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Food Analytical Methods

, Volume 11, Issue 5, pp 1356–1366 | Cite as

Quality Assessment of Intact Chicken Breast Fillets Using Factor Analysis with Vis/NIR Spectroscopy

  • Yi Yang
  • Hong Zhuang
  • Seung-Chul Yoon
  • Wei Wang
  • Hongzhe Jiang
  • Beibei Jia
  • Chunyang Li
Article

Abstract

Factor analysis (FA) method was tested to assess quality of chicken breast fillets with the visible/near-infrared (Vis/NIR) spectroscopy with wavelength range between 400 and 2500 nm. According to inherent correlation, three factors were extracted from the measured eight quality traits (L*, a*, b*, pH, moisture, drip loss, expressible fluid, and salt-induced water gain). The extracted “grade factor” (F 1), “color factor” (F 2), and “moisture factor” (F 3) could respectively represent the characteristics and the variation tendency of the corresponding quality traits and were defined as three new quality assessment indexes. Furthermore, partial least squares regression (PLSR) models were established to quantitatively relate spectral information to eight individual quality traits and three factors. The results indicated that the models for predicting each factor performed better than those for individual quality traits. Key wavelengths of each quality trait were then selected, and the corresponding spectra were taken to build new PLSR prediction models. The selected key wavelengths showed obvious practical significance, and the new models had comparable predictive performance to those models developed based on the full spectra, among which the new models of F 1 and F 2 had acceptable and robust predictive abilities (R2p = 0.73, RPD = 1.91; R2p = 0.74, RPD = 1.97). Our results in the present study demonstrate the potential for FA and Vis/NIR spectroscopy as a useful method to assess the quality of chicken breast fillets.

Keywords

Poultry Pectoralis major Water hold capacity pH Color Partial least squares regression (PLSR) 

Notes

Funding Information

The authors acknowledge financial support by the China National Science and Technology Support Program (Grant no. 2012BAK08B04).

Compliance with Ethical Standards

Conflict of Interest

Yi Yang declares that he has no conflict of interest. Hong Zhuang declares that he has no conflict of interest. Seung-Chul Yoon declares that he has no conflict of interest. Wei Wang declares that he has no conflict of interest. Hongzhe Jiang declares that he has no conflict of interest. Beibei Jia declares that he has no conflict of interest. Chunyang Li 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, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Yi Yang
    • 1
  • Hong Zhuang
    • 2
  • Seung-Chul Yoon
    • 2
  • Wei Wang
    • 1
  • Hongzhe Jiang
    • 1
  • Beibei Jia
    • 1
  • Chunyang Li
    • 3
  1. 1.College of EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Quality & Safety Assessment Research Unit, U.S. National Poultry Research CenterUSDA-ARSAthensUSA
  3. 3.Institute of Food Science and TechnologyJiangsu Academy of Agricultural SciencesNanjingChina

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