The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight
Samo za registrovane korisnike
2019
Autori
Tomović, VladimirPezo, Lato
Jokanović, Marija
Tomović, Mila
Šojić, Branislav
Škaljac, Snežana
Vujadinović, Dragan
Ivić, Maja
Djekić, Ilija
Tomašević, Igor
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Early post-mortem, objective and non-destructive prediction of tissue distribution in the major pork cuts is a challenge for the meat industry. Mathematical models to predict pig carcass composition using total lean meat percentage and carcass weight were evaluated in this study. The data were obtained from 455 cold pig carcasses which were dissected according to the EU reference method; total lean meat percentage and carcass weight ranged from 42.45 to 69.21% and from 23.26 to 55.22 kg, respectively. Developed empirical models gave a reasonable fit to the experimental data and successfully predicted the carcass composition and tissue distribution in primal cuts. The second order polynomial models showed high coefficients of determination for prediction of experimental results (between 0.612 and 0.929), while the artificial neural network (ANN) model, based on the Broyden-Fletcher-Goldfarb-Shanno iterative algorithm, showed better prediction capabilities (overall r(2) was 0.889). The n...ewly developed software, based on ANN model is easy, fast, cheap and with sufficient precision for application in the meat industry.
Ključne reči:
Pig / Carcass composition / Tissue distribution / Meatiness / Fatness / Mathematical modellingIzvor:
Journal of Food Measurement and Characterization, 2019, 13, 3, 2230-2240Izdavač:
- Springer, New York
Finansiranje / projekti:
- Razvoj tradicionalnih tehnologija proizvodnje fermentisanih suvih kobasica sa oznakom geografskog porekla u cilju dobijanja bezbednih proizvoda standardnog kvaliteta (RS-MESTD-Technological Development (TD or TR)-31032)
DOI: 10.1007/s11694-019-00143-2
ISSN: 2193-4126
WoS: 000481420900063
Scopus: 2-s2.0-85065762524
Institucija/grupa
Poljoprivredni fakultetTY - JOUR AU - Tomović, Vladimir AU - Pezo, Lato AU - Jokanović, Marija AU - Tomović, Mila AU - Šojić, Branislav AU - Škaljac, Snežana AU - Vujadinović, Dragan AU - Ivić, Maja AU - Djekić, Ilija AU - Tomašević, Igor PY - 2019 UR - http://aspace.agrif.bg.ac.rs/handle/123456789/4951 AB - Early post-mortem, objective and non-destructive prediction of tissue distribution in the major pork cuts is a challenge for the meat industry. Mathematical models to predict pig carcass composition using total lean meat percentage and carcass weight were evaluated in this study. The data were obtained from 455 cold pig carcasses which were dissected according to the EU reference method; total lean meat percentage and carcass weight ranged from 42.45 to 69.21% and from 23.26 to 55.22 kg, respectively. Developed empirical models gave a reasonable fit to the experimental data and successfully predicted the carcass composition and tissue distribution in primal cuts. The second order polynomial models showed high coefficients of determination for prediction of experimental results (between 0.612 and 0.929), while the artificial neural network (ANN) model, based on the Broyden-Fletcher-Goldfarb-Shanno iterative algorithm, showed better prediction capabilities (overall r(2) was 0.889). The newly developed software, based on ANN model is easy, fast, cheap and with sufficient precision for application in the meat industry. PB - Springer, New York T2 - Journal of Food Measurement and Characterization T1 - The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight EP - 2240 IS - 3 SP - 2230 VL - 13 DO - 10.1007/s11694-019-00143-2 ER -
@article{ author = "Tomović, Vladimir and Pezo, Lato and Jokanović, Marija and Tomović, Mila and Šojić, Branislav and Škaljac, Snežana and Vujadinović, Dragan and Ivić, Maja and Djekić, Ilija and Tomašević, Igor", year = "2019", abstract = "Early post-mortem, objective and non-destructive prediction of tissue distribution in the major pork cuts is a challenge for the meat industry. Mathematical models to predict pig carcass composition using total lean meat percentage and carcass weight were evaluated in this study. The data were obtained from 455 cold pig carcasses which were dissected according to the EU reference method; total lean meat percentage and carcass weight ranged from 42.45 to 69.21% and from 23.26 to 55.22 kg, respectively. Developed empirical models gave a reasonable fit to the experimental data and successfully predicted the carcass composition and tissue distribution in primal cuts. The second order polynomial models showed high coefficients of determination for prediction of experimental results (between 0.612 and 0.929), while the artificial neural network (ANN) model, based on the Broyden-Fletcher-Goldfarb-Shanno iterative algorithm, showed better prediction capabilities (overall r(2) was 0.889). The newly developed software, based on ANN model is easy, fast, cheap and with sufficient precision for application in the meat industry.", publisher = "Springer, New York", journal = "Journal of Food Measurement and Characterization", title = "The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight", pages = "2240-2230", number = "3", volume = "13", doi = "10.1007/s11694-019-00143-2" }
Tomović, V., Pezo, L., Jokanović, M., Tomović, M., Šojić, B., Škaljac, S., Vujadinović, D., Ivić, M., Djekić, I.,& Tomašević, I.. (2019). The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight. in Journal of Food Measurement and Characterization Springer, New York., 13(3), 2230-2240. https://doi.org/10.1007/s11694-019-00143-2
Tomović V, Pezo L, Jokanović M, Tomović M, Šojić B, Škaljac S, Vujadinović D, Ivić M, Djekić I, Tomašević I. The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight. in Journal of Food Measurement and Characterization. 2019;13(3):2230-2240. doi:10.1007/s11694-019-00143-2 .
Tomović, Vladimir, Pezo, Lato, Jokanović, Marija, Tomović, Mila, Šojić, Branislav, Škaljac, Snežana, Vujadinović, Dragan, Ivić, Maja, Djekić, Ilija, Tomašević, Igor, "The prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight" in Journal of Food Measurement and Characterization, 13, no. 3 (2019):2230-2240, https://doi.org/10.1007/s11694-019-00143-2 . .