4.6 Article

Can Bioelectrical Impedance Analysis (BIA) Be Used to Predict Pig's Meat Quality In Vivo?

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 23, Pages -

Publisher

MDPI
DOI: 10.3390/app122312035

Keywords

bioelectrical impedance; resistance; reactance; pork meat quality

Funding

  1. Polish Ministry of Science and Higher Education within Faculty of Human Nutrition and Consumer Sciences, Warsaw University of Life Sciences (WULS), for scientific research

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This study aimed to evaluate the feasibility of using bioelectrical impedance analysis (BIA) to estimate pork quality. The results showed significant correlations between BIA parameters and meat quality traits, indicating the potential of BIA as a tool for predicting meat quality.
The aim of the current study was to evaluate the possibility of application of bioelectrical impedance analysis (BIA) in order to estimate pork quality. The BIA measurements were tested on 18 living animals for the prediction of the meat quality. The absolute resultant electrical resistance (Rz) and reactance (Xc) of the body was measured with a set of disposable surface electrodes at the frequency of 50 kHz and the current intensity of 400 mu A. The characteristics of meat quality, pH measured 1 h and 24 h after slaughter, meat color parameters represented in CIE L*a*b* system, glycolytic potential, intramuscular fat, and natural drip loss, were assessed on the samples of the Longissimus dorsi (LD) muscle. The slaughter value of pigs was characterized on the basis of hot carcass weight (HCW) and percent of meat in carcass. The results showed a significant Pearson correlation between bioelectrical impedance parameter Rz and pH(1) (r = 0.48*, p < 0.05). A significant Spearman correlation was showed between color b* value and the Rz/Xc/HCW ratio (r = -0.62*, p < 0.05) and Xc (r = -0.51*, p < 0.05), as well as between the Rz/Xc ratio with pH(1) (r = 0.48*, p < 0.05). The multivariate statistical method (principal component analysis and cluster analysis) showed that bioimpedance measurements combined with meat quality traits make it possible to distinguish groups with different quality parameters. However, the relationships between them are complex and still require analysis.

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