Literature DB >> 21673177

Feasibility of the direct application of near-infrared reflectance spectroscopy on intact chicken breasts to predict meat color and physical traits.

M De Marchi1, M Penasa, M Battagin, E Zanetti, C Pulici, M Cassandro.   

Abstract

Physical and color characteristics of chicken meat were investigated on 193 animals by directly applying a fiberoptic probe to the breast muscle and using the visible-near-infrared (NIR) spectral range from 350 to 1,800 nm. Data on pH was recorded 48 h postmortem (pH); lightness (L*), redness (a*), and yellowness (b*) 48 h postmortem; thawing and cooking losses and shear force after freezing. Partial least squares regressions were performed using untreated data, raw absorbance data (log(1/R)), and multiplicative scatter correction plus first or second derivative spectra. Models were validated using full cross-validation, and their predictive ability was determined by root mean square error of cross-validation (RMSE(CV)) and correlation coefficient of cross-validation (r(cv)). Means (±SD) of pH, L*, a*, b*, thawing loss, cooking loss, and shear force were 5.83 ± 0.13, 44.54 ± 2.42, -1.90 ± 0.62, 3.21 ± 3.28, 4.84 ± 2.44%, 19.39 ± 2.95%, and 16.08 ± 3.83 N, respectively. The best prediction models were developed using log(1/R) spectra for b* (r(cv) = 0.93; RMSE(CV) = 1.16) and a* (r(cv) = 0.88; RMSE(CV) = 0.29), while a medium predictive ability of NIR was obtained for pH, L*, and thawing and cooking losses (r(cv) from 0.69 to 0.76; RMSE(CV) from 0.01 to 1.73). Finally, predicted model for shear force (r(cv) = 0.41; RMSE(CV) = 3.18) was unsatisfactory. Results suggest that NIR is a feasible technique for the assessment of several quality traits of intact breast muscle.

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Year:  2011        PMID: 21673177     DOI: 10.3382/ps.2010-01239

Source DB:  PubMed          Journal:  Poult Sci        ISSN: 0032-5791            Impact factor:   3.352


  4 in total

1.  Rapid Nondestructive Prediction of Multiple Quality Attributes for Different Commercial Meat Cut Types Using Optical System.

Authors:  Jiangying An; Yanlei Li; Chunzhi Zhang; Dequan Zhang
Journal:  Food Sci Anim Resour       Date:  2022-07-01

Review 2.  Predicting the Quality of Meat: Myth or Reality?

Authors:  Cécile Berri; Brigitte Picard; Bénédicte Lebret; Donato Andueza; Florence Lefèvre; Elisabeth Le Bihan-Duval; Stéphane Beauclercq; Pascal Chartrin; Antoine Vautier; Isabelle Legrand; Jean-François Hocquette
Journal:  Foods       Date:  2019-09-24

3.  The effect of dietary Marula nut meal on the physical properties, proximate and fatty acid content of Japanese quail meat.

Authors:  Bulelani E Mazizi; Kennedy H Erlwanger; Eliton Chivandi
Journal:  Vet Anim Sci       Date:  2020-02-04

4.  Online Prediction of Physico-Chemical Quality Attributes of Beef Using Visible-Near-Infrared Spectroscopy and Chemometrics.

Authors:  Amna Sahar; Paul Allen; Torres Sweeney; Jamie Cafferky; Gerard Downey; Andrew Cromie; Ruth M Hamill
Journal:  Foods       Date:  2019-10-23
  4 in total

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