Food Analytical Methods

, Volume 10, Issue 10, pp 3443–3451 | Cite as

Predicting Color Traits of Intact Broiler Breast Fillets Using Visible and Near-Infrared Spectroscopy

  • Hongzhe Jiang
  • Seung-Chul Yoon
  • Hong Zhuang
  • Wei WangEmail author


This study was conducted to assess the potential for visible and near-infrared (Vis/NIR) spectroscopy to predict an important quality attribute, color traits, of intact broiler breast fillets (pectoralis major). A total of 214 boneless and skinless chicken fillets were procured from a commercial processing plant. The quantitative calibration models were established between five color trait parameters (CIELAB L*, a*, b*, chroma, and hue angle) and spectra from four different spectral ranges (400–2500, 400–1100, 1100–2500, and 900–1700 nm) collected from skin (ventral) and bone (dorsal) sides of fillets individually by partial least squares regressions (PLSR). Predictive ability was assessed by coefficient of determination of prediction (R p 2), ratio performance deviation (RPD), and range error ratio (RER). Models developed based on spectra collected from fillet bone side performed better than those from skin side regardless of color trait, best results were all obtained using 400–2500 nm and closely followed by 400–1100 nm. Prediction results for meat redness a* (R p 2 = 0.81; RPD = 2.21; RER = 12.13) and hue angle (R p 2 = 0.80; RPD = 2.07; RER = 12.65) were the best and for L*, b*, and chroma (R p 2 ≥ 0.72; RPD ≥ 1.81; RER ≥ 8.48) were also well. This work systematically evaluated the influence of different color trait parameters, fillet side spectra, spectral ranges, and pre-treatment methods compared with previous investigation, and results suggest that Vis/NIR spectroscopy can be a feasible method for prediction of color traits of intact broiler breast fillets, especially when spectra are collected from the fillet bone side and range of optimal partial ranges is included.


Color traits Vis/NIR Intact chicken meat Fillet sides Spectral ranges PLSR 



The authors would like to thank the organizations or individuals who had contributed to this manuscript. This work was supported financially by the China National Science and Technology Support Program (2012BAK08B04).

Compliance with Ethical Standards

Conflict of Interest

Hongzhe Jiang declares that he has no conflict of interest. Seung-Chul Yoon declares that he has no conflict of interest. Hong Zhuang declares that he has no conflict of interest. Wei Wang declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed Consent

Not applicable.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Hongzhe Jiang
    • 1
  • Seung-Chul Yoon
    • 2
  • Hong Zhuang
    • 2
  • Wei Wang
    • 1
    Email author
  1. 1.College of EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Quality & Safety Assessment Research Unit, U. S. National Poultry Research Center, USDA-ARSAthensUSA

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