Physico-biochemical characterization of breast muscle in fast and slow growing chickens
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With increasing consumption of poultry products, it is important for consumers, retailers, and poultry industry to concern on consistent high quality. Growth rate and water holding capacity (WHC) are important meat quality parameters. Selection for growth has affected meat attributes. Pale, soft, and exudative meat has poor WHC which results in an economic loss of processors, as well as a decrease in consumer acceptance. Our goal was to find the relationship in changes of muscles from two chicken populations with varying growth rate and WHC through online monitoring method and proteomic analysis. Two chicken populations were established; a slow growing sub-population (SG) with an average growth rate of 229 g/wk and a fast growing sub-population (FG) with an average growth rate of 319 g/wk. The initial and final pH was higher in the FG compared to the SG population. The SG had significantly higher L*, b*, drip loss (DL), and cook yield when compared to the FG. From spectrum of raw breast chicken muscles by Raman spectroscopy, there were 8 wavenumbers (P<0.05) differed in growth population: 538, 582, 682, 691, 1367, 1625, 1704, 1743 cm-1 and 5 wavenumbers (P<0.05) in WHC population: 1270, 1277, 1354, 1653, 1737 cm-1. For proteomic analysis, protein markers that are associated with growth and WHC from chicken muscle were investigated. Water soluble protein (WSP) and non-WSP extracts were prepared from breast muscle of chickens that differed in growth rate or WHC. A total of 22 selected protein spots were excised from two-dimensional gel electrophoresis and analyzed by in-gel tryptic digestion and MALDI-TOF mass spectrometry. The mass spectra of 20 protein spots significantly matched to the on-line database (protein score > 83; p<0.05). In non-WSP extract, there were unique proteins that were present only in FG population: gi|118099530; gi|20664362; gi|71895043; gi|114794125; gi|297343122; gi|296214263. Overall conclusions were: FG showed better technological yields than SG chickens; color parameters and Raman spectroscopy could be used to segregate muscle for further processing and online monitoring; information from proteomics could be used to identify functional candidate genes for meat quality traits in chickens.