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

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...

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Veröffentlicht in:Applied sciences 2022-12, Vol.12 (23), p.12035
Hauptverfasser: Przybylski, Wiesław, Jaworska, Danuta, Sot, Magdalena, Sieczko, Leszek, Niemyjski, Stanisław, Dukaczewska, Karina, Wojtasik-Kalinowska, Iwona
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Sprache:eng
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Zusammenfassung: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 µA. 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 pH1 (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 pH1 (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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app122312035