Journal Highlight: Challenges in model development for meat composition using multipoint NIR spectroscopy from at-line to in-line monitoring

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  • Published: Jul 31, 2017
  • Author: spectroscopyNOW
  • Channels: Infrared Spectroscopy
thumbnail image: Journal Highlight: Challenges in model development for meat composition using multipoint NIR spectroscopy from at-line to in-line monitoring

Multipoint near-infrared spectroscopy has been used to predict the fat and moisture content of minced beef samples in at-line and on-line modes and the obstacles be encountered during in-line monitoring have been identified.

Challenges in model development for meat composition using multipoint NIR spectroscopy from at-line to in-line monitoring

Journal of Food Science, 2017, 82, 1557-1562
Y. Dixit, Maria P. Casado-Gavalda, R. Cama-Moncunill, P. J. Cullen and Carl Sullivan

Abstract: This study evaluates the efficiency of multipoint near-infrared spectroscopy (NIRS) to predict the fat and moisture content of minced beef samples both in at-line and on-line modes. Additionally, it aims at identifying the obstacles that can be encountered in the path of performing in-line monitoring. Near-infrared (NIR) reflectance spectra of minced beef samples were collected using an NIR spectrophotometer, employing a Fabry-Perot interferometer. Partial least squares regression (PLSR) models based on reference values from proximate analysis yielded calibration coefficients of determination (Rc2) of 0.96 for both fat and moisture. For an independent batch of samples, fat was estimated with a prediction coefficient of determination (Rp2) of 0.87 and 0.82 for the samples in at-line and on-line modes, respectively. All the models were found to have good prediction accuracy; however, a higher bias was observed for predictions under on-line mode. Overall results from this study illustrate that multipoint NIR systems combined with multivariate analysis has potential as a process analytical technology (PAT) tool for monitoring process parameters such as fat and moisture in the meat industry, providing real-time spectral and spatial information. The new multipoint NIR device illustrates potential as an in-line quality monitoring tool for the meat processing industry. With further developments in the field of NIR optics, it could be possible to use this device in an industrial environment.

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