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[EN] The primary objective of this study was to compare the colour of muscle from bulls finished at pasture or indoors on a high concentrate diet. The ancillary objectives were to identify possible explanations for any differences in the colour observed and the potential of muscle colour to discriminate between bull beef from different production systems. Growth, longissimus muscle colour, fibre type composition and metabolic profile were measured in late-maturing breed sired suckler bulls slaughtered at 19 months of age after 199 days at pasture (G0), 100 days indoors after 98 days at pasture (G0AL) and indoors for 199 days (AL). When compared to bulls finished indoors and offered a high concentrate ration, the carcass weight of G0 bulls was lower, their carcasses were leaner, and their longissimus muscle was similar in lightness but less red and had a lower glycolytic metabolism. The temperature at which the longissimus muscle reached pH 6.0 was lower (19.7 °C) for G0 than for G0AL (29.9 °C) and AL (31.6 °C), which did not differ. Co-variate adjustment for this variable removed the differences in redness. Adjusting the chill settings appears to be a practical strategy for abattoirs to minimise early post-mortem differences in muscle colour between lighter grass-fed and heavier concentrate-fed carcasses. The preliminary results demonstrate the potential of both L*, a*, b* values and the visible reflectance spectra of muscle to discriminate between grass- finished and concentrate-finished bull beef, but further refinement and validation of the models is required.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.