Rapid Non-destructive Detection of Spoilage of Intact Chicken Breast Muscle Using Near-infrared and Fourier Transform Mid-infrared Spectroscopy and Multivariate Statistics

Abstract

Near-infrared (NIR) transflectance and Fourier transform-infrared (FT-IR) attenuated total reflectance spectra of intact chicken breast muscle packed under aerobic conditions and stored at 4° for 14 days were collected and investigated for their potential use in rapid non-destructive detection of spoilage. Multiplicative scatter correction-transformed NIR and standard normal variate-transformed FT-IR spectra were analysed using principal component analysis (PCA), partial least-squares discriminant analysis (PLS2-DA) and outer product analysis (OPA). PCA and PLS2-DA regression failed to completely discriminate between days 0 and 4 samples (total viable count (TVC) days 0 and 4 = 5.23 and 6.75 log10 cfu g−1) which had bacterial loads smaller than the accepted levels (8 log10 cfu g−1) of sensory spoilage detection but classified correctly days 8 and 14 samples (TVC days 8 and 14 = 9.61 and 10.37 log10 cfu g−1). OPA performed on both NIR and FT-IR datasets revealed several correlations that highlight the effect of proteolysis in influencing the spectra. These correlations indicate that increase in free amino acids and peptides could be the main factor in the discrimination of intact chicken breast muscle. This investigation suggests that NIR and FT-IR spectroscopy can become useful, rapid, non-destructive tools for spoilage detection.