Non-destructive assessment of the myoglobin content of Tan sheep using hyperspectral imaging

Abstract

This study aimed to develop simplified models for rapid and nondestructive monitoring myoglobin contents (DeoMb, MbO₂ and MetMb) during refrigerated storage of Tan sheep based on a hyperspectral imaging (HSI) system in the spectral range of 400-1000 nm. Partial least squares regression (PLSR) and least-squares support vector machines (LSSVM) were applied to correlate the spectral data with the reference values of myoglobin contents measured by a traditional method. In order to simplify the LSSVM models, competitive adaptive reweighted sampling (CARS) and Interval variable iterative space shrinkage approach (iVISSA) were used to select key wavelengths. The new CARS-LSSVM models of DeoMb and MbO₂ yielded good results, with R²p of 0.810 and 0.914, RMSEP of 1.127 and 2.598, respectively. The best model of MetMb was new iVISSA-CARS-LSSVM, with an R²p of 0.915 and RMSEP of 2.777. The overall results from this study indicated that it was feasible to predict myoglobin contents in Tan sheep using HSI.

Keywords: Hyperspectral imaging; Least-squares support vector machines (LSSVM); Myoglobin content; Tan sheep; Wavelengths selection.