A method for nondestructive prediction of pork meat quality and safety attributes by hyperspectral imaging technique

• Hyperspectral imaging was exploited for nondestructively predicting pork attributes.
• A more effective data analysis method for resolving “hypercube” was presented.
• Gompertz parameters were evaluated for predicting different attributes of pork.
• One promising tool for monitoring the multiple attributes of pork was provided.

Rapid and nondestructive methods for predicting meat quality and safety attributes are of great concerns at present. A Hyperspectral imaging technique was investigated for evaluating pork meat tenderness and Escherichia coli (E. coli) contamination in this study. Totally 31 samples were used for hyperspectral imaging in the spectral range of 400–1100 nm. A novel method by Modified Gompertz function was exploited to extract the scattering characteristics of pork meat from the spatially-resolved hyperspectral images. Gompertz parameters α, β, ε and δ which can represent different optical meanings were derived by curve-fitting to the original scattering profiles. The fitting coefficients were all around 0.99 between 470 and 960 nm, which indicating the effective interpretation by Gompertz function. Multi-linear regression models were established using both individual parameters and integrated parameters, and the results showed that Gompertz parameter δ was superior to other individual parameters for both pork meat tenderness and E. coli contamination, and the integrated parameter can perform better than individual parameters. The validation results (RCV) by the integrated parameter method were 0.949 and 0.939 for pork meat tenderness and E. coli contamination respectively. The study demonstrated that hyperspectral imaging technique combined with Gompertz function was potential for rapid determination of pork meat tenderness and E. coli contamination, and so hopefully to provide a promising tool for monitoring the multiple attributes concerning meat quality and safety.