Visible/near infrared spectroscopy in muscle beef analysis: How device choice and sampling affect prediction accuracy

This study evaluated the performance of two portable spectral devices (visible: Vis; near-infrared: NIR) and one benchtop combined Vis/NIR instrument for predicting beef biochemical traits related to meat quality. A total of 497 muscle samples were collected from 55 fattening farms across five European countries. Reference values were obtained exclusively from pooled samples. For the benchtop device, two sampling strategies were compared: 1) direct scanning of pooled samples (n = 99) used for reference analyses, and 2) scanning individual samples followed by spectral averaging to match pooled references. Partial least squares regression models were developed using several preprocessing methods. For total and heme iron, predictive performance was also evaluated by separately analyzing the visible region of the benchtop device. Results showed that the benchtop Vis/NIR instrument clearly outperformed the portable devices, providing higher prediction accuracies for all traits across the full spectral range. Compared with portable instruments, the benchtop device achieved superior performance for proximate composition (R2 = 0.51–0.85 vs 0.10–0.22), major fatty acids (R2 = 0.50–0.68 vs 0.01–0.31), and total and heme iron (R2 = 0.79–0.93 vs 0.46–0.91). Moreover, scanning individual samples and averaging spectra yielded better prediction models than direct scanning of pooled samples, with good accuracies for moisture, protein, fat content, major saturated and monounsaturated fatty acids, and iron. Conversely, poor prediction (R2 < 0.40) was observed for polyunsaturated fatty acids, TBARS, carnosine, anserine, zinc, selenium and B-group vitamins. Overall, Vis/NIR spectroscopy showed strong potential for beef quality assessment, although further optimization is required for portable devices.