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Prediction of Fat Content in Poultry Meat by Near-Infrared Transmission Analysis

U. S. Department of Agriculture, Agricultural Research Service, Richard B. Russell Agricultural Research Center, Poultry Processing and Meat Quality Research Unit, P. O. Box 5677, Athens, Georgia 30604-5677

Correspondence: W. R. Windham, E-mail: rwindham{at}saa.ars.usda.gov

The meat industry routinely determines fat content of meat for quality monitoring and processed product formulation. Meat, as a raw material, is extremely variable and may range from 1 to 65% fat. Fat analysis on a batch-by-batch basis is essential. The reference methods for fat are typically time consuming and generate hazardous waste [1]. In the past 10 yr, near-infrared reflectance (NIR) and transmittance (NIT) spectroscopy have gained widespread use for analyses of quality constituents in many materials. Near-infrared spectroscopy relies on a reference method for calibration and instrument standardization. However, it is often preferred to reference methods because it is rapid, accurate, and cost effective; it does not require skilled operators; and it does not generate hazardous waste. The use of NIT for the prediction of fat in boned raw poultry breast muscle, trimmings, and raw finished product (chicken nuggets) was investigated in this study. We used a database supplied by the NIT instrument manufacturer and samples collected from a local processing plant to develop fat calibration models with an error of 0.70 and 0.33% fat, respectively. Fat calibration models were validated with local processor samples. The standard error of performance was 0.84 and 0.38% fat for the instrument manufacturer and local processor calibration, respectively. Typical within-product standard errors for other rapidmethods are 0.9 and 1.6%for Banco andUnivex rendering, respectively [2]. Badcock fat has been rejected as an official method due to loss of accuracy for samples greater than 27% fat and high bias for samples less than 27% fat [2]. Standard errors for Official AOAC Soxhlet type methods have ranged from 0.41 to 1.14% for fat [1]. USDA performance criteria for repeatability require standard errors of less than 0.63 for fat [1]. This study supports that NIT can be a useful tool in the poultry processing industry for fat analysis in quality monitoring and processed product formulation.

Key Words: analysis • fat • near-infrared transmittance • product formulation