Evaluation of factors in development of Vis/NIR spectroscopy models for discriminating PSE, DFD and normal broiler breast meat

Authors: JIANG, HONGZHE - US Department Of Agriculture (USDA); Yoon, Seung-Chul; Zhuang, Hong; WANG, WEI - China Agricultural University; YANG, YI - China Agricultural University

Submitted to: British Poultry Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/13/2017
Publication Date: 9/4/2017
Citation: Jiang, H., Yoon, S.C., Zhuang, H., Wang, W., Yang, Y. 2017. Evaluation of factors in development of Vis/NIR spectroscopy models for discriminating PSE, DFD and normal broiler breast meat. British Poultry Science. 58(6):673-680.

Interpretive Summary: The consumption of chicken meat is growing steadily worldwide. Similar to red meat, the quality defects of chicken meat such as pale, soft and exudative (PSE) and dark, firm and dry (DFD) meats, which look unattractive to consumers, would directly impact consumer’s purchase and result in significant financial loss to poultry industry. The problem of PSE or DFD has been widely studied in pork in the last decades; however, very limited studies were conducted to differentiate PSE or DFD chicken meat from normal meat. In the present study, visible and near-infrared (Vis/NIR) spectroscopy models were developed for discriminating PSE, normal and DFD poultry breast fillets. The results of the present study showed that the performance of Vis/NIR spectroscopy for the discrimination of PSE, normal and DFD broiler breast fillets was affected by several factors such as wavelength range, use of original spectra for selection of key wavelengths, and use of drip loss as the WHC indicator. Data analysis in this study provides useful information for future development of Vis/NIR spectroscopic methods to classify true intact PSE, normal and DFD chicken meat non-destructively.

Technical Abstract: 1. To evaluate the performance of visible and near-infrared (Vis/NIR) spectroscopic models for discriminating true pale, soft and exudative (PSE), normal and dark, firm and dry (DFD) broiler breast meat in different conditions of preprocessing methods, spectral ranges, characteristic wavelength selection and water-holding capacity (WHC) indexes were assessed. 2. Quality attributes of 214 intact chicken fillets (pectoralis major), such as lightness (L*), pH and WHC indicators including drip loss (DL), water gain and expressible fluid were measured. Fillets were grouped into PSE, normal and DFD categories based on combination of L*, pH and WHC threshold criteria. Classification models were developed using support vector machine based methods on characteristic wavelengths selected from the unprocessed or 2nd-derivative spectra, respectively, in three spectral subsets of 400–2500, 400–1100 and 1100–2500 nm. 3. Better classification of three meat groups was obtained based on unprocessed spectra (72–94%) than 2nd-derivative spectra (55–72%). The classification based on 400–2500 nm (91% average) and 400–1100 nm (89% average) performed better than that on 1100–2500 nm (78% average). In terms of the three different WHC indicators, the combination of L*, pH and DL produced better results than the other two groups, with recognition accuracy of 94.4% using 400–2500-nm range. 4. These analytical results suggest that for a better classification of true PSE, normal and DFD broiler breast meat with Vis/NIR spectra, unprocessed spectra wavelengths should be used, ranges of 400–1000 nm should be included in the data collection, and DL as an indicator of WHC might provide a better prediction model.