Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection

Popis výsledku anglicky

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

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21101 - Food and beverages

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Foods

ISSN

2304-8158

e-ISSN

2304-8158

Svazek periodika

11

Číslo periodika v rámci svazku

20

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

000872875200001

EID výsledku v databázi Scopus

2-s2.0-85140786118