Skip to main content
ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #345758
Research Project: Assessment and Improvement of Poultry Meat, Egg, and Feed Quality

Location: Quality and Safety Assessment Research Unit

Title: Prediction of quality attributes of chicken breast fillets by using Vis/NIR spectroscopy combined with factor analysis method

Author
item YANG, YI - China Agricultural University
item Yoon, Seung-Chul
item Zhuang, Hong
item WANG, WEI - China Agricultural University
item JIANG, HONGZHE - China Agricultural University
item JIA, BEIBEI - China Agricultural University

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 6/7/2017
Publication Date: 7/24/2017
Citation: Yang, Y., Yoon, S.C., Zhuang, H., Wang, W., Jiang, H. 2017. Prediction of quality attributes of chicken breast fillets by using Vis/NIR spectroscopy combined with factor analysis method. ASABE Annual International Meeting. DOI:10.13031/aim.201700728.

Interpretive Summary: With the improvement of people's living standard, more attention has been paid to the quality of poultry meat in the market. Characteristics of poultry meat, such as color, pH, and drip loss, are commonly used for its quality assessment. The traditional methods used for measuring those quality characteristics are time-consuming and/or laborious. Visible and near-infrared (Vis/NIR) spectroscopy is an efficient and advanced technique to detecting multi-quality attributes simultaneously. It has been proved that Vis/NIR spectroscopy has a great potential for predicting meat quality. Factor analysis (FA) is a powerful multivariate statistical technique for extracting the uncorrelated factors, which are more fundamental but hidden in the directly measured variables, from the numerous and high correlation quality attributes. In recent years, FA has been evaluated in fruit and water quality assessment. However, there is a lack of study of using Vis/NIR spectroscopy methods combined with FA for predicting chicken quality attributes in literature. Thus the objective of this study was to investigate the potential of using Vis/NIR spectroscopy technique combined with FA to predict the quality of chicken breast fillets (pectoralis major). Our results show that Vis/NIR spectroscopy combined with factor analysis method can be used as a tool to predict multiple quality attributes of raw chicken meat simultaneously.

Technical Abstract: Visible/near-infrared (Vis/NIR) spectroscopy with wavelength range between 400 and 2500 nm combined with factor analysis method was tested to predict quality attributes of chicken breast fillets. Quality attributes, including color (L*, a*, b*), pH, and drip loss were analyzed using factor analysis method. Factors (F1 and F2), as a comprehensive performance of quality attributes, were classified from quality attributes according to their internal correlations. Individual quality attributes and factors were predicted using partial least-squares regression (PLSR). Results indicated that F1 and F2 had good predictive ability (R2p=0.79, RPD=2.0; R2p=0.83, RPD=2.4). Results revealed that Vis/NIR spectroscopy combined with factor analysis method can be used as a tool for quality assessment of chicken meat.