TY  - JOUR
AU  - Simunović, Stefan
AU  - Rajić, Sara
AU  - Đorđević, Vesna Ž.
AU  - Tomović, Vladimir
AU  - Vujadinović, Dragan
AU  - Đekić, Ilija
AU  - Tomašević, Igor
PY  - 2021
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/5920
AB  - The 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.
PB  - Institute of Meat Hygiene and Technology
T2  - Meat Technology
T1  - Estimation of fat content in fermented sausages by means of computer vision system (cvs)
EP  - 32
IS  - 1
SP  - 27
VL  - 62
DO  - 10.18485/MEATTECH.2021.62.1.3
ER  - 

@article{
author = "Simunović, Stefan and Rajić, Sara and Đorđević, Vesna Ž. and Tomović, Vladimir and Vujadinović, Dragan and Đekić, Ilija and Tomašević, Igor",
year = "2021",
abstract = "The 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.",
publisher = "Institute of Meat Hygiene and Technology",
journal = "Meat Technology",
title = "Estimation of fat content in fermented sausages by means of computer vision system (cvs)",
pages = "32-27",
number = "1",
volume = "62",
doi = "10.18485/MEATTECH.2021.62.1.3"
}

Simunović, S., Rajić, S., Đorđević, V. Ž., Tomović, V., Vujadinović, D., Đekić, I.,& Tomašević, I.. (2021). Estimation of fat content in fermented sausages by means of computer vision system (cvs). in Meat Technology
Institute of Meat Hygiene and Technology., 62(1), 27-32.
https://doi.org/10.18485/MEATTECH.2021.62.1.3

Simunović S, Rajić S, Đorđević VŽ, Tomović V, Vujadinović D, Đekić I, Tomašević I. Estimation of fat content in fermented sausages by means of computer vision system (cvs). in Meat Technology. 2021;62(1):27-32.
doi:10.18485/MEATTECH.2021.62.1.3 .

Simunović, Stefan, Rajić, Sara, Đorđević, Vesna Ž., Tomović, Vladimir, Vujadinović, Dragan, Đekić, Ilija, Tomašević, Igor, "Estimation of fat content in fermented sausages by means of computer vision system (cvs)" in Meat Technology, 62, no. 1 (2021):27-32,
https://doi.org/10.18485/MEATTECH.2021.62.1.3 . .

TY  - JOUR
AU  - Đekić, Ilija
AU  - Ilić, Jovan
AU  - Chen, Jianshe
AU  - Đekić, Rastko
AU  - Sołowiej, Bartosz G.
AU  - Vujadinović, Dragan
AU  - Tomašević, Igor
PY  - 2021
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/5970
AB  - Pungency is an interesting sensory stimulus analyzed from different perspectives, in particular the underpinning mechanisms of its sensation and perception. In this study, grilled pork meat coated with three types of hot sauces were investigated regarding its main food oral processing characteristics and evaluated using time-intensity and temporal dominance of pungency sensations methods analyzing the pungency descriptors and intensities. Besides these methods, facial expressions obtained from video capturing were subject to emotion detection. Mastication parameters showed a slight, but not statistically significant, trend of an increased number of chews and consumption time associated with pungency intensity, while saliva incorporation indicated an increasing trend depending on the pungency intensity, especially after 25 strokes and before swallowing. Both time intensity and temporal dominance of pungency sensations showed that the complexity of understanding these sensations is in relation to intensity and type. Finally, the use of emotion detection software in analyzing the faces of panelists during mastication confirmed the increase in non-neutral emotions associated with the increase in pungency intensity.
PB  - MDPI
T2  - Applied Sciences (Switzerland)
T1  - Analysis of Pungency Sensation Effects from an Oral Processing, Sensorial and Emotions Detection Perspective—Case Study with Grilled Pork Meat
IS  - 21
SP  - 10459
VL  - 11
DO  - 10.3390/app112110459
ER  - 

@article{
author = "Đekić, Ilija and Ilić, Jovan and Chen, Jianshe and Đekić, Rastko and Sołowiej, Bartosz G. and Vujadinović, Dragan and Tomašević, Igor",
year = "2021",
abstract = "Pungency is an interesting sensory stimulus analyzed from different perspectives, in particular the underpinning mechanisms of its sensation and perception. In this study, grilled pork meat coated with three types of hot sauces were investigated regarding its main food oral processing characteristics and evaluated using time-intensity and temporal dominance of pungency sensations methods analyzing the pungency descriptors and intensities. Besides these methods, facial expressions obtained from video capturing were subject to emotion detection. Mastication parameters showed a slight, but not statistically significant, trend of an increased number of chews and consumption time associated with pungency intensity, while saliva incorporation indicated an increasing trend depending on the pungency intensity, especially after 25 strokes and before swallowing. Both time intensity and temporal dominance of pungency sensations showed that the complexity of understanding these sensations is in relation to intensity and type. Finally, the use of emotion detection software in analyzing the faces of panelists during mastication confirmed the increase in non-neutral emotions associated with the increase in pungency intensity.",
publisher = "MDPI",
journal = "Applied Sciences (Switzerland)",
title = "Analysis of Pungency Sensation Effects from an Oral Processing, Sensorial and Emotions Detection Perspective—Case Study with Grilled Pork Meat",
number = "21",
pages = "10459",
volume = "11",
doi = "10.3390/app112110459"
}

Đekić, I., Ilić, J., Chen, J., Đekić, R., Sołowiej, B. G., Vujadinović, D.,& Tomašević, I.. (2021). Analysis of Pungency Sensation Effects from an Oral Processing, Sensorial and Emotions Detection Perspective—Case Study with Grilled Pork Meat. in Applied Sciences (Switzerland)
MDPI., 11(21), 10459.
https://doi.org/10.3390/app112110459

Đekić I, Ilić J, Chen J, Đekić R, Sołowiej BG, Vujadinović D, Tomašević I. Analysis of Pungency Sensation Effects from an Oral Processing, Sensorial and Emotions Detection Perspective—Case Study with Grilled Pork Meat. in Applied Sciences (Switzerland). 2021;11(21):10459.
doi:10.3390/app112110459 .

Đekić, Ilija, Ilić, Jovan, Chen, Jianshe, Đekić, Rastko, Sołowiej, Bartosz G., Vujadinović, Dragan, Tomašević, Igor, "Analysis of Pungency Sensation Effects from an Oral Processing, Sensorial and Emotions Detection Perspective—Case Study with Grilled Pork Meat" in Applied Sciences (Switzerland), 11, no. 21 (2021):10459,
https://doi.org/10.3390/app112110459 . .

TY  - 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 . .