Прегледај по Аутор "Tomašević, Igor"
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- СтавкаEstimation of fat content in fermented sausages by means of Computer Vision System (CVS)(Institute of Meat Hygiene and Technology, Belgrade, 2021) Simunović, Stefan; Rajić, Sara; Đorđević, Vesna; Tomović, Vladimir; Vujadinović, Dragan; Đekić, Ilija; Tomašević, IgorThe aim of this study was to investigate the possibility of computer vision system (CVS) application in fat content estimation for different types of fermented sausages. Four different types of local fermented sausages with different fat contents were studied: Njeguška, Kulen, Pirotska and tea sausage. Results obtained for CVS-estimated fat content were compared to the results of traditional chemical analysis. Relative errors of fat content estimation in Njeguška, Kulen, Pirotska and tea sausage were 1.47%, 0.46%, 20.84% and 11.19%, respectively. Results of t-test showed a significant (p<0.01) difference between mean fat contents obtained by CVS and chemical analysis in the case of Pirotska sausage. On the other hand, there was no significant (p<0.01) difference between mean fat contents obtained by the two methods for the rest of the analysed sausages. The results indicate CVS has potential for application in the analysis of fat content of fermented sausages.
- СтавкаThe prediction of lean meat and subcutaneous fat with skin content in pork cuts on the carcass meatness and weight(Springer, 2019) Tomović, Vladimir; Pezo, Lato; Jokanović, Marija; Tomović, Mila; Šojić, Branislav; Škaljac, Snežana; Vujadinović, Dragan; Ivić, Maja; Djekić, Ilija; Tomašević, IgorEarly 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 r2 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.