Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F22%3A91551" target="_blank" >RIV/60460709:41210/22:91551 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2304-8158/11/20/3270/htm" target="_blank" >https://www.mdpi.com/2304-8158/11/20/3270/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/foods11203270" target="_blank" >10.3390/foods11203270</a>
Alternative languages
Result language
angličtina
Original language name
Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection
Original language description
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. Plat
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
21101 - Food and beverages
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Foods
ISSN
2304-8158
e-ISSN
2304-8158
Volume of the periodical
11
Issue of the periodical within the volume
20
Country of publishing house
CH - SWITZERLAND
Number of pages
14
Pages from-to
1-14
UT code for WoS article
000872875200001
EID of the result in the Scopus database
2-s2.0-85140786118