Title: Poultry water holding capacity measurements using infrared spectroscopies correlated to traditional methods Authors
Submitted to: Annual Meeting of the Institute of Food Technologists
Publication Type: Abstract Only
Publication Acceptance Date: February 10, 2011
Publication Date: July 11, 2011
Citation: Hawkins, S.A., Zhuang, H. 2011. Poultry water holding capacity measurements using infrared spectroscopies correlated to traditional methods. Annual Meeting of the Institute of Food Technologists. Technical Abstract: Water holding capacity (WHC) in chicken meat is directly correlated with the quality of the meat. Lower water holding capacity is linked with decreased sensory qualities and therefore lower consumer satisfaction. Additionally, measurement of WHC is subject to wide variations which can depend on many factors including errors in the methodology and seemingly uncontrollable variations in the conditions such as muscle variations. New methods of measurement are needed that can standardize the measurement and give more quantitative results. In this study, core samples of chicken breast filets were subjected to water holding capacity measurements by the traditional drip loss and compression filter paper methods. From the same breast filet samples, a small core sample from each was subjected to thermogravimetric analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy and near-infrared (NIR) spectroscopy. The TGA traces, FTIR and NIR spectra were inspected for correlation with the results from the traditional methods. The data was also examined using chemometric software to look for correlations by partial least squares regression and principal component regression. The results suggest that instrumental examination when paired with chemometric analysis may be a more objective approach for measurement of water holding capacity of poultry meat. The measurements from both traditional and instrumental methods were used to create an initial prediction model. The use of instrumental analysis along with the prediction model can lead to reduction in variation of WHC measurements and thus a more reliable quality indicator.