Analysis, 3, 131–140.

    Google Scholar 

  • Spiegelman, C. H., McShane, M. J., Goetz, M. J., Motamedi, M., Yue, Q. L., & Cote, G. L. (1998). Theorotical justification of wavelength selection in PLS calibration: Development of a new algorithm. Analytical Chemistry, 70, 35–44.

    Article  CAS  Google Scholar 

  • The Unscrambler (2007) The Unscrambler User’s Guide: ver. 9.7. Woodbridge: CAMO Software AS.

    Google Scholar 

  • Wells, P. C., & Norris, K. H. (1987). Egg quality—current problem and recent advances. In B. M. Freeman (Ed.), Egg quality—current problems and recent advances. Abingdon: Carfax.

    Google Scholar 

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Acknowledgements

The authors would like to appreciate the Poultry Industry of Canada for funding this study.

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Authors and Affiliations

  1. Department of Bioresource Engineering, McGill University, Macdonald Campus, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, Canada, H9X 3V9

    Nicolas Abdel-Nour, Michael Ngadi, Shiv Prasher & Yousef Karimi

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  1. Nicolas Abdel-Nour
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  2. Michael Ngadi
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  3. Shiv Prasher
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  4. Yousef Karimi
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Correspondence to Michael Ngadi.

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Abdel-Nour, N., Ngadi, M., Prasher, S. et al. Prediction of Egg Freshness and Albumen Quality Using Visible/Near Infrared Spectroscopy. Food Bioprocess Technol 4, 731–736 (2011). https://doi.org/10.1007/s11947-009-0265-0

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  • DOI: https://doi.org/10.1007/s11947-009-0265-0

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