Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
PubMed
37431018
PubMed Central
PMC9601423
DOI
10.3390/foods11203270
PII: foods11203270
Knihovny.cz E-zdroje
- Klíčová slova
- bioelectrical impedance, hand palpation, in-line processing, supervised learning, unsupervised learning, woody breast,
- Publikační typ
- časopisecké články MeSH
Bioelectrical impedance analysis (BIA) was established to quantify diverse cellular characteristics. This technique has been widely used in various species, such as fish, poultry, and humans for compositional analysis. This technology was limited to offline quality assurance/detection of woody breast (WB); however, inline technology that can be retrofitted on the conveyor belt would be more helpful to processors. Freshly deboned (n = 80) chicken breast fillets were collected from a local processor and analyzed by hand-palpation for different WB severity levels. Data collected from both BIA setups were subjected to supervised and unsupervised learning algorithms. The modified BIA showed better detection ability for regular fillets than the probe BIA setup. In the plate BIA setup, fillets were 80.00% for normal, 66.67% for moderate (data for mild and moderate merged), and 85.00% for severe WB. However, hand-held BIA showed 77.78, 85.71, and 88.89% for normal, moderate, and severe WB, respectively. Plate BIA setup is more effective in detecting WB myopathies and could be installed without slowing the processing line. Breast fillet detection on the processing line can be significantly improved using a modified automated plate BIA.
Department of Animal Science Czech University of Life Sciences Prague 16500 Prague Czech Republic
Department of Animal Sciences Auburn University Auburn AL 36849 USA
Department of Business Analytics and Information Auburn University Auburn AL 36849 USA
Department of Poultry Science Auburn University Auburn AL 36849 USA
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