TY  - JOUR
AU  - Šumić, Zdravko
AU  - Tepić Horecki, Aleksandra
AU  - Kašiković, Vladimir
AU  - Rajković, Andreja
AU  - Pezo, Lato
AU  - Daničić, Tatjana
AU  - Pavlić, Branimir
AU  - Milić, Anita
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/1007
AB  - The following article describes new research about the design, construction and installation of the new prototype of a vacuum dryer with an ejector system. Moreover, the testing of this new prototype involved comparing the qualities of fruit dried in a vacuum drier with an ejector system to fruit dried in a convectional vacuum drier. The data obtained were then analyzed and presented. Due to their economic relevance and highly valuable nutritional value and sensory properties, sour cherries and apricots have been chosen to be the subjects for the testing. The most appropriate quality indicators for analyzing were moisture content, aw value, share and penetration force, total phenol, flavonoid and anthocyanin content and antioxidant activity (FRAP, DPPH and ABTS test). The main results of this study were achieved by designing, constructing, installing and testing the usage of the innovative prototype of a vacuum dryer with an ejector system in the laboratory of the Technology of fruit and vegetable products of the Faculty of Technology Novi Sad, University of Novi Sad. Based on our analyses of the obtained data, it was concluded that vacuum dryer with an ejector system are similar to vacuum dryer with a vacuum pump in terms of all tested physical, chemical and biological properties of dried samples. We observed similarities in some of the most important parameters, including product safety and quality, such as the aw value and the total phenol content, respectively. For example, in dried sour cherry, the aw values ranged from 0.250 to 0.521 with the vacuum pump and from 0.232 to 0.417 with the ejector system; the total phenol content ranged from 2322 to 2765 mg GAE/100 g DW with the vacuum pump and from 2327 to 2617 mg GAE/100 g DW with the ejector system. In dried apricot, the aw ranged from 0.176 to 0.405 with the vacuum pump and from 0.166 to 0.313 with the ejector system; total phenol content ranged from 392 to 439 mg GAE/100 g DW with the vacuum pump and from 378 to 428 mg GAE/100 g DW with the ejector system.
PB  - MDPI
T2  - Foods
T1  - Prototype of an Innovative Vacuum Dryer with an Ejector System: Comparative Drying Analysis with a Vacuum Dryer with a Vacuum Pump on Selected Fruits
IS  - 17
SP  - 3198
VL  - 12
DO  - 10.3390/foods12173198
ER  - 

@article{
author = "Šumić, Zdravko and Tepić Horecki, Aleksandra and Kašiković, Vladimir and Rajković, Andreja and Pezo, Lato and Daničić, Tatjana and Pavlić, Branimir and Milić, Anita",
year = "2023",
abstract = "The following article describes new research about the design, construction and installation of the new prototype of a vacuum dryer with an ejector system. Moreover, the testing of this new prototype involved comparing the qualities of fruit dried in a vacuum drier with an ejector system to fruit dried in a convectional vacuum drier. The data obtained were then analyzed and presented. Due to their economic relevance and highly valuable nutritional value and sensory properties, sour cherries and apricots have been chosen to be the subjects for the testing. The most appropriate quality indicators for analyzing were moisture content, aw value, share and penetration force, total phenol, flavonoid and anthocyanin content and antioxidant activity (FRAP, DPPH and ABTS test). The main results of this study were achieved by designing, constructing, installing and testing the usage of the innovative prototype of a vacuum dryer with an ejector system in the laboratory of the Technology of fruit and vegetable products of the Faculty of Technology Novi Sad, University of Novi Sad. Based on our analyses of the obtained data, it was concluded that vacuum dryer with an ejector system are similar to vacuum dryer with a vacuum pump in terms of all tested physical, chemical and biological properties of dried samples. We observed similarities in some of the most important parameters, including product safety and quality, such as the aw value and the total phenol content, respectively. For example, in dried sour cherry, the aw values ranged from 0.250 to 0.521 with the vacuum pump and from 0.232 to 0.417 with the ejector system; the total phenol content ranged from 2322 to 2765 mg GAE/100 g DW with the vacuum pump and from 2327 to 2617 mg GAE/100 g DW with the ejector system. In dried apricot, the aw ranged from 0.176 to 0.405 with the vacuum pump and from 0.166 to 0.313 with the ejector system; total phenol content ranged from 392 to 439 mg GAE/100 g DW with the vacuum pump and from 378 to 428 mg GAE/100 g DW with the ejector system.",
publisher = "MDPI",
journal = "Foods",
title = "Prototype of an Innovative Vacuum Dryer with an Ejector System: Comparative Drying Analysis with a Vacuum Dryer with a Vacuum Pump on Selected Fruits",
number = "17",
pages = "3198",
volume = "12",
doi = "10.3390/foods12173198"
}

Šumić, Z., Tepić Horecki, A., Kašiković, V., Rajković, A., Pezo, L., Daničić, T., Pavlić, B.,& Milić, A.. (2023). Prototype of an Innovative Vacuum Dryer with an Ejector System: Comparative Drying Analysis with a Vacuum Dryer with a Vacuum Pump on Selected Fruits. in Foods
MDPI., 12(17), 3198.
https://doi.org/10.3390/foods12173198

Šumić Z, Tepić Horecki A, Kašiković V, Rajković A, Pezo L, Daničić T, Pavlić B, Milić A. Prototype of an Innovative Vacuum Dryer with an Ejector System: Comparative Drying Analysis with a Vacuum Dryer with a Vacuum Pump on Selected Fruits. in Foods. 2023;12(17):3198.
doi:10.3390/foods12173198 .

Šumić, Zdravko, Tepić Horecki, Aleksandra, Kašiković, Vladimir, Rajković, Andreja, Pezo, Lato, Daničić, Tatjana, Pavlić, Branimir, Milić, Anita, "Prototype of an Innovative Vacuum Dryer with an Ejector System: Comparative Drying Analysis with a Vacuum Dryer with a Vacuum Pump on Selected Fruits" in Foods, 12, no. 17 (2023):3198,
https://doi.org/10.3390/foods12173198 . .

TY  - JOUR
AU  - Đurović, Saša
AU  - Pezo, Lato
AU  - Gašić, Uroš
AU  - Gorjanović, Stanislava
AU  - Pastor, Ferenc T.
AU  - Bazarnova, Julia
AU  - Smyatskaya, Yulia A.
AU  - Zeković, Zoran
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/1004
AB  - Stinging nettle (Urtica dioica L.) is one fantastic plant widely used in folk medicine, pharmacy, cosmetics, and food. This plant's popularity may be explained by its chemical composition, containing a wide range of compounds significant for human health and diet. This study aimed to investigate extracts of exhausted stinging nettle leaves after supercritical fluid extraction obtained using ultrasound and microwave techniques. Extracts were analyzed to obtain insight into the chemical composition and biological activity. These extracts were shown to be more potent than those of previously untreated leaves. The principal component analysis was applied as a pattern recognition tool to visualize the antioxidant capacity and cytotoxic activity of extract obtained from exhausted stinging nettle leaves. An artificial neural network model is presented for the prediction of the antioxidant activity of samples according to polyphenolic profile data, showing a suitable anticipation property (the r(2) value during the training cycle for output variables was 0.999).
PB  - MDPI AG
T2  - Foods
T1  - Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction
IS  - 4
VL  - 12
DO  - 10.3390/foods12040809
UR  - conv_1086
ER  - 

@article{
author = "Đurović, Saša and Pezo, Lato and Gašić, Uroš and Gorjanović, Stanislava and Pastor, Ferenc T. and Bazarnova, Julia and Smyatskaya, Yulia A. and Zeković, Zoran",
year = "2023",
abstract = "Stinging nettle (Urtica dioica L.) is one fantastic plant widely used in folk medicine, pharmacy, cosmetics, and food. This plant's popularity may be explained by its chemical composition, containing a wide range of compounds significant for human health and diet. This study aimed to investigate extracts of exhausted stinging nettle leaves after supercritical fluid extraction obtained using ultrasound and microwave techniques. Extracts were analyzed to obtain insight into the chemical composition and biological activity. These extracts were shown to be more potent than those of previously untreated leaves. The principal component analysis was applied as a pattern recognition tool to visualize the antioxidant capacity and cytotoxic activity of extract obtained from exhausted stinging nettle leaves. An artificial neural network model is presented for the prediction of the antioxidant activity of samples according to polyphenolic profile data, showing a suitable anticipation property (the r(2) value during the training cycle for output variables was 0.999).",
publisher = "MDPI AG",
journal = "Foods",
title = "Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction",
number = "4",
volume = "12",
doi = "10.3390/foods12040809",
url = "conv_1086"
}

Đurović, S., Pezo, L., Gašić, U., Gorjanović, S., Pastor, F. T., Bazarnova, J., Smyatskaya, Y. A.,& Zeković, Z.. (2023). Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction. in Foods
MDPI AG., 12(4).
https://doi.org/10.3390/foods12040809
conv_1086

Đurović S, Pezo L, Gašić U, Gorjanović S, Pastor FT, Bazarnova J, Smyatskaya YA, Zeković Z. Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction. in Foods. 2023;12(4).
doi:10.3390/foods12040809
conv_1086 .

Đurović, Saša, Pezo, Lato, Gašić, Uroš, Gorjanović, Stanislava, Pastor, Ferenc T., Bazarnova, Julia, Smyatskaya, Yulia A., Zeković, Zoran, "Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction" in Foods, 12, no. 4 (2023),
https://doi.org/10.3390/foods12040809 .,
conv_1086 .

TY  - JOUR
AU  - Demir, Hasan
AU  - Demir, Hande
AU  - Lončar, Biljana
AU  - Pezo, Lato
AU  - Brandić, Ivan
AU  - Voca, Neven
AU  - Yilmaz, Fatma
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/1003
AB  - One of the essential factors for the selection of the drying process is energy consumption. This study intended to optimize the drying treatment of capers using convection (CD), refractive window (RWD), and vacuum drying (VD) combined with ultrasonic pretreatment by a comparative approach among artificial neural networks (ANN) and response surface methodology (RSM) focusing on the specific energy consumption (SEC). For this purpose, the effects of drying temperature (50, 60, 70 degrees C), ultrasonication time (0, 20, 40 min), and drying method (RWD, CD, VD) on the SEC value (MJ/g) were tested using a face-centered central composite design (FCCD). RSM (R-2: 0.938) determined the optimum drying-temperature-ultrasonication-time values that minimize SEC as; 50 degrees C-35.5 min, 70 degrees C-40 min and 70 degrees C-24 min for RWD, CD and VD, respectively. The conduct of the ANN model is evidenced by the correlation coefficient for training (0.976), testing (0.971) and validation (0.972), which shows the high suitability of the model for optimising specific energy consumption (SEC).
PB  - MDPI AG
T2  - Energies
T1  - Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics
IS  - 4
VL  - 16
DO  - 10.3390/en16041687
UR  - conv_1085
ER  - 

@article{
author = "Demir, Hasan and Demir, Hande and Lončar, Biljana and Pezo, Lato and Brandić, Ivan and Voca, Neven and Yilmaz, Fatma",
year = "2023",
abstract = "One of the essential factors for the selection of the drying process is energy consumption. This study intended to optimize the drying treatment of capers using convection (CD), refractive window (RWD), and vacuum drying (VD) combined with ultrasonic pretreatment by a comparative approach among artificial neural networks (ANN) and response surface methodology (RSM) focusing on the specific energy consumption (SEC). For this purpose, the effects of drying temperature (50, 60, 70 degrees C), ultrasonication time (0, 20, 40 min), and drying method (RWD, CD, VD) on the SEC value (MJ/g) were tested using a face-centered central composite design (FCCD). RSM (R-2: 0.938) determined the optimum drying-temperature-ultrasonication-time values that minimize SEC as; 50 degrees C-35.5 min, 70 degrees C-40 min and 70 degrees C-24 min for RWD, CD and VD, respectively. The conduct of the ANN model is evidenced by the correlation coefficient for training (0.976), testing (0.971) and validation (0.972), which shows the high suitability of the model for optimising specific energy consumption (SEC).",
publisher = "MDPI AG",
journal = "Energies",
title = "Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics",
number = "4",
volume = "16",
doi = "10.3390/en16041687",
url = "conv_1085"
}

Demir, H., Demir, H., Lončar, B., Pezo, L., Brandić, I., Voca, N.,& Yilmaz, F.. (2023). Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics. in Energies
MDPI AG., 16(4).
https://doi.org/10.3390/en16041687
conv_1085

Demir H, Demir H, Lončar B, Pezo L, Brandić I, Voca N, Yilmaz F. Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics. in Energies. 2023;16(4).
doi:10.3390/en16041687
conv_1085 .

Demir, Hasan, Demir, Hande, Lončar, Biljana, Pezo, Lato, Brandić, Ivan, Voca, Neven, Yilmaz, Fatma, "Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics" in Energies, 16, no. 4 (2023),
https://doi.org/10.3390/en16041687 .,
conv_1085 .

TY  - JOUR
AU  - Šuput, Danijela
AU  - Pezo, Lato
AU  - Lončar, Biljana
AU  - Popović, Senka
AU  - Tepic Horecki, Aleksandra
AU  - Danicić, Tatjana
AU  - Cvetković, Dragoljub
AU  - Ranitović, Aleksandra
AU  - Hromiš, Nevena
AU  - Ugarković, Jovana
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/1001
AB  - This work aimed to determine the influence of biopolymer coatings based on pumpkin oil cake, with and without the addition of Mentha piperita essential oil, on the quality and shelf-life of the Afus Ali variety of grapes, stored at room temperature and in the refrigerator. Furthermore, a 10% (w/w) aqueous solution of composite pumpkin oil cake (PuOC) with the addition of 30% glycerol was prepared at 60 degrees C and pH 10. The active biopolymer coating was prepared similarly by adding 1% (v/v) Mentha piperita essential oil. The quality of packed grapes was tested by determining the dry matter content, total sugar content, total acidity, alcohol content, total phenolic compounds content, and total flavonoid content, as well as by determining the antioxidant activity, through the application of the DPPH, FRAP and ABTS tests. Additionally, microbiological parameters were investigated: total aerobic microbial count, yeasts, and molds. The obtained results proved that in all tested samples, over a certain period of time, the content of dry matter, content of phenolic and flavonoids substances and sugar content decreased as a consequence of the spoilage of grapes, that is, the consumption of sugar for the production of alcohol, which consequently leads to the total acidity increasing. The application of lower storage temperatures and active coating (with Mentha piperita essential oil) had a positive effect on all inevitable reactions. Grapes' antioxidant potential may be enhanced or maintained by applying PuOC coating with or without Mentha piperita essential oil, which is best observed in the case of the DPPH test. The uncoated sample stored at room temperature had the largest decrease in DPPH values during storage, with changes ranging from 2.119 mg/g to 1.471 mu mol mg/g. The samples, coated with PuOC and PuOC with the addition of essential oil, had uniform DPPH values throughout the entire storage period. Additionally, regarding phenolic content, at the end of storage period the highest phenolic content was observed in samples with active coating stored at room temperature (734.746 +/- 2.462) and at refrigerator temperature (680.827 +/- 0.448) compared with untreated samples and with samples with plain PuOC coating. The presence of active essential oil in the applied coating significantly affected the microbiological profile of grapes during the storage period. Besides the positive impact of the applied lower storage temperature, the effectiveness of the applied active packaging is even greater (microbiological results were in the order of PuOC+essential oil  LT  PuOC  LT  Control). The developed artificial neural networks were found to be adequate for modeling the microbiological profile, antioxidant activity, phenolic and flavonoid content.
PB  - MDPI AG
T2  - Coatings
T1  - The Influence of Biopolymer Coating Based on Pumpkin Oil Cake Activated with Mentha piperita Essential Oil on the Quality and Shelf-Life of Grape
IS  - 2
VL  - 13
DO  - 10.3390/coatings13020299
UR  - conv_1083
ER  - 

@article{
author = "Šuput, Danijela and Pezo, Lato and Lončar, Biljana and Popović, Senka and Tepic Horecki, Aleksandra and Danicić, Tatjana and Cvetković, Dragoljub and Ranitović, Aleksandra and Hromiš, Nevena and Ugarković, Jovana",
year = "2023",
abstract = "This work aimed to determine the influence of biopolymer coatings based on pumpkin oil cake, with and without the addition of Mentha piperita essential oil, on the quality and shelf-life of the Afus Ali variety of grapes, stored at room temperature and in the refrigerator. Furthermore, a 10% (w/w) aqueous solution of composite pumpkin oil cake (PuOC) with the addition of 30% glycerol was prepared at 60 degrees C and pH 10. The active biopolymer coating was prepared similarly by adding 1% (v/v) Mentha piperita essential oil. The quality of packed grapes was tested by determining the dry matter content, total sugar content, total acidity, alcohol content, total phenolic compounds content, and total flavonoid content, as well as by determining the antioxidant activity, through the application of the DPPH, FRAP and ABTS tests. Additionally, microbiological parameters were investigated: total aerobic microbial count, yeasts, and molds. The obtained results proved that in all tested samples, over a certain period of time, the content of dry matter, content of phenolic and flavonoids substances and sugar content decreased as a consequence of the spoilage of grapes, that is, the consumption of sugar for the production of alcohol, which consequently leads to the total acidity increasing. The application of lower storage temperatures and active coating (with Mentha piperita essential oil) had a positive effect on all inevitable reactions. Grapes' antioxidant potential may be enhanced or maintained by applying PuOC coating with or without Mentha piperita essential oil, which is best observed in the case of the DPPH test. The uncoated sample stored at room temperature had the largest decrease in DPPH values during storage, with changes ranging from 2.119 mg/g to 1.471 mu mol mg/g. The samples, coated with PuOC and PuOC with the addition of essential oil, had uniform DPPH values throughout the entire storage period. Additionally, regarding phenolic content, at the end of storage period the highest phenolic content was observed in samples with active coating stored at room temperature (734.746 +/- 2.462) and at refrigerator temperature (680.827 +/- 0.448) compared with untreated samples and with samples with plain PuOC coating. The presence of active essential oil in the applied coating significantly affected the microbiological profile of grapes during the storage period. Besides the positive impact of the applied lower storage temperature, the effectiveness of the applied active packaging is even greater (microbiological results were in the order of PuOC+essential oil  LT  PuOC  LT  Control). The developed artificial neural networks were found to be adequate for modeling the microbiological profile, antioxidant activity, phenolic and flavonoid content.",
publisher = "MDPI AG",
journal = "Coatings",
title = "The Influence of Biopolymer Coating Based on Pumpkin Oil Cake Activated with Mentha piperita Essential Oil on the Quality and Shelf-Life of Grape",
number = "2",
volume = "13",
doi = "10.3390/coatings13020299",
url = "conv_1083"
}

Šuput, D., Pezo, L., Lončar, B., Popović, S., Tepic Horecki, A., Danicić, T., Cvetković, D., Ranitović, A., Hromiš, N.,& Ugarković, J.. (2023). The Influence of Biopolymer Coating Based on Pumpkin Oil Cake Activated with Mentha piperita Essential Oil on the Quality and Shelf-Life of Grape. in Coatings
MDPI AG., 13(2).
https://doi.org/10.3390/coatings13020299
conv_1083

Šuput D, Pezo L, Lončar B, Popović S, Tepic Horecki A, Danicić T, Cvetković D, Ranitović A, Hromiš N, Ugarković J. The Influence of Biopolymer Coating Based on Pumpkin Oil Cake Activated with Mentha piperita Essential Oil on the Quality and Shelf-Life of Grape. in Coatings. 2023;13(2).
doi:10.3390/coatings13020299
conv_1083 .

Šuput, Danijela, Pezo, Lato, Lončar, Biljana, Popović, Senka, Tepic Horecki, Aleksandra, Danicić, Tatjana, Cvetković, Dragoljub, Ranitović, Aleksandra, Hromiš, Nevena, Ugarković, Jovana, "The Influence of Biopolymer Coating Based on Pumpkin Oil Cake Activated with Mentha piperita Essential Oil on the Quality and Shelf-Life of Grape" in Coatings, 13, no. 2 (2023),
https://doi.org/10.3390/coatings13020299 .,
conv_1083 .

TY  - JOUR
AU  - Seregelj, Vanja
AU  - Tumbas Saponjac, Vesna
AU  - Pezo, Lato
AU  - Kojić, Jovana
AU  - Cvetković, Biljana
AU  - Ilić, Nebojša
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/998
AB  - Antioxidants in fruit and vegetable juices have become increasingly popular because of their potential health benefits. Nowadays, juice mixes made from berries present frequent consumer choices, due to their nutritive value and high content of bioactive compounds. Commercial fruit and vegetable juices available in Serbian markets (n = 32) were analyzed for the physicochemical properties, chemical composition, and antioxidant activity. Relative antioxidant capacity index was used for the ranking of the juices according to antioxidant capacity, while antioxidant effectiveness of phenolic compounds contained in juice samples was investigated depending on phenolic antioxidant coefficients. Principal component analysis was applied to study the data structure. In addition, a multi-layer perceptron model was used for modeling an artificial neural network model (ANN) for prediction antioxidant activity (DPPH, reducing power, and ABTS) based on total phenolic, total pigments, and vitamin C content. The obtained ANN showed good prediction capabilities (the r(2) values during training cycle for output variables were 0.942). Phenolic, pigments, and vitamin C contents showed a positive correlation with the investigated antioxidant activity. The consumption of commercial berry fruit juices available in Serbian markets may deliver great health benefits through the supply of natural antioxidants.
T2  - Food Science and Technology International
T1  - Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets
DO  - 10.1177/10820132231158961
UR  - conv_1081
ER  - 

@article{
author = "Seregelj, Vanja and Tumbas Saponjac, Vesna and Pezo, Lato and Kojić, Jovana and Cvetković, Biljana and Ilić, Nebojša",
year = "2023",
abstract = "Antioxidants in fruit and vegetable juices have become increasingly popular because of their potential health benefits. Nowadays, juice mixes made from berries present frequent consumer choices, due to their nutritive value and high content of bioactive compounds. Commercial fruit and vegetable juices available in Serbian markets (n = 32) were analyzed for the physicochemical properties, chemical composition, and antioxidant activity. Relative antioxidant capacity index was used for the ranking of the juices according to antioxidant capacity, while antioxidant effectiveness of phenolic compounds contained in juice samples was investigated depending on phenolic antioxidant coefficients. Principal component analysis was applied to study the data structure. In addition, a multi-layer perceptron model was used for modeling an artificial neural network model (ANN) for prediction antioxidant activity (DPPH, reducing power, and ABTS) based on total phenolic, total pigments, and vitamin C content. The obtained ANN showed good prediction capabilities (the r(2) values during training cycle for output variables were 0.942). Phenolic, pigments, and vitamin C contents showed a positive correlation with the investigated antioxidant activity. The consumption of commercial berry fruit juices available in Serbian markets may deliver great health benefits through the supply of natural antioxidants.",
journal = "Food Science and Technology International",
title = "Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets",
doi = "10.1177/10820132231158961",
url = "conv_1081"
}

Seregelj, V., Tumbas Saponjac, V., Pezo, L., Kojić, J., Cvetković, B.,& Ilić, N.. (2023). Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets. in Food Science and Technology International.
https://doi.org/10.1177/10820132231158961
conv_1081

Seregelj V, Tumbas Saponjac V, Pezo L, Kojić J, Cvetković B, Ilić N. Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets. in Food Science and Technology International. 2023;.
doi:10.1177/10820132231158961
conv_1081 .

Seregelj, Vanja, Tumbas Saponjac, Vesna, Pezo, Lato, Kojić, Jovana, Cvetković, Biljana, Ilić, Nebojša, "Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets" in Food Science and Technology International (2023),
https://doi.org/10.1177/10820132231158961 .,
conv_1081 .

TY  - JOUR
AU  - Brandić, Ivan
AU  - Antonović, Alan
AU  - Pezo, Lato
AU  - Matin, Bozidar
AU  - Kricka, Tajana
AU  - Jurisić, Vanja
AU  - Spelić, Karlo
AU  - Kontek, Mislav
AU  - Kukuruzović, Juraj
AU  - Grubor, Mateja
AU  - Matin, Ana
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/994
AB  - Agricultural biomass is one of the most important renewable energy sources. As a byproduct of corn, soybean and sunflower production, large amounts of biomass are produced that can be used as an energy source through conversion. In order to assess the quality and the possibility of the use of biomass, its composition and calorific value must be determined. The use of nonlinear models allows for an easier estimation of the energy properties of biomass concerning certain input and output parameters. In this paper, RFR (Random Forest Regression) and SVM (Support Vector Machine) models were developed to determine their capabilities in estimating the HHV (higher heating value) of biomass based on input parameters of ultimate analysis. The developed models showed good performance in terms of HHV estimation, confirmed by the coefficient of determination for the RFR (R-2 = 0.79) and SVM (R-2 = 0.93) models. The developed models have shown promising results in accurately predicting the HHV of biomass from various sources. The use of these algorithms for biomass energy prediction has the potential for further development.
PB  - MDPI AG
T2  - Energies
T1  - Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models
IS  - 2
VL  - 16
DO  - 10.3390/en16020690
UR  - conv_1076
ER  - 

@article{
author = "Brandić, Ivan and Antonović, Alan and Pezo, Lato and Matin, Bozidar and Kricka, Tajana and Jurisić, Vanja and Spelić, Karlo and Kontek, Mislav and Kukuruzović, Juraj and Grubor, Mateja and Matin, Ana",
year = "2023",
abstract = "Agricultural biomass is one of the most important renewable energy sources. As a byproduct of corn, soybean and sunflower production, large amounts of biomass are produced that can be used as an energy source through conversion. In order to assess the quality and the possibility of the use of biomass, its composition and calorific value must be determined. The use of nonlinear models allows for an easier estimation of the energy properties of biomass concerning certain input and output parameters. In this paper, RFR (Random Forest Regression) and SVM (Support Vector Machine) models were developed to determine their capabilities in estimating the HHV (higher heating value) of biomass based on input parameters of ultimate analysis. The developed models showed good performance in terms of HHV estimation, confirmed by the coefficient of determination for the RFR (R-2 = 0.79) and SVM (R-2 = 0.93) models. The developed models have shown promising results in accurately predicting the HHV of biomass from various sources. The use of these algorithms for biomass energy prediction has the potential for further development.",
publisher = "MDPI AG",
journal = "Energies",
title = "Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models",
number = "2",
volume = "16",
doi = "10.3390/en16020690",
url = "conv_1076"
}

Brandić, I., Antonović, A., Pezo, L., Matin, B., Kricka, T., Jurisić, V., Spelić, K., Kontek, M., Kukuruzović, J., Grubor, M.,& Matin, A.. (2023). Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models. in Energies
MDPI AG., 16(2).
https://doi.org/10.3390/en16020690
conv_1076

Brandić I, Antonović A, Pezo L, Matin B, Kricka T, Jurisić V, Spelić K, Kontek M, Kukuruzović J, Grubor M, Matin A. Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models. in Energies. 2023;16(2).
doi:10.3390/en16020690
conv_1076 .

Brandić, Ivan, Antonović, Alan, Pezo, Lato, Matin, Bozidar, Kricka, Tajana, Jurisić, Vanja, Spelić, Karlo, Kontek, Mislav, Kukuruzović, Juraj, Grubor, Mateja, Matin, Ana, "Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models" in Energies, 16, no. 2 (2023),
https://doi.org/10.3390/en16020690 .,
conv_1076 .

TY  - JOUR
AU  - Strbac, Snežana
AU  - Kasanin-Grubin, Milica
AU  - Pezo, Lato
AU  - Stojić, Nataša
AU  - Lončar, Biljana
AU  - Ćurčić, Ljiljana
AU  - Pucarević, Mira
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/993
AB  - With the goal of enhancing the quality of the environment, urban green infrastructure (UGI) is an essential element in sustainable cities, and nature-based solutions (NBS) are being carried out as new infrastructure solutions that increase the resilience of cities. In this research, the method of theoretical analysis and the content analysis as the basic fact-gathering technique was applied to answer to following questions: What are the hindrances and bottlenecks in implementing NBS? Are the current decision-making mechanisms helping NBS get in route to shape cities? Is there any binding policy in practice that promotes NBS? In Belgrade is planned Type 3 of the degree of intervention/level and engineering type-Creation and new ecosystem management in the classifications of intensive urban green space management; urban planning strategies; urban water management; ecological restoration of degraded terrestrial ecosystems; and restoration and creation of semi-natural water bodies and hydrographic networks. In the future, it is essential to implement policies and incentives on national, regional, and local scales that help encourage the usage of NBS in the development of urban infrastructure.
T2  - International Journal of Environmental Research and Public Health
T1  - Green Infrastructure Designed through Nature-Based Solutions for Sustainable Urban Development
IS  - 2
VL  - 20
DO  - 10.3390/ijerph20021102
UR  - conv_1075
ER  - 

@article{
author = "Strbac, Snežana and Kasanin-Grubin, Milica and Pezo, Lato and Stojić, Nataša and Lončar, Biljana and Ćurčić, Ljiljana and Pucarević, Mira",
year = "2023",
abstract = "With the goal of enhancing the quality of the environment, urban green infrastructure (UGI) is an essential element in sustainable cities, and nature-based solutions (NBS) are being carried out as new infrastructure solutions that increase the resilience of cities. In this research, the method of theoretical analysis and the content analysis as the basic fact-gathering technique was applied to answer to following questions: What are the hindrances and bottlenecks in implementing NBS? Are the current decision-making mechanisms helping NBS get in route to shape cities? Is there any binding policy in practice that promotes NBS? In Belgrade is planned Type 3 of the degree of intervention/level and engineering type-Creation and new ecosystem management in the classifications of intensive urban green space management; urban planning strategies; urban water management; ecological restoration of degraded terrestrial ecosystems; and restoration and creation of semi-natural water bodies and hydrographic networks. In the future, it is essential to implement policies and incentives on national, regional, and local scales that help encourage the usage of NBS in the development of urban infrastructure.",
journal = "International Journal of Environmental Research and Public Health",
title = "Green Infrastructure Designed through Nature-Based Solutions for Sustainable Urban Development",
number = "2",
volume = "20",
doi = "10.3390/ijerph20021102",
url = "conv_1075"
}

Strbac, S., Kasanin-Grubin, M., Pezo, L., Stojić, N., Lončar, B., Ćurčić, L.,& Pucarević, M.. (2023). Green Infrastructure Designed through Nature-Based Solutions for Sustainable Urban Development. in International Journal of Environmental Research and Public Health, 20(2).
https://doi.org/10.3390/ijerph20021102
conv_1075

Strbac S, Kasanin-Grubin M, Pezo L, Stojić N, Lončar B, Ćurčić L, Pucarević M. Green Infrastructure Designed through Nature-Based Solutions for Sustainable Urban Development. in International Journal of Environmental Research and Public Health. 2023;20(2).
doi:10.3390/ijerph20021102
conv_1075 .

Strbac, Snežana, Kasanin-Grubin, Milica, Pezo, Lato, Stojić, Nataša, Lončar, Biljana, Ćurčić, Ljiljana, Pucarević, Mira, "Green Infrastructure Designed through Nature-Based Solutions for Sustainable Urban Development" in International Journal of Environmental Research and Public Health, 20, no. 2 (2023),
https://doi.org/10.3390/ijerph20021102 .,
conv_1075 .

TY  - JOUR
AU  - Filipović, V
AU  - Ugrenović, Vladan
AU  - Popović, V
AU  - Dimitrijević, S
AU  - Popović, S
AU  - Aćimović, Milica
AU  - Dragumilo, A
AU  - Pezo, Lato
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/990
AB  - This article describes still insufficiently known technology of pot marigold cultivation with the compost produced from the organic waste of the processing of medicinal plants. For the first time the application was analyzed of different amounts of compost (control – without compost, 2, 10 and 30 kg/m2) on the morphological, productive and qualitative parameters of two pot marigold varieties (Domaći oranž and Plamen Plus). During the five-year period, the best results in both tested pot marigold varieties were achieved with the 30 kg/m2 compost application. The yield of dry flower was higher for the Domaći oranž pot marigold variety fertilized with 30 kg/m2 compost (1957.4 kg/ha) compared with the Plamen Plus variety (451.1 kg/ha). A significantly higher fresh flower yield of the Domaći oranž variety greatly influenced the increase in the quantities of examined quality parameters (total carotenoids, total phenolic, total flavonoids, and DPPH reduction), whose content was higher in the Plamen Plus variety. The artificial neural network model, was built applying the Broyden-Fletcher-Goldfarb-Shanno algorithm, exerted the adequate forecasting abilities for the productivity and quality of pot marigold flowers and the influence of compost material, produced from medicinal plants waste (R2 was 0.837 for the training period). This research demonstrates that it is possible to use organic waste obtained in the processing of medicinal plants, supporting the effectiveness of a circular economy model in the cultivation of pot marigold.
PB  - Elsevier B.V.
T2  - Industrial Crops and Products
T1  - Productivity and flower quality of different pot marigold (Calendula officinalis L.) varieties on the compost produced from medicinal plant waste
VL  - 192
DO  - 10.1016/j.indcrop.2022.116093
UR  - conv_1120
ER  - 

@article{
author = "Filipović, V and Ugrenović, Vladan and Popović, V and Dimitrijević, S and Popović, S and Aćimović, Milica and Dragumilo, A and Pezo, Lato",
year = "2023",
abstract = "This article describes still insufficiently known technology of pot marigold cultivation with the compost produced from the organic waste of the processing of medicinal plants. For the first time the application was analyzed of different amounts of compost (control – without compost, 2, 10 and 30 kg/m2) on the morphological, productive and qualitative parameters of two pot marigold varieties (Domaći oranž and Plamen Plus). During the five-year period, the best results in both tested pot marigold varieties were achieved with the 30 kg/m2 compost application. The yield of dry flower was higher for the Domaći oranž pot marigold variety fertilized with 30 kg/m2 compost (1957.4 kg/ha) compared with the Plamen Plus variety (451.1 kg/ha). A significantly higher fresh flower yield of the Domaći oranž variety greatly influenced the increase in the quantities of examined quality parameters (total carotenoids, total phenolic, total flavonoids, and DPPH reduction), whose content was higher in the Plamen Plus variety. The artificial neural network model, was built applying the Broyden-Fletcher-Goldfarb-Shanno algorithm, exerted the adequate forecasting abilities for the productivity and quality of pot marigold flowers and the influence of compost material, produced from medicinal plants waste (R2 was 0.837 for the training period). This research demonstrates that it is possible to use organic waste obtained in the processing of medicinal plants, supporting the effectiveness of a circular economy model in the cultivation of pot marigold.",
publisher = "Elsevier B.V.",
journal = "Industrial Crops and Products",
title = "Productivity and flower quality of different pot marigold (Calendula officinalis L.) varieties on the compost produced from medicinal plant waste",
volume = "192",
doi = "10.1016/j.indcrop.2022.116093",
url = "conv_1120"
}

Filipović, V., Ugrenović, V., Popović, V., Dimitrijević, S., Popović, S., Aćimović, M., Dragumilo, A.,& Pezo, L.. (2023). Productivity and flower quality of different pot marigold (Calendula officinalis L.) varieties on the compost produced from medicinal plant waste. in Industrial Crops and Products
Elsevier B.V.., 192.
https://doi.org/10.1016/j.indcrop.2022.116093
conv_1120

Filipović V, Ugrenović V, Popović V, Dimitrijević S, Popović S, Aćimović M, Dragumilo A, Pezo L. Productivity and flower quality of different pot marigold (Calendula officinalis L.) varieties on the compost produced from medicinal plant waste. in Industrial Crops and Products. 2023;192.
doi:10.1016/j.indcrop.2022.116093
conv_1120 .

Filipović, V, Ugrenović, Vladan, Popović, V, Dimitrijević, S, Popović, S, Aćimović, Milica, Dragumilo, A, Pezo, Lato, "Productivity and flower quality of different pot marigold (Calendula officinalis L.) varieties on the compost produced from medicinal plant waste" in Industrial Crops and Products, 192 (2023),
https://doi.org/10.1016/j.indcrop.2022.116093 .,
conv_1120 .

TY  - JOUR
AU  - Terzić, Anja
AU  - Pezo, Milada
AU  - Pezo, Lato
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/989
AB  - The machine learning technique for prediction and optimization of building material performances became an essential feature in the contemporary civil engineering. The Artificial Neural Network (ANN) prognosis of mortar behavior was conducted in this study. The model appraised the design and characteristics of seventeen either building or high -temperature mortars. Seven different cement types were employed. Seventeen mineral additives of primary and secondary origin were embedded in the mortar mixtures. Cluster Analysis and Principal Component Analysis designated groups of similar mortars assigning them a specific purpose based on monitored characteristics. ANN foresaw the quality of designed mortars. The impact of implemented raw materials on the mortar quality was assessed and evaluated. ANN outputs highlighted the high suitability level of anticipation, i.e., 0.999 during the training period, which is regarded appropriate enough to correctly predict the observed outputs in a wide range of processing parameters. Due to the high predictive accuracy, ANN can replace or be used in combination with standard destructive tests thereby saving the construction industry time, resources, and capital. Good performances of altered cement mortars are positive sign for widening of economical mineral additives application in building materials and making progress towards achieved carbon neutrality by reducing its emission.
PB  - Međunarodni Institut za nauku o sinterovanju, Beograd
T2  - Science of Sintering
T1  - Application of Artificial Neural Networks in Performance Prediction of Cement Mortars with Various Mineral Additives
EP  - 27
IS  - 1
SP  - 11
VL  - 55
UR  - conv_1097
ER  - 

@article{
author = "Terzić, Anja and Pezo, Milada and Pezo, Lato",
year = "2023",
abstract = "The machine learning technique for prediction and optimization of building material performances became an essential feature in the contemporary civil engineering. The Artificial Neural Network (ANN) prognosis of mortar behavior was conducted in this study. The model appraised the design and characteristics of seventeen either building or high -temperature mortars. Seven different cement types were employed. Seventeen mineral additives of primary and secondary origin were embedded in the mortar mixtures. Cluster Analysis and Principal Component Analysis designated groups of similar mortars assigning them a specific purpose based on monitored characteristics. ANN foresaw the quality of designed mortars. The impact of implemented raw materials on the mortar quality was assessed and evaluated. ANN outputs highlighted the high suitability level of anticipation, i.e., 0.999 during the training period, which is regarded appropriate enough to correctly predict the observed outputs in a wide range of processing parameters. Due to the high predictive accuracy, ANN can replace or be used in combination with standard destructive tests thereby saving the construction industry time, resources, and capital. Good performances of altered cement mortars are positive sign for widening of economical mineral additives application in building materials and making progress towards achieved carbon neutrality by reducing its emission.",
publisher = "Međunarodni Institut za nauku o sinterovanju, Beograd",
journal = "Science of Sintering",
title = "Application of Artificial Neural Networks in Performance Prediction of Cement Mortars with Various Mineral Additives",
pages = "27-11",
number = "1",
volume = "55",
url = "conv_1097"
}

Terzić, A., Pezo, M.,& Pezo, L.. (2023). Application of Artificial Neural Networks in Performance Prediction of Cement Mortars with Various Mineral Additives. in Science of Sintering
Međunarodni Institut za nauku o sinterovanju, Beograd., 55(1), 11-27.
conv_1097

Terzić A, Pezo M, Pezo L. Application of Artificial Neural Networks in Performance Prediction of Cement Mortars with Various Mineral Additives. in Science of Sintering. 2023;55(1):11-27.
conv_1097 .

Terzić, Anja, Pezo, Milada, Pezo, Lato, "Application of Artificial Neural Networks in Performance Prediction of Cement Mortars with Various Mineral Additives" in Science of Sintering, 55, no. 1 (2023):11-27,
conv_1097 .

TY  - JOUR
AU  - Stojić, Nataša
AU  - Pezo, Lato
AU  - Lončar, Biljana
AU  - Pucarević, Mira
AU  - Filipović, Vladimir
AU  - Prokić, Dunja
AU  - Ćurčić, Ljiljana
AU  - Strbac, Snežana
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/985
AB  - The main objective of this study is to determine the possibility of predicting the impact of land use and soil type on concentrations of heavy metals (HMs) and phthalates (PAEs) in soil based on an artificial neural network model (ANN). Qualitative analysis of HMs was performed with inductively coupled plasma-optical emission spectrometry (ICP/OES) and Direct Mercury Analyzer. Determination of PAEs was performed with gas chromatography (GC) coupled with a single quadrupole mass spectrometry (MS). An ANN, based on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) iterative algorithm, for the prediction of HM and PAE concentrations, based on land use and soil type parameters, showed good prediction capabilities (the coefficient of determination (r(2)) values during the training cycle for HM concentration variables were 0.895, 0.927, 0.885, 0.813, 0.883, 0.917, 0.931, and 0.883, respectively, and for PAEs, the concentration variables were 0.950, 0.974, 0.958, 0.974, and 0.943, respectively). The results of this study indicate that HM and PAE concentrations, based on land use and soil type, can be predicted using ANN.
PB  - MDPI AG
T2  - Toxics
T1  - Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation
IS  - 3
VL  - 11
DO  - 10.3390/toxics11030269
UR  - conv_1093
ER  - 

@article{
author = "Stojić, Nataša and Pezo, Lato and Lončar, Biljana and Pucarević, Mira and Filipović, Vladimir and Prokić, Dunja and Ćurčić, Ljiljana and Strbac, Snežana",
year = "2023",
abstract = "The main objective of this study is to determine the possibility of predicting the impact of land use and soil type on concentrations of heavy metals (HMs) and phthalates (PAEs) in soil based on an artificial neural network model (ANN). Qualitative analysis of HMs was performed with inductively coupled plasma-optical emission spectrometry (ICP/OES) and Direct Mercury Analyzer. Determination of PAEs was performed with gas chromatography (GC) coupled with a single quadrupole mass spectrometry (MS). An ANN, based on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) iterative algorithm, for the prediction of HM and PAE concentrations, based on land use and soil type parameters, showed good prediction capabilities (the coefficient of determination (r(2)) values during the training cycle for HM concentration variables were 0.895, 0.927, 0.885, 0.813, 0.883, 0.917, 0.931, and 0.883, respectively, and for PAEs, the concentration variables were 0.950, 0.974, 0.958, 0.974, and 0.943, respectively). The results of this study indicate that HM and PAE concentrations, based on land use and soil type, can be predicted using ANN.",
publisher = "MDPI AG",
journal = "Toxics",
title = "Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation",
number = "3",
volume = "11",
doi = "10.3390/toxics11030269",
url = "conv_1093"
}

Stojić, N., Pezo, L., Lončar, B., Pucarević, M., Filipović, V., Prokić, D., Ćurčić, L.,& Strbac, S.. (2023). Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation. in Toxics
MDPI AG., 11(3).
https://doi.org/10.3390/toxics11030269
conv_1093

Stojić N, Pezo L, Lončar B, Pucarević M, Filipović V, Prokić D, Ćurčić L, Strbac S. Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation. in Toxics. 2023;11(3).
doi:10.3390/toxics11030269
conv_1093 .

Stojić, Nataša, Pezo, Lato, Lončar, Biljana, Pucarević, Mira, Filipović, Vladimir, Prokić, Dunja, Ćurčić, Ljiljana, Strbac, Snežana, "Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation" in Toxics, 11, no. 3 (2023),
https://doi.org/10.3390/toxics11030269 .,
conv_1093 .

TY  - JOUR
AU  - Rajković, Dragana
AU  - Marjanovic Jeromela, Ana
AU  - Pezo, Lato
AU  - Lončar, Biljana
AU  - Grahovac, Nada
AU  - Kondic Spika, Ankica
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/984
AB  - With the aid of models used in artificial intelligence, a wide range of data can be processed quickly with high accuracy. The quality of rapeseed oil from 40 genotypes cultivated during four consecutive years was analysed. Two machine learning techniques (artificial neural network - ANN, and random forest regression - RFR) were applied for the modelling of fatty acids content (C16:0; C18:0; C18:1; C18:2; C18:3 and C22:1), alpha-tocopherol, gamma-tocopherol and total tocopherols, according to the data of production year and winter rapeseed genotype. The developed models exerted high-quality anticipation features, showing high r2 during the training cycle. The best fit between the modelled and measured traits for ANN model was observed for erucic acid content. RFR modelling for all fatty acids was more effective than ANN model, with the highest precision for palmitic, stearic, and oleic fatty acids (r2>0.9). This study emphasized the possibility of using ANN and RFR models to model winter rapeseed quality traits.
T2  - Journal of Food Composition and Analysis
T1  - Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed
VL  - 115
DO  - 10.1016/j.jfca.2022.105020
UR  - conv_1066
ER  - 

@article{
author = "Rajković, Dragana and Marjanovic Jeromela, Ana and Pezo, Lato and Lončar, Biljana and Grahovac, Nada and Kondic Spika, Ankica",
year = "2023",
abstract = "With the aid of models used in artificial intelligence, a wide range of data can be processed quickly with high accuracy. The quality of rapeseed oil from 40 genotypes cultivated during four consecutive years was analysed. Two machine learning techniques (artificial neural network - ANN, and random forest regression - RFR) were applied for the modelling of fatty acids content (C16:0; C18:0; C18:1; C18:2; C18:3 and C22:1), alpha-tocopherol, gamma-tocopherol and total tocopherols, according to the data of production year and winter rapeseed genotype. The developed models exerted high-quality anticipation features, showing high r2 during the training cycle. The best fit between the modelled and measured traits for ANN model was observed for erucic acid content. RFR modelling for all fatty acids was more effective than ANN model, with the highest precision for palmitic, stearic, and oleic fatty acids (r2>0.9). This study emphasized the possibility of using ANN and RFR models to model winter rapeseed quality traits.",
journal = "Journal of Food Composition and Analysis",
title = "Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed",
volume = "115",
doi = "10.1016/j.jfca.2022.105020",
url = "conv_1066"
}

Rajković, D., Marjanovic Jeromela, A., Pezo, L., Lončar, B., Grahovac, N.,& Kondic Spika, A.. (2023). Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed. in Journal of Food Composition and Analysis, 115.
https://doi.org/10.1016/j.jfca.2022.105020
conv_1066

Rajković D, Marjanovic Jeromela A, Pezo L, Lončar B, Grahovac N, Kondic Spika A. Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed. in Journal of Food Composition and Analysis. 2023;115.
doi:10.1016/j.jfca.2022.105020
conv_1066 .

Rajković, Dragana, Marjanovic Jeromela, Ana, Pezo, Lato, Lončar, Biljana, Grahovac, Nada, Kondic Spika, Ankica, "Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed" in Journal of Food Composition and Analysis, 115 (2023),
https://doi.org/10.1016/j.jfca.2022.105020 .,
conv_1066 .

TY  - JOUR
AU  - Brandić, Ivan
AU  - Pezo, Lato
AU  - Bilandžija, Nikola
AU  - Peter, Anamarija
AU  - Surić, Jona
AU  - Voca, Neven
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/982
AB  - The aim of this study was to investigate the potential of using structural analysis parameters for estimating the higher heating value (HHV) of biomass by obtaining information on the composition of cellulose, lignin, and hemicellulose. To achieve this goal, several nonlinear mathematical models were developed, including polynomials, support vector machines (SVMs), random forest regression (RFR) and artificial neural networks (ANN) for predicting HHV. The performed statistical analysis “goodness of fit” showed that the ANN model has the best performance in terms of coefficient of determination (R2 = 0.90) and the lowest level of model error for the parameters X2 (0.25), RMSE (0.50), and MPE (2.22). Thus, the ANN model was identified as the most appropriate model for determining the HHV of different biomasses based on the specified input parameters. In conclusion, the results of this study demonstrate the potential of using structural analysis parameters as input for HHV modeling, which is a promising approach for the field of biomass energy production. The development of the model ANN and the comparative analysis of the different models provide important insights for future research in this field.
PB  - MDPI
T2  - Mathematics
T1  - Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass
IS  - 9
VL  - 11
DO  - 10.3390/math11092098
UR  - conv_1118
ER  - 

@article{
author = "Brandić, Ivan and Pezo, Lato and Bilandžija, Nikola and Peter, Anamarija and Surić, Jona and Voca, Neven",
year = "2023",
abstract = "The aim of this study was to investigate the potential of using structural analysis parameters for estimating the higher heating value (HHV) of biomass by obtaining information on the composition of cellulose, lignin, and hemicellulose. To achieve this goal, several nonlinear mathematical models were developed, including polynomials, support vector machines (SVMs), random forest regression (RFR) and artificial neural networks (ANN) for predicting HHV. The performed statistical analysis “goodness of fit” showed that the ANN model has the best performance in terms of coefficient of determination (R2 = 0.90) and the lowest level of model error for the parameters X2 (0.25), RMSE (0.50), and MPE (2.22). Thus, the ANN model was identified as the most appropriate model for determining the HHV of different biomasses based on the specified input parameters. In conclusion, the results of this study demonstrate the potential of using structural analysis parameters as input for HHV modeling, which is a promising approach for the field of biomass energy production. The development of the model ANN and the comparative analysis of the different models provide important insights for future research in this field.",
publisher = "MDPI",
journal = "Mathematics",
title = "Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass",
number = "9",
volume = "11",
doi = "10.3390/math11092098",
url = "conv_1118"
}

Brandić, I., Pezo, L., Bilandžija, N., Peter, A., Surić, J.,& Voca, N.. (2023). Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass. in Mathematics
MDPI., 11(9).
https://doi.org/10.3390/math11092098
conv_1118

Brandić I, Pezo L, Bilandžija N, Peter A, Surić J, Voca N. Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass. in Mathematics. 2023;11(9).
doi:10.3390/math11092098
conv_1118 .

Brandić, Ivan, Pezo, Lato, Bilandžija, Nikola, Peter, Anamarija, Surić, Jona, Voca, Neven, "Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass" in Mathematics, 11, no. 9 (2023),
https://doi.org/10.3390/math11092098 .,
conv_1118 .

TY  - JOUR
AU  - Vasić, Milica V.
AU  - Goel, Gaurav
AU  - Dubale, Mandefrot
AU  - Živković, Slavica
AU  - Trivunić, Milan
AU  - Pezo, Milada
AU  - Pezo, Lato
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/981
AB  - The main idea of the present study was to investigate the impact of the ongoing world crisis on the socio-economic issues in Serbia concerning building materials usage and purchase. This research fills in the gaps in the literature and contributes to the comprehension of how the crisis has affected salaries, market pricing, and materials consumption in the building sector. The data are gathered through a questionnaire and analyzed using a statistical methodology (frequencies, descriptive statistics, and Spearman's correlations). Most of the former studies investigated the surveys conducted on specialists in the field, while this study analyzed the perspectives of random people. Socio-demographic issues are analyzed along with materials consumption before and after the crisis. A special emphasis is given to ecological awareness and novel materials usage. Additionally, it captures a broad shift in the economy and ecological consciousness in a developing country. The majority of respondents are open to using novel building materials and products, but their choice would largely be influenced by cost, the amount of effort involved, and their understanding of the advantages. Statistical approaches revealed that the crisis has a considerable impact on the markets for construction and building supplies, altering consumers' decisions when purchasing. This contribution lays the groundwork for developing countries in the modern world to improve sustainability and adopt circular thinking. Professionals in Serbia need to have a more eco-aware mindset and enhance how they provide pertinent information to potential clients. This study is limited by the number of respondents. For future mathematical modeling and forecasting, more answerers are needed.
PB  - MDPI AG
T2  - Sustainability
T1  - Socio-Economic Analysis of the Construction and Building Materials' Usage-Ecological Awareness in the Case of Serbia
IS  - 5
VL  - 15
DO  - 10.3390/su15054080
UR  - conv_1088
ER  - 

@article{
author = "Vasić, Milica V. and Goel, Gaurav and Dubale, Mandefrot and Živković, Slavica and Trivunić, Milan and Pezo, Milada and Pezo, Lato",
year = "2023",
abstract = "The main idea of the present study was to investigate the impact of the ongoing world crisis on the socio-economic issues in Serbia concerning building materials usage and purchase. This research fills in the gaps in the literature and contributes to the comprehension of how the crisis has affected salaries, market pricing, and materials consumption in the building sector. The data are gathered through a questionnaire and analyzed using a statistical methodology (frequencies, descriptive statistics, and Spearman's correlations). Most of the former studies investigated the surveys conducted on specialists in the field, while this study analyzed the perspectives of random people. Socio-demographic issues are analyzed along with materials consumption before and after the crisis. A special emphasis is given to ecological awareness and novel materials usage. Additionally, it captures a broad shift in the economy and ecological consciousness in a developing country. The majority of respondents are open to using novel building materials and products, but their choice would largely be influenced by cost, the amount of effort involved, and their understanding of the advantages. Statistical approaches revealed that the crisis has a considerable impact on the markets for construction and building supplies, altering consumers' decisions when purchasing. This contribution lays the groundwork for developing countries in the modern world to improve sustainability and adopt circular thinking. Professionals in Serbia need to have a more eco-aware mindset and enhance how they provide pertinent information to potential clients. This study is limited by the number of respondents. For future mathematical modeling and forecasting, more answerers are needed.",
publisher = "MDPI AG",
journal = "Sustainability",
title = "Socio-Economic Analysis of the Construction and Building Materials' Usage-Ecological Awareness in the Case of Serbia",
number = "5",
volume = "15",
doi = "10.3390/su15054080",
url = "conv_1088"
}

Vasić, M. V., Goel, G., Dubale, M., Živković, S., Trivunić, M., Pezo, M.,& Pezo, L.. (2023). Socio-Economic Analysis of the Construction and Building Materials' Usage-Ecological Awareness in the Case of Serbia. in Sustainability
MDPI AG., 15(5).
https://doi.org/10.3390/su15054080
conv_1088

Vasić MV, Goel G, Dubale M, Živković S, Trivunić M, Pezo M, Pezo L. Socio-Economic Analysis of the Construction and Building Materials' Usage-Ecological Awareness in the Case of Serbia. in Sustainability. 2023;15(5).
doi:10.3390/su15054080
conv_1088 .

Vasić, Milica V., Goel, Gaurav, Dubale, Mandefrot, Živković, Slavica, Trivunić, Milan, Pezo, Milada, Pezo, Lato, "Socio-Economic Analysis of the Construction and Building Materials' Usage-Ecological Awareness in the Case of Serbia" in Sustainability, 15, no. 5 (2023),
https://doi.org/10.3390/su15054080 .,
conv_1088 .

TY  - JOUR
AU  - Erceg, Tamara
AU  - Sovljanski, Olja
AU  - Stupar, Alena
AU  - Ugarković, Jovana
AU  - Aćimović, Milica
AU  - Pezo, Lato
AU  - Tomić, Ana
AU  - Todosijević, Marina
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/976
AB  - Biopolymer-based films present an ideal matrix for the incorporation of active substances such as antimicrobial agents, giving active packaging a framework of green chemistry and a step forward in food packaging technology. The chitosan-gelatine active coating has been prepared using lemongrass oil as an antimicrobial compound applying a different approach. Instead of surfactants, to achieve compatibilization of compounds, beta-cyclodextrin was used to encapsulate lemongrass oil. The antimicrobial effect was assessed using the dip-coating method on freshly harvested cherry tomatoes artificially contaminated by Penicillium aurantiogriseum during 20 days of cold storage. According to the evaluation of the antimicrobial effect of coating formulation on cherry tomato samples, which was mathematically assessed by predictive kinetic models and digital imaging, the applied coating formulation was found to be very effective since the development of fungal contamination for active-coated samples was observed for 20 days.
T2  - International Journal of Biological Macromolecules
T1  - A comprehensive approach to chitosan-gelatine edible coating with beta-cyclodextrin/lemongrass essential oil inclusion complex - Characterization and food application
EP  - 410
SP  - 400
VL  - 228
DO  - 10.1016/j.ijbiomac.2022.12.132
UR  - conv_1072
ER  - 

@article{
author = "Erceg, Tamara and Sovljanski, Olja and Stupar, Alena and Ugarković, Jovana and Aćimović, Milica and Pezo, Lato and Tomić, Ana and Todosijević, Marina",
year = "2023",
abstract = "Biopolymer-based films present an ideal matrix for the incorporation of active substances such as antimicrobial agents, giving active packaging a framework of green chemistry and a step forward in food packaging technology. The chitosan-gelatine active coating has been prepared using lemongrass oil as an antimicrobial compound applying a different approach. Instead of surfactants, to achieve compatibilization of compounds, beta-cyclodextrin was used to encapsulate lemongrass oil. The antimicrobial effect was assessed using the dip-coating method on freshly harvested cherry tomatoes artificially contaminated by Penicillium aurantiogriseum during 20 days of cold storage. According to the evaluation of the antimicrobial effect of coating formulation on cherry tomato samples, which was mathematically assessed by predictive kinetic models and digital imaging, the applied coating formulation was found to be very effective since the development of fungal contamination for active-coated samples was observed for 20 days.",
journal = "International Journal of Biological Macromolecules",
title = "A comprehensive approach to chitosan-gelatine edible coating with beta-cyclodextrin/lemongrass essential oil inclusion complex - Characterization and food application",
pages = "410-400",
volume = "228",
doi = "10.1016/j.ijbiomac.2022.12.132",
url = "conv_1072"
}

Erceg, T., Sovljanski, O., Stupar, A., Ugarković, J., Aćimović, M., Pezo, L., Tomić, A.,& Todosijević, M.. (2023). A comprehensive approach to chitosan-gelatine edible coating with beta-cyclodextrin/lemongrass essential oil inclusion complex - Characterization and food application. in International Journal of Biological Macromolecules, 228, 400-410.
https://doi.org/10.1016/j.ijbiomac.2022.12.132
conv_1072

Erceg T, Sovljanski O, Stupar A, Ugarković J, Aćimović M, Pezo L, Tomić A, Todosijević M. A comprehensive approach to chitosan-gelatine edible coating with beta-cyclodextrin/lemongrass essential oil inclusion complex - Characterization and food application. in International Journal of Biological Macromolecules. 2023;228:400-410.
doi:10.1016/j.ijbiomac.2022.12.132
conv_1072 .

Erceg, Tamara, Sovljanski, Olja, Stupar, Alena, Ugarković, Jovana, Aćimović, Milica, Pezo, Lato, Tomić, Ana, Todosijević, Marina, "A comprehensive approach to chitosan-gelatine edible coating with beta-cyclodextrin/lemongrass essential oil inclusion complex - Characterization and food application" in International Journal of Biological Macromolecules, 228 (2023):400-410,
https://doi.org/10.1016/j.ijbiomac.2022.12.132 .,
conv_1072 .

TY  - JOUR
AU  - Fotirić-Aksić, Milica
AU  - Tešić, Živoslav
AU  - Kalaba, Milica
AU  - Cirić, Ivanka
AU  - Pezo, Lato
AU  - Lončar, Biljana
AU  - Gašić, Uroš
AU  - Dojčinović, Biljana
AU  - Tosti, Tomislav
AU  - Meland, Mekjell
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/975
AB  - The aim of this study was to find the chemical parameters for the differentiation of plum cultivars grown along the fjord areas of Western Norway and Eastern Norway, having specific agroclimatic conditions. Chemical analysis of the fruits confirmed the contents of 13 quantified elements, 22 sugar compounds, 11 organic acids, 19 phenolic compounds, and antioxidant activity in 68 plum cultivars. Dominated contents were noted for nitrogen (with the maximum mean value of 3.11%), potassium (8055.80 mg/kg), and phosphorous (7878.88 mg/kg). Averagely, the highest level of sugars was determined for glucose (244.46 g/kg), fructose (197.92 g/kg), sucrose (208.25 g/kg), and sorbitol (98.02 g/kg), organic acids for malic acid (24.06 g/kg), and for polyphenol compounds were 5-O-caffeoylquinic acid (66.31 mg/kg), and rutin (58.06 mg/kg). Applied principal component analysis has been useful for distinguishing the plum cultivars from three areas in Norway where copper, iron, potassium, magnesium, manganese, and sodium; sucrose, ribose, maltose, and raffinose; p-hydroxybenzoic acid, rutin, ferulic acid, kaempferol 7-O-glucoside, p-coumaric acid, and 5-O-caffeoylquinic acid were the most influential. In regard to human health and future breeding work that will have the aim to produce functional food with high health-related compounds, the plum cultivar 'Mallard' should be underlined due to the high level of elements, 'Valor' due to high sugar content, 'Helgoyplomme' due to content of organic acids, and 'Diamond' due to the content of phenolic compounds.
PB  - MDPI AG
T2  - Horticulturae
T1  - Breakthrough Analysis of Chemical Composition and Applied Chemometrics of European Plum Cultivars Grown in Norway
IS  - 4
VL  - 9
DO  - 10.3390/horticulturae9040477
UR  - conv_1100
ER  - 

@article{
author = "Fotirić-Aksić, Milica and Tešić, Živoslav and Kalaba, Milica and Cirić, Ivanka and Pezo, Lato and Lončar, Biljana and Gašić, Uroš and Dojčinović, Biljana and Tosti, Tomislav and Meland, Mekjell",
year = "2023",
abstract = "The aim of this study was to find the chemical parameters for the differentiation of plum cultivars grown along the fjord areas of Western Norway and Eastern Norway, having specific agroclimatic conditions. Chemical analysis of the fruits confirmed the contents of 13 quantified elements, 22 sugar compounds, 11 organic acids, 19 phenolic compounds, and antioxidant activity in 68 plum cultivars. Dominated contents were noted for nitrogen (with the maximum mean value of 3.11%), potassium (8055.80 mg/kg), and phosphorous (7878.88 mg/kg). Averagely, the highest level of sugars was determined for glucose (244.46 g/kg), fructose (197.92 g/kg), sucrose (208.25 g/kg), and sorbitol (98.02 g/kg), organic acids for malic acid (24.06 g/kg), and for polyphenol compounds were 5-O-caffeoylquinic acid (66.31 mg/kg), and rutin (58.06 mg/kg). Applied principal component analysis has been useful for distinguishing the plum cultivars from three areas in Norway where copper, iron, potassium, magnesium, manganese, and sodium; sucrose, ribose, maltose, and raffinose; p-hydroxybenzoic acid, rutin, ferulic acid, kaempferol 7-O-glucoside, p-coumaric acid, and 5-O-caffeoylquinic acid were the most influential. In regard to human health and future breeding work that will have the aim to produce functional food with high health-related compounds, the plum cultivar 'Mallard' should be underlined due to the high level of elements, 'Valor' due to high sugar content, 'Helgoyplomme' due to content of organic acids, and 'Diamond' due to the content of phenolic compounds.",
publisher = "MDPI AG",
journal = "Horticulturae",
title = "Breakthrough Analysis of Chemical Composition and Applied Chemometrics of European Plum Cultivars Grown in Norway",
number = "4",
volume = "9",
doi = "10.3390/horticulturae9040477",
url = "conv_1100"
}

Fotirić-Aksić, M., Tešić, Ž., Kalaba, M., Cirić, I., Pezo, L., Lončar, B., Gašić, U., Dojčinović, B., Tosti, T.,& Meland, M.. (2023). Breakthrough Analysis of Chemical Composition and Applied Chemometrics of European Plum Cultivars Grown in Norway. in Horticulturae
MDPI AG., 9(4).
https://doi.org/10.3390/horticulturae9040477
conv_1100

Fotirić-Aksić M, Tešić Ž, Kalaba M, Cirić I, Pezo L, Lončar B, Gašić U, Dojčinović B, Tosti T, Meland M. Breakthrough Analysis of Chemical Composition and Applied Chemometrics of European Plum Cultivars Grown in Norway. in Horticulturae. 2023;9(4).
doi:10.3390/horticulturae9040477
conv_1100 .

Fotirić-Aksić, Milica, Tešić, Živoslav, Kalaba, Milica, Cirić, Ivanka, Pezo, Lato, Lončar, Biljana, Gašić, Uroš, Dojčinović, Biljana, Tosti, Tomislav, Meland, Mekjell, "Breakthrough Analysis of Chemical Composition and Applied Chemometrics of European Plum Cultivars Grown in Norway" in Horticulturae, 9, no. 4 (2023),
https://doi.org/10.3390/horticulturae9040477 .,
conv_1100 .

TY  - JOUR
AU  - Tomić, Ana
AU  - Sovljanski, Olja
AU  - Nikolić, Visnja
AU  - Pezo, Lato
AU  - Aćimović, Milica
AU  - Cvetković, Mirjana
AU  - Stanojev, Jovana
AU  - Kuzmanović, Nebojša
AU  - Markov, Siniša
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/972
AB  - The main challenge in controlling the microbiological contamination of historical paper is finding an adequate method that includes the use of cost-effective, harmless, and non-toxic biocides whose effectiveness is maintained over time and without adverse effects on cultural heritage and human health. Therefore, this study demonstrated the possibility of using a non-invasive method of historical paper conservation based on plant essential oils (EOs) application. Evaluation of antimicrobial effects of different EOs (lemongrass, oregano, rosemary, peppermint, and eucalyptus) was conducted against Cladosporium cladosporoides, Aspergillus fumigatus, and Penicillium chrysogenum, which are commonly found on archive papers. Using a mixture of oregano, lemongrass and peppermint in ratio 1:1:1, the lower minimal inhibition concentration (0.78%) and better efficiency during a vapour test at the highest tested distance (5.5 cm) compared with individual EOs was proven. At the final step, this EOs mixture was used in the in situ conservation of historical paper samples obtained from the Archives of Vojvodina. According to the SEM imaging, the applied EOs mixture demonstrates complete efficiency in the inhibition of fungi colonization of archive papers, since fungal growth was not observed on samples, unlike the control samples.
PB  - MDPI AG
T2  - Antibiotics-Basel
T1  - Screening of Antifungal Activity of Essential Oils in Controlling Biocontamination of Historical Papers in Archives
IS  - 1
VL  - 12
DO  - 10.3390/antibiotics12010103
UR  - conv_1074
ER  - 

@article{
author = "Tomić, Ana and Sovljanski, Olja and Nikolić, Visnja and Pezo, Lato and Aćimović, Milica and Cvetković, Mirjana and Stanojev, Jovana and Kuzmanović, Nebojša and Markov, Siniša",
year = "2023",
abstract = "The main challenge in controlling the microbiological contamination of historical paper is finding an adequate method that includes the use of cost-effective, harmless, and non-toxic biocides whose effectiveness is maintained over time and without adverse effects on cultural heritage and human health. Therefore, this study demonstrated the possibility of using a non-invasive method of historical paper conservation based on plant essential oils (EOs) application. Evaluation of antimicrobial effects of different EOs (lemongrass, oregano, rosemary, peppermint, and eucalyptus) was conducted against Cladosporium cladosporoides, Aspergillus fumigatus, and Penicillium chrysogenum, which are commonly found on archive papers. Using a mixture of oregano, lemongrass and peppermint in ratio 1:1:1, the lower minimal inhibition concentration (0.78%) and better efficiency during a vapour test at the highest tested distance (5.5 cm) compared with individual EOs was proven. At the final step, this EOs mixture was used in the in situ conservation of historical paper samples obtained from the Archives of Vojvodina. According to the SEM imaging, the applied EOs mixture demonstrates complete efficiency in the inhibition of fungi colonization of archive papers, since fungal growth was not observed on samples, unlike the control samples.",
publisher = "MDPI AG",
journal = "Antibiotics-Basel",
title = "Screening of Antifungal Activity of Essential Oils in Controlling Biocontamination of Historical Papers in Archives",
number = "1",
volume = "12",
doi = "10.3390/antibiotics12010103",
url = "conv_1074"
}

Tomić, A., Sovljanski, O., Nikolić, V., Pezo, L., Aćimović, M., Cvetković, M., Stanojev, J., Kuzmanović, N.,& Markov, S.. (2023). Screening of Antifungal Activity of Essential Oils in Controlling Biocontamination of Historical Papers in Archives. in Antibiotics-Basel
MDPI AG., 12(1).
https://doi.org/10.3390/antibiotics12010103
conv_1074

Tomić A, Sovljanski O, Nikolić V, Pezo L, Aćimović M, Cvetković M, Stanojev J, Kuzmanović N, Markov S. Screening of Antifungal Activity of Essential Oils in Controlling Biocontamination of Historical Papers in Archives. in Antibiotics-Basel. 2023;12(1).
doi:10.3390/antibiotics12010103
conv_1074 .

Tomić, Ana, Sovljanski, Olja, Nikolić, Visnja, Pezo, Lato, Aćimović, Milica, Cvetković, Mirjana, Stanojev, Jovana, Kuzmanović, Nebojša, Markov, Siniša, "Screening of Antifungal Activity of Essential Oils in Controlling Biocontamination of Historical Papers in Archives" in Antibiotics-Basel, 12, no. 1 (2023),
https://doi.org/10.3390/antibiotics12010103 .,
conv_1074 .

TY  - JOUR
AU  - Vunduk, Jovana
AU  - Klaus, Anita
AU  - Lazić, Vesna
AU  - Kozarski, Maja
AU  - Radić, Danka
AU  - Sovljanski, Olja
AU  - Pezo, Lato
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/971
AB  - The problem of microbial biofilms has come to the fore alongside food, pharmaceutical, and healthcare industrialization. The development of new antibiofilm products has become urgent, but it includes bioprospecting and is time and money-consuming. Contemporary efforts are directed at the pursuit of effective compounds of natural origin, also known as "green" agents. Mushrooms appear to be a possible new source of antibiofilm compounds, as has been demonstrated recently. The existing modeling methods are directed toward predicting bacterial biofilm formation, not in the presence of antibiofilm materials. Moreover, the modeling is almost exclusively targeted at biofilms in healthcare, while modeling related to the food industry remains under-researched. The present study applied an Artificial Neural Network (ANN) model to analyze the anti-adhesion and anti-biofilm-forming effects of 40 extracts from 20 mushroom species against two very important food-borne bacterial species for food and food-related industries-Listeria monocytogenes and Salmonella enteritidis. The models developed in this study exhibited high prediction quality, as indicated by high r(2) values during the training cycle. The best fit between the modeled and measured values was observed for the inhibition of adhesion. This study provides a valuable contribution to the field, supporting industrial settings during the initial stage of biofilm formation, when these communities are the most vulnerable, and promoting innovative and improved safety management.
PB  - MDPI AG
T2  - Antibiotics-Basel
T1  - Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens
IS  - 3
VL  - 12
DO  - 10.3390/antibiotics12030627
UR  - conv_1099
ER  - 

@article{
author = "Vunduk, Jovana and Klaus, Anita and Lazić, Vesna and Kozarski, Maja and Radić, Danka and Sovljanski, Olja and Pezo, Lato",
year = "2023",
abstract = "The problem of microbial biofilms has come to the fore alongside food, pharmaceutical, and healthcare industrialization. The development of new antibiofilm products has become urgent, but it includes bioprospecting and is time and money-consuming. Contemporary efforts are directed at the pursuit of effective compounds of natural origin, also known as "green" agents. Mushrooms appear to be a possible new source of antibiofilm compounds, as has been demonstrated recently. The existing modeling methods are directed toward predicting bacterial biofilm formation, not in the presence of antibiofilm materials. Moreover, the modeling is almost exclusively targeted at biofilms in healthcare, while modeling related to the food industry remains under-researched. The present study applied an Artificial Neural Network (ANN) model to analyze the anti-adhesion and anti-biofilm-forming effects of 40 extracts from 20 mushroom species against two very important food-borne bacterial species for food and food-related industries-Listeria monocytogenes and Salmonella enteritidis. The models developed in this study exhibited high prediction quality, as indicated by high r(2) values during the training cycle. The best fit between the modeled and measured values was observed for the inhibition of adhesion. This study provides a valuable contribution to the field, supporting industrial settings during the initial stage of biofilm formation, when these communities are the most vulnerable, and promoting innovative and improved safety management.",
publisher = "MDPI AG",
journal = "Antibiotics-Basel",
title = "Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens",
number = "3",
volume = "12",
doi = "10.3390/antibiotics12030627",
url = "conv_1099"
}

Vunduk, J., Klaus, A., Lazić, V., Kozarski, M., Radić, D., Sovljanski, O.,& Pezo, L.. (2023). Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens. in Antibiotics-Basel
MDPI AG., 12(3).
https://doi.org/10.3390/antibiotics12030627
conv_1099

Vunduk J, Klaus A, Lazić V, Kozarski M, Radić D, Sovljanski O, Pezo L. Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens. in Antibiotics-Basel. 2023;12(3).
doi:10.3390/antibiotics12030627
conv_1099 .

Vunduk, Jovana, Klaus, Anita, Lazić, Vesna, Kozarski, Maja, Radić, Danka, Sovljanski, Olja, Pezo, Lato, "Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens" in Antibiotics-Basel, 12, no. 3 (2023),
https://doi.org/10.3390/antibiotics12030627 .,
conv_1099 .

TY  - JOUR
AU  - Demir, Hasan
AU  - Demir, Hande
AU  - Lončar, Biljana
AU  - Nićetin, Milica
AU  - Pezo, Lato
AU  - Yilmaz, Fatma
PY  - 2023
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/968
AB  - This study aimed to investigate the drying kinetics of capers at different temperatures and to examine the morphological changes of capers during the drying and rehydration processes. Computer-aided image processing and Artificial Neural Network models (ANN) were used to analyze the shrinkage and moisture ratio of capers (drying) and the expansion of capers (rehydration). Lewis, Page, Fick's law, and logarithmic models were investigated to describe the conventional drying kinetics of capers at 50, 60, and 70 degrees C; the logarithmic model was shown to be the best describing model (r(2): 0.9996, 0.9996 and 0.9981, respectively). Effective diffusivities varied between 1.91 x 10(-10) and 2.62 x 10(-10) m(2)/s for the temperature range. The activation energy was 14.572 kJ/mol. Image processing revealed that diameter reduction rates were 1 x 10(-4) mm/s for 50 and 70 & DEG;C and 7 x 10(-5) mm/s for 60 degrees C. ANN was applied using multilayer perceptron models with three layers (input: ANN1, hidden: ANN2, and output: ANN3) which were sufficiently valid for predicting the experimental parameters (r(2): 0.9992, 0.9915, and 0.8484, respectively). All morphological properties were reduced with drying, and shrinkage of capers was increased proportionally with the moisture content. The Global Sensitivity Analysis recognized treatment time as the most influential parameter affecting the moisture ratio and the caper diameter changes. Practical applications One of the major problems for humans has been to improve food preservation techniques for long-term storage. The major scope of industry is the drying of fruits and/or vegetables to produce dried foods with high quality and a long shelf life. To the best of our knowledge, drying of capers regarding the drying kinetics, modeling and quality changes has not been published to date. In this study, goal was to better understand drying kinetics and geometric changes that occur to capers during the dehydration and rehydration processes at various drying temperatures. Quantitative information regarding geometrical changes to capers was supplied by the image processing of the acquired pictures, which enabled rapid monitoring of physical changes during dehydration and rehydration. The remarked kinetic model, ANN model, and Quantitative information regarding geometrical changes are valuable information for researchers studying on drying of food and large-scale dryer designers.
T2  - Journal of Food Process Engineering
T1  - Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes
IS  - 2
VL  - 46
DO  - 10.1111/jfpe.14249
UR  - conv_1068
ER  - 

@article{
author = "Demir, Hasan and Demir, Hande and Lončar, Biljana and Nićetin, Milica and Pezo, Lato and Yilmaz, Fatma",
year = "2023",
abstract = "This study aimed to investigate the drying kinetics of capers at different temperatures and to examine the morphological changes of capers during the drying and rehydration processes. Computer-aided image processing and Artificial Neural Network models (ANN) were used to analyze the shrinkage and moisture ratio of capers (drying) and the expansion of capers (rehydration). Lewis, Page, Fick's law, and logarithmic models were investigated to describe the conventional drying kinetics of capers at 50, 60, and 70 degrees C; the logarithmic model was shown to be the best describing model (r(2): 0.9996, 0.9996 and 0.9981, respectively). Effective diffusivities varied between 1.91 x 10(-10) and 2.62 x 10(-10) m(2)/s for the temperature range. The activation energy was 14.572 kJ/mol. Image processing revealed that diameter reduction rates were 1 x 10(-4) mm/s for 50 and 70 & DEG;C and 7 x 10(-5) mm/s for 60 degrees C. ANN was applied using multilayer perceptron models with three layers (input: ANN1, hidden: ANN2, and output: ANN3) which were sufficiently valid for predicting the experimental parameters (r(2): 0.9992, 0.9915, and 0.8484, respectively). All morphological properties were reduced with drying, and shrinkage of capers was increased proportionally with the moisture content. The Global Sensitivity Analysis recognized treatment time as the most influential parameter affecting the moisture ratio and the caper diameter changes. Practical applications One of the major problems for humans has been to improve food preservation techniques for long-term storage. The major scope of industry is the drying of fruits and/or vegetables to produce dried foods with high quality and a long shelf life. To the best of our knowledge, drying of capers regarding the drying kinetics, modeling and quality changes has not been published to date. In this study, goal was to better understand drying kinetics and geometric changes that occur to capers during the dehydration and rehydration processes at various drying temperatures. Quantitative information regarding geometrical changes to capers was supplied by the image processing of the acquired pictures, which enabled rapid monitoring of physical changes during dehydration and rehydration. The remarked kinetic model, ANN model, and Quantitative information regarding geometrical changes are valuable information for researchers studying on drying of food and large-scale dryer designers.",
journal = "Journal of Food Process Engineering",
title = "Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes",
number = "2",
volume = "46",
doi = "10.1111/jfpe.14249",
url = "conv_1068"
}

Demir, H., Demir, H., Lončar, B., Nićetin, M., Pezo, L.,& Yilmaz, F.. (2023). Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes. in Journal of Food Process Engineering, 46(2).
https://doi.org/10.1111/jfpe.14249
conv_1068

Demir H, Demir H, Lončar B, Nićetin M, Pezo L, Yilmaz F. Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes. in Journal of Food Process Engineering. 2023;46(2).
doi:10.1111/jfpe.14249
conv_1068 .

Demir, Hasan, Demir, Hande, Lončar, Biljana, Nićetin, Milica, Pezo, Lato, Yilmaz, Fatma, "Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes" in Journal of Food Process Engineering, 46, no. 2 (2023),
https://doi.org/10.1111/jfpe.14249 .,
conv_1068 .

TY  - JOUR
AU  - Fotirić-Aksić, Milica
AU  - Nešović, Milica
AU  - Cirić, Ivanka
AU  - Tešić, Živoslav
AU  - Pezo, Lato
AU  - Tosti, Tomislav
AU  - Gašić, Uroš
AU  - Dojčinović, Biljana
AU  - Lončar, Biljana
AU  - Meland, Mekjell
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/941
AB  - Using modern analytical techniques, a comprehensive study of the chemical composition of fruits from apple cultivars grown in Western Norway during 2019 and 2020 was done. Metals, sugars, organic acids, antioxidant tests, and polyphenol content have been observed. In all investigated samples, the most dominant sugars were glucose, fructose, and sucrose. Among 11 tested organic acids, the dominant was malic acid, followed by citric and maleic acid. The most common metal was potassium, followed by magnesium and zinc. The quantification of polyphenols showed that among the 11 quantified polyphenols, chlorogenic acid, quercetin 3-O-rhamnoside, quercetin 3-O-glucoside, quercetin, and phlorizin were the most abundant. A detailed study of the polyphenolic profile of nine investigated apple samples provided 30 identified polyphenolic compounds from the class of hydroxybenzoic and hydroxycinnamic acids, flavonoids, and dihydrochalcones. In addition to the identified 3-O-caffeoylquinic acid, its two isomers of 5-O-caffeoylquinic acid and three esters were also found. Present polyphenols of the tested apples provided significant data on the quality of Norwegian apples, and they contribute to the distinguishing of these apple samples.
PB  - Frontiers Media S.A.
T2  - Frontiers in Nutrition
T1  - Polyphenolics and Chemical Profiles of Domestic Norwegian Apple (Malus x domestica Borkh.) Cultivars
VL  - 9
DO  - 10.3389/fnut.2022.941487
UR  - conv_1022
ER  - 

@article{
author = "Fotirić-Aksić, Milica and Nešović, Milica and Cirić, Ivanka and Tešić, Živoslav and Pezo, Lato and Tosti, Tomislav and Gašić, Uroš and Dojčinović, Biljana and Lončar, Biljana and Meland, Mekjell",
year = "2022",
abstract = "Using modern analytical techniques, a comprehensive study of the chemical composition of fruits from apple cultivars grown in Western Norway during 2019 and 2020 was done. Metals, sugars, organic acids, antioxidant tests, and polyphenol content have been observed. In all investigated samples, the most dominant sugars were glucose, fructose, and sucrose. Among 11 tested organic acids, the dominant was malic acid, followed by citric and maleic acid. The most common metal was potassium, followed by magnesium and zinc. The quantification of polyphenols showed that among the 11 quantified polyphenols, chlorogenic acid, quercetin 3-O-rhamnoside, quercetin 3-O-glucoside, quercetin, and phlorizin were the most abundant. A detailed study of the polyphenolic profile of nine investigated apple samples provided 30 identified polyphenolic compounds from the class of hydroxybenzoic and hydroxycinnamic acids, flavonoids, and dihydrochalcones. In addition to the identified 3-O-caffeoylquinic acid, its two isomers of 5-O-caffeoylquinic acid and three esters were also found. Present polyphenols of the tested apples provided significant data on the quality of Norwegian apples, and they contribute to the distinguishing of these apple samples.",
publisher = "Frontiers Media S.A.",
journal = "Frontiers in Nutrition",
title = "Polyphenolics and Chemical Profiles of Domestic Norwegian Apple (Malus x domestica Borkh.) Cultivars",
volume = "9",
doi = "10.3389/fnut.2022.941487",
url = "conv_1022"
}

Fotirić-Aksić, M., Nešović, M., Cirić, I., Tešić, Ž., Pezo, L., Tosti, T., Gašić, U., Dojčinović, B., Lončar, B.,& Meland, M.. (2022). Polyphenolics and Chemical Profiles of Domestic Norwegian Apple (Malus x domestica Borkh.) Cultivars. in Frontiers in Nutrition
Frontiers Media S.A.., 9.
https://doi.org/10.3389/fnut.2022.941487
conv_1022

Fotirić-Aksić M, Nešović M, Cirić I, Tešić Ž, Pezo L, Tosti T, Gašić U, Dojčinović B, Lončar B, Meland M. Polyphenolics and Chemical Profiles of Domestic Norwegian Apple (Malus x domestica Borkh.) Cultivars. in Frontiers in Nutrition. 2022;9.
doi:10.3389/fnut.2022.941487
conv_1022 .

Fotirić-Aksić, Milica, Nešović, Milica, Cirić, Ivanka, Tešić, Živoslav, Pezo, Lato, Tosti, Tomislav, Gašić, Uroš, Dojčinović, Biljana, Lončar, Biljana, Meland, Mekjell, "Polyphenolics and Chemical Profiles of Domestic Norwegian Apple (Malus x domestica Borkh.) Cultivars" in Frontiers in Nutrition, 9 (2022),
https://doi.org/10.3389/fnut.2022.941487 .,
conv_1022 .

TY  - JOUR
AU  - Đurović, Saša
AU  - Micić, Darko
AU  - Pezo, Lato
AU  - Radić, Danka
AU  - Bazarnova, Julia
AU  - Smyatskaya, Yulia A.
AU  - Blagojević, Stevan
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/916
AB  - In this study, the influence of the mowing and drying on the chemical profile, thermal behavior, antioxidant activity (DPPH, CUPRAC, FRAP, ABTS, HRSA, and TBARS), microbiological data (Candida albicans (ATCC 10231), Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Candida albicans (ATCC 10231), Bacillus subtilis (ATCC 6633), Proteus vulgaris (ATCC 13315), Proteus mirabilis (ATCC 14153) and Aspergillus niger (ATCC 16404) and cytotoxic activity of peppermint samples (HeLa, LS-174, A549, and MRC-5) was investigated. Chemical profiles showed that mowing did not have a significant impact on essential oil composition compared to drying. Menthone was the principal compound in essential oil from the fresh material, while menthol was the main compound in the samples from the dried ones. These differences influenced the biological activity of the samples, where fresh had better antioxidants, while dried had better antimicrobial activity. Thermal analysis showed that samples completely evaporated to about 120-123 degrees C in non-isothermal conditions, while in isothermal conditions the time required for complete evaporation was 20-30 min, depending on the sample. An artificial neural network model was developed, for the anticipation of antioxidant activity. These models showed good prediction properties (the r2 value during the training cycle for output variables was 1.000).
T2  - Industrial Crops and Products
T1  - Influence of the mowing and drying on the quality of the peppermint (Mentha x piperita L.) essential oil: Chemical profile, thermal properties, and biological activity
VL  - 177
DO  - 10.1016/j.indcrop.2021.114492
UR  - conv_980
ER  - 

@article{
author = "Đurović, Saša and Micić, Darko and Pezo, Lato and Radić, Danka and Bazarnova, Julia and Smyatskaya, Yulia A. and Blagojević, Stevan",
year = "2022",
abstract = "In this study, the influence of the mowing and drying on the chemical profile, thermal behavior, antioxidant activity (DPPH, CUPRAC, FRAP, ABTS, HRSA, and TBARS), microbiological data (Candida albicans (ATCC 10231), Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Candida albicans (ATCC 10231), Bacillus subtilis (ATCC 6633), Proteus vulgaris (ATCC 13315), Proteus mirabilis (ATCC 14153) and Aspergillus niger (ATCC 16404) and cytotoxic activity of peppermint samples (HeLa, LS-174, A549, and MRC-5) was investigated. Chemical profiles showed that mowing did not have a significant impact on essential oil composition compared to drying. Menthone was the principal compound in essential oil from the fresh material, while menthol was the main compound in the samples from the dried ones. These differences influenced the biological activity of the samples, where fresh had better antioxidants, while dried had better antimicrobial activity. Thermal analysis showed that samples completely evaporated to about 120-123 degrees C in non-isothermal conditions, while in isothermal conditions the time required for complete evaporation was 20-30 min, depending on the sample. An artificial neural network model was developed, for the anticipation of antioxidant activity. These models showed good prediction properties (the r2 value during the training cycle for output variables was 1.000).",
journal = "Industrial Crops and Products",
title = "Influence of the mowing and drying on the quality of the peppermint (Mentha x piperita L.) essential oil: Chemical profile, thermal properties, and biological activity",
volume = "177",
doi = "10.1016/j.indcrop.2021.114492",
url = "conv_980"
}

Đurović, S., Micić, D., Pezo, L., Radić, D., Bazarnova, J., Smyatskaya, Y. A.,& Blagojević, S.. (2022). Influence of the mowing and drying on the quality of the peppermint (Mentha x piperita L.) essential oil: Chemical profile, thermal properties, and biological activity. in Industrial Crops and Products, 177.
https://doi.org/10.1016/j.indcrop.2021.114492
conv_980

Đurović S, Micić D, Pezo L, Radić D, Bazarnova J, Smyatskaya YA, Blagojević S. Influence of the mowing and drying on the quality of the peppermint (Mentha x piperita L.) essential oil: Chemical profile, thermal properties, and biological activity. in Industrial Crops and Products. 2022;177.
doi:10.1016/j.indcrop.2021.114492
conv_980 .

Đurović, Saša, Micić, Darko, Pezo, Lato, Radić, Danka, Bazarnova, Julia, Smyatskaya, Yulia A., Blagojević, Stevan, "Influence of the mowing and drying on the quality of the peppermint (Mentha x piperita L.) essential oil: Chemical profile, thermal properties, and biological activity" in Industrial Crops and Products, 177 (2022),
https://doi.org/10.1016/j.indcrop.2021.114492 .,
conv_980 .

TY  - JOUR
AU  - Dragojlović, Danka
AU  - Đuragić, Olivera
AU  - Pezo, Lato
AU  - Popović, Ljiljana
AU  - Rakita, Slađana
AU  - Tomicić, Zorica
AU  - Spasevski, Nedeljka
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/905
AB  - Simple Summary Currently, the food industry is facing numerous problems related to the increase in the global human population resulting in an increase in the demand for livestock. Animal feed production, as the chain leader of food production, needs to reduce the utilization of commonly used feeds, such as soybean meal and fish meal, and replace them with more sustainable ones. The utilization of insects as an alternative sustainable feed in the upcoming years can be one of the solutions. Optimization of rearing conditions, which includes the choice of insect species, time of harvest, and proper insect diet, is highly desirable for wider insect mass production. Along with the optimization of rearing conditions, insect producers will be able to obtain the desirable biomass and nutritive composition of insect products with the minimization of production costs. With their desirable nutritional composition, super worms could be used in extended mass production. Additionally, in animal feed production, super worms and yellow mealworms can be used as a nutritional source and a promising alternative to traditional feed ingredients. However, the optimization of the rearing conditions is needed for wider use in the animal feed industry. Edible insects are acknowledged as a valuable nutritional source and promising alternative to traditional feed ingredients, while the optimization of rearing conditions is required for their wider utilization in the animal feed industry. The main goal of this study was to compare and optimize the rearing conditions of the two species' larvae and identify the most favorable nutritive composition of the full-fat larval meal. For that purpose, Tenebrio molitor (TM) and Zophobas morio (ZM) were reared on three different substrates and harvested after three time periods. An artificial neural network (ANN) with multi-objective optimization (MOO) was used to investigate the influence between the observed parameters as well as to optimize and determine rearing conditions. The optimization of the larval rearing conditions showed that the best nutritive composition of full-fat larval meal was obtained for ZM larvae reared on a mixture of cabbage, carrot and flaxseed and harvested after 104 days. The best nutritive composition contained 39.52% protein, 32% crude fat, 44.01% essential amino acids, 65.21 mg/100 g Ca and 651.15 mg/100 g P with a favorable ratio of 1.5 of n6/n3 fatty acids. Additionally, the incorporation of flaxseed in the larval diet resulted in an increase in C18:3n3 content in all samples.
PB  - MDPI AG
T2  - Animals
T1  - Comparison of Nutritional Profiles of Super Worm (Zophobas morio) and Yellow Mealworm (Tenebrio molitor) as Alternative Feeds Used in Animal Husbandry: Is Super Worm Superior?
IS  - 10
VL  - 12
DO  - 10.3390/ani12101277
UR  - conv_1012
ER  - 

@article{
author = "Dragojlović, Danka and Đuragić, Olivera and Pezo, Lato and Popović, Ljiljana and Rakita, Slađana and Tomicić, Zorica and Spasevski, Nedeljka",
year = "2022",
abstract = "Simple Summary Currently, the food industry is facing numerous problems related to the increase in the global human population resulting in an increase in the demand for livestock. Animal feed production, as the chain leader of food production, needs to reduce the utilization of commonly used feeds, such as soybean meal and fish meal, and replace them with more sustainable ones. The utilization of insects as an alternative sustainable feed in the upcoming years can be one of the solutions. Optimization of rearing conditions, which includes the choice of insect species, time of harvest, and proper insect diet, is highly desirable for wider insect mass production. Along with the optimization of rearing conditions, insect producers will be able to obtain the desirable biomass and nutritive composition of insect products with the minimization of production costs. With their desirable nutritional composition, super worms could be used in extended mass production. Additionally, in animal feed production, super worms and yellow mealworms can be used as a nutritional source and a promising alternative to traditional feed ingredients. However, the optimization of the rearing conditions is needed for wider use in the animal feed industry. Edible insects are acknowledged as a valuable nutritional source and promising alternative to traditional feed ingredients, while the optimization of rearing conditions is required for their wider utilization in the animal feed industry. The main goal of this study was to compare and optimize the rearing conditions of the two species' larvae and identify the most favorable nutritive composition of the full-fat larval meal. For that purpose, Tenebrio molitor (TM) and Zophobas morio (ZM) were reared on three different substrates and harvested after three time periods. An artificial neural network (ANN) with multi-objective optimization (MOO) was used to investigate the influence between the observed parameters as well as to optimize and determine rearing conditions. The optimization of the larval rearing conditions showed that the best nutritive composition of full-fat larval meal was obtained for ZM larvae reared on a mixture of cabbage, carrot and flaxseed and harvested after 104 days. The best nutritive composition contained 39.52% protein, 32% crude fat, 44.01% essential amino acids, 65.21 mg/100 g Ca and 651.15 mg/100 g P with a favorable ratio of 1.5 of n6/n3 fatty acids. Additionally, the incorporation of flaxseed in the larval diet resulted in an increase in C18:3n3 content in all samples.",
publisher = "MDPI AG",
journal = "Animals",
title = "Comparison of Nutritional Profiles of Super Worm (Zophobas morio) and Yellow Mealworm (Tenebrio molitor) as Alternative Feeds Used in Animal Husbandry: Is Super Worm Superior?",
number = "10",
volume = "12",
doi = "10.3390/ani12101277",
url = "conv_1012"
}

Dragojlović, D., Đuragić, O., Pezo, L., Popović, L., Rakita, S., Tomicić, Z.,& Spasevski, N.. (2022). Comparison of Nutritional Profiles of Super Worm (Zophobas morio) and Yellow Mealworm (Tenebrio molitor) as Alternative Feeds Used in Animal Husbandry: Is Super Worm Superior?. in Animals
MDPI AG., 12(10).
https://doi.org/10.3390/ani12101277
conv_1012

Dragojlović D, Đuragić O, Pezo L, Popović L, Rakita S, Tomicić Z, Spasevski N. Comparison of Nutritional Profiles of Super Worm (Zophobas morio) and Yellow Mealworm (Tenebrio molitor) as Alternative Feeds Used in Animal Husbandry: Is Super Worm Superior?. in Animals. 2022;12(10).
doi:10.3390/ani12101277
conv_1012 .

Dragojlović, Danka, Đuragić, Olivera, Pezo, Lato, Popović, Ljiljana, Rakita, Slađana, Tomicić, Zorica, Spasevski, Nedeljka, "Comparison of Nutritional Profiles of Super Worm (Zophobas morio) and Yellow Mealworm (Tenebrio molitor) as Alternative Feeds Used in Animal Husbandry: Is Super Worm Superior?" in Animals, 12, no. 10 (2022),
https://doi.org/10.3390/ani12101277 .,
conv_1012 .

TY  - JOUR
AU  - Đurović, Saša
AU  - Micić, Darko
AU  - Pezo, Lato
AU  - Radić, Danka
AU  - Bazarnova, Julia
AU  - Smyatskaya, Yulia A.
AU  - Blagojević, Stevan
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/894
AB  - In this study, influence of the extraction techniques on the quality of the sage essential oil was investigated. Obtained samples were analyzed for chemical composition by GC/MS, thermal properties by thermogravimetric analysis (TGA), and for biological activity: antioxidant (DPPH, CUPRAC, FRAP, ABTS, HRSA and TBARS), microbiological (Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus niger), and cytotoxic (HeLa, LS-174, A549 and MRC-5) activities. Chemical composition showed that viridiflorol was principal compound in all samples followed by camphor, thujones, and verticiol. MWD 400 W was the most potent antioxidant agent, D 200 W and MWD 400 W antimicrobial agents, while hydrodistallates (D 200 W and D 400 W) were the most potent cytotoxic agents. An artificial neural network model was developed for the antioxidant activity anticipation of analyzed samples. These models showed good prediction properties (the r2 value during training cycle for output variables was 0.998).
PB  - Elsevier
T2  - Food Chemistry-X
T1  - The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity
VL  - 13
DO  - 10.1016/j.fochx.2022.100213
UR  - conv_1000
ER  - 

@article{
author = "Đurović, Saša and Micić, Darko and Pezo, Lato and Radić, Danka and Bazarnova, Julia and Smyatskaya, Yulia A. and Blagojević, Stevan",
year = "2022",
abstract = "In this study, influence of the extraction techniques on the quality of the sage essential oil was investigated. Obtained samples were analyzed for chemical composition by GC/MS, thermal properties by thermogravimetric analysis (TGA), and for biological activity: antioxidant (DPPH, CUPRAC, FRAP, ABTS, HRSA and TBARS), microbiological (Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus niger), and cytotoxic (HeLa, LS-174, A549 and MRC-5) activities. Chemical composition showed that viridiflorol was principal compound in all samples followed by camphor, thujones, and verticiol. MWD 400 W was the most potent antioxidant agent, D 200 W and MWD 400 W antimicrobial agents, while hydrodistallates (D 200 W and D 400 W) were the most potent cytotoxic agents. An artificial neural network model was developed for the antioxidant activity anticipation of analyzed samples. These models showed good prediction properties (the r2 value during training cycle for output variables was 0.998).",
publisher = "Elsevier",
journal = "Food Chemistry-X",
title = "The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity",
volume = "13",
doi = "10.1016/j.fochx.2022.100213",
url = "conv_1000"
}

Đurović, S., Micić, D., Pezo, L., Radić, D., Bazarnova, J., Smyatskaya, Y. A.,& Blagojević, S.. (2022). The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity. in Food Chemistry-X
Elsevier., 13.
https://doi.org/10.1016/j.fochx.2022.100213
conv_1000

Đurović S, Micić D, Pezo L, Radić D, Bazarnova J, Smyatskaya YA, Blagojević S. The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity. in Food Chemistry-X. 2022;13.
doi:10.1016/j.fochx.2022.100213
conv_1000 .

Đurović, Saša, Micić, Darko, Pezo, Lato, Radić, Danka, Bazarnova, Julia, Smyatskaya, Yulia A., Blagojević, Stevan, "The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity" in Food Chemistry-X, 13 (2022),
https://doi.org/10.1016/j.fochx.2022.100213 .,
conv_1000 .

TY  - JOUR
AU  - Lubura, J
AU  - Pezo, Lato
AU  - Sandu, M.A
AU  - Voronova, V
AU  - Donsì, F
AU  - Šic Žlabur, J
AU  - Ribić, B
AU  - Peter, Anamarija
AU  - Surić, Jona
AU  - Brandić, Ivan
AU  - Klõga, M
AU  - Ostojić, Sanja
AU  - Pataro, G
AU  - Virsta, A
AU  - Oros, A.E
AU  - Micić, Darko
AU  - Đurović, Saša
AU  - De Feo, G
AU  - Procentese, A
AU  - Voca, Neven
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/872
AB  - In this study, an evaluation of food waste generation was conducted, using images taken before and after the daily meals of people aged between 20 and 30 years in Serbia, for the period between 1 January and 31 April in 2022. A convolutional neural network (CNN) was employed for the tasks of recognizing food images before the meal and estimating the percentage of food waste according to the photographs taken. Keeping in mind the vast variates and types of food available, the image recognition and validation of food items present a generally very challenging task. Nevertheless, deep learning has recently been shown to be a very potent image recognition procedure, while CNN presents a state-of-the-art method of deep learning. The CNN technique was implemented to the food detection and food waste estimation tasks throughout the parameter optimization procedure. The images of the most frequently encountered food items were collected from the internet to create an image dataset, covering 157 food categories, which was used to evaluate recognition performance. Each category included between 50 and 200 images, while the total number of images in the database reached 23,552. The CNN model presented good prediction capabilities, showing an accuracy of 0.988 and a loss of 0.102, after the network training cycle. The average food waste per meal, in the frame of the analysis in Serbia, was 21.3%, according to the images collected for food waste evaluation.
PB  - MDPI
T2  - Electronics (Switzerland)
T1  - Food Recognition and Food Waste Estimation Using Convolutional Neural Network
IS  - 22
VL  - 11
DO  - 10.3390/electronics11223746
UR  - conv_1125
ER  - 

@article{
author = "Lubura, J and Pezo, Lato and Sandu, M.A and Voronova, V and Donsì, F and Šic Žlabur, J and Ribić, B and Peter, Anamarija and Surić, Jona and Brandić, Ivan and Klõga, M and Ostojić, Sanja and Pataro, G and Virsta, A and Oros, A.E and Micić, Darko and Đurović, Saša and De Feo, G and Procentese, A and Voca, Neven",
year = "2022",
abstract = "In this study, an evaluation of food waste generation was conducted, using images taken before and after the daily meals of people aged between 20 and 30 years in Serbia, for the period between 1 January and 31 April in 2022. A convolutional neural network (CNN) was employed for the tasks of recognizing food images before the meal and estimating the percentage of food waste according to the photographs taken. Keeping in mind the vast variates and types of food available, the image recognition and validation of food items present a generally very challenging task. Nevertheless, deep learning has recently been shown to be a very potent image recognition procedure, while CNN presents a state-of-the-art method of deep learning. The CNN technique was implemented to the food detection and food waste estimation tasks throughout the parameter optimization procedure. The images of the most frequently encountered food items were collected from the internet to create an image dataset, covering 157 food categories, which was used to evaluate recognition performance. Each category included between 50 and 200 images, while the total number of images in the database reached 23,552. The CNN model presented good prediction capabilities, showing an accuracy of 0.988 and a loss of 0.102, after the network training cycle. The average food waste per meal, in the frame of the analysis in Serbia, was 21.3%, according to the images collected for food waste evaluation.",
publisher = "MDPI",
journal = "Electronics (Switzerland)",
title = "Food Recognition and Food Waste Estimation Using Convolutional Neural Network",
number = "22",
volume = "11",
doi = "10.3390/electronics11223746",
url = "conv_1125"
}

Lubura, J., Pezo, L., Sandu, M.A, Voronova, V., Donsì, F., Šic Žlabur, J., Ribić, B., Peter, A., Surić, J., Brandić, I., Klõga, M., Ostojić, S., Pataro, G., Virsta, A., Oros, A.E, Micić, D., Đurović, S., De Feo, G., Procentese, A.,& Voca, N.. (2022). Food Recognition and Food Waste Estimation Using Convolutional Neural Network. in Electronics (Switzerland)
MDPI., 11(22).
https://doi.org/10.3390/electronics11223746
conv_1125

Lubura J, Pezo L, Sandu M, Voronova V, Donsì F, Šic Žlabur J, Ribić B, Peter A, Surić J, Brandić I, Klõga M, Ostojić S, Pataro G, Virsta A, Oros A, Micić D, Đurović S, De Feo G, Procentese A, Voca N. Food Recognition and Food Waste Estimation Using Convolutional Neural Network. in Electronics (Switzerland). 2022;11(22).
doi:10.3390/electronics11223746
conv_1125 .

Lubura, J, Pezo, Lato, Sandu, M.A, Voronova, V, Donsì, F, Šic Žlabur, J, Ribić, B, Peter, Anamarija, Surić, Jona, Brandić, Ivan, Klõga, M, Ostojić, Sanja, Pataro, G, Virsta, A, Oros, A.E, Micić, Darko, Đurović, Saša, De Feo, G, Procentese, A, Voca, Neven, "Food Recognition and Food Waste Estimation Using Convolutional Neural Network" in Electronics (Switzerland), 11, no. 22 (2022),
https://doi.org/10.3390/electronics11223746 .,
conv_1125 .

TY  - JOUR
AU  - Pezo, Lato
AU  - Lončar, Biljana
AU  - Sovljanski, Olja
AU  - Tomić, Ana
AU  - Travicić, Vanja
AU  - Pezo, Milada
AU  - Aćimović, Milica
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/869
AB  - Simple Summary The artificial neural network (ANN) model was developed to predict and optimize the aniseed parameters including: plant height, umbel diameter, number of umbels, number of seeds, 1000-seed weight, yield per plant, plant weight, harvest index, yield per ha, essential oil yield, germination energy, total germination and essential oil content; as well as the content of obtained essential oil, such as: limonene, cis-dihydro carvone, methyl chavicol, carvone, cis-anethole, trans-anethole, beta-elemene, alpha-himachalene, trans-beta-farnesene, gamma-himachalene, trans-muurola-4(14),5-diene, alpha-zingiberene, beta-himachalene, beta-bisabolene, trans-pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate), according to growing year, locality and fertilization type. Predicting yield is essential for producers, stakeholders and international interchange demand. The majority of the divergence in yield and essential oil content is associated with environmental aspects, including weather conditions, soil variety and cultivation techniques. Therefore, aniseed production was examined in this study. The categorical input variables for artificial neural network modelling were growing year (two successive growing years), growing locality (three different locations in Vojvodina Province, Serbia) and fertilization type (six different treatments). The output variables were morphological and quality parameters, with agricultural importance such as plant height, umbel diameter, number of umbels, number of seeds per umbel, 1000-seed weight, seed yield per plant, plant weight, harvest index, yield per ha, essential oil (EO) yield, germination energy, total germination, EO content, as well as the share of EOs compounds, including limonene, cis-dihydro carvone, methyl chavicol, carvone, cis-anethole, trans-anethole, beta-elemene, alpha-himachalene, trans-beta-farnesene, gamma-himachalene, trans-muurola-4(14),5-diene, alpha-zingiberene, beta-himachalene, beta-bisabolene, trans-pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate. The ANN model predicted agricultural parameters accurately, showing r(2) values between 0.555 and 0.918, while r(2) values for the forecasting of essential oil content were between 0.379 and 0.908. According to global sensitivity analysis, the fertilization type was a more influential variable to agricultural parameters, while the location site was more influential to essential oils content.
PB  - MDPI AG
T2  - Life-Basel
T1  - Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach
IS  - 11
VL  - 12
DO  - 10.3390/life12111722
UR  - conv_1057
ER  - 

@article{
author = "Pezo, Lato and Lončar, Biljana and Sovljanski, Olja and Tomić, Ana and Travicić, Vanja and Pezo, Milada and Aćimović, Milica",
year = "2022",
abstract = "Simple Summary The artificial neural network (ANN) model was developed to predict and optimize the aniseed parameters including: plant height, umbel diameter, number of umbels, number of seeds, 1000-seed weight, yield per plant, plant weight, harvest index, yield per ha, essential oil yield, germination energy, total germination and essential oil content; as well as the content of obtained essential oil, such as: limonene, cis-dihydro carvone, methyl chavicol, carvone, cis-anethole, trans-anethole, beta-elemene, alpha-himachalene, trans-beta-farnesene, gamma-himachalene, trans-muurola-4(14),5-diene, alpha-zingiberene, beta-himachalene, beta-bisabolene, trans-pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate), according to growing year, locality and fertilization type. Predicting yield is essential for producers, stakeholders and international interchange demand. The majority of the divergence in yield and essential oil content is associated with environmental aspects, including weather conditions, soil variety and cultivation techniques. Therefore, aniseed production was examined in this study. The categorical input variables for artificial neural network modelling were growing year (two successive growing years), growing locality (three different locations in Vojvodina Province, Serbia) and fertilization type (six different treatments). The output variables were morphological and quality parameters, with agricultural importance such as plant height, umbel diameter, number of umbels, number of seeds per umbel, 1000-seed weight, seed yield per plant, plant weight, harvest index, yield per ha, essential oil (EO) yield, germination energy, total germination, EO content, as well as the share of EOs compounds, including limonene, cis-dihydro carvone, methyl chavicol, carvone, cis-anethole, trans-anethole, beta-elemene, alpha-himachalene, trans-beta-farnesene, gamma-himachalene, trans-muurola-4(14),5-diene, alpha-zingiberene, beta-himachalene, beta-bisabolene, trans-pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate. The ANN model predicted agricultural parameters accurately, showing r(2) values between 0.555 and 0.918, while r(2) values for the forecasting of essential oil content were between 0.379 and 0.908. According to global sensitivity analysis, the fertilization type was a more influential variable to agricultural parameters, while the location site was more influential to essential oils content.",
publisher = "MDPI AG",
journal = "Life-Basel",
title = "Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach",
number = "11",
volume = "12",
doi = "10.3390/life12111722",
url = "conv_1057"
}

Pezo, L., Lončar, B., Sovljanski, O., Tomić, A., Travicić, V., Pezo, M.,& Aćimović, M.. (2022). Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach. in Life-Basel
MDPI AG., 12(11).
https://doi.org/10.3390/life12111722
conv_1057

Pezo L, Lončar B, Sovljanski O, Tomić A, Travicić V, Pezo M, Aćimović M. Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach. in Life-Basel. 2022;12(11).
doi:10.3390/life12111722
conv_1057 .

Pezo, Lato, Lončar, Biljana, Sovljanski, Olja, Tomić, Ana, Travicić, Vanja, Pezo, Milada, Aćimović, Milica, "Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach" in Life-Basel, 12, no. 11 (2022),
https://doi.org/10.3390/life12111722 .,
conv_1057 .

TY  - JOUR
AU  - Bokić, Jelena
AU  - Kojić, Jovana
AU  - Krulj, Jelena
AU  - Pezo, Lato
AU  - Banjac, Vojislav
AU  - Tumbas Saponjac, Vesna
AU  - Travicić, Vanja
AU  - Moreno, Diego A.
AU  - Bodroža-Solarov, Marija
PY  - 2022
UR  - https://riofh.iofh.bg.ac.rs/handle/123456789/867
AB  - This study aimed to investigate the impact of chicory root addition (20-40%) and extrusion conditions (moisture content from 16.3 to 22.5%, and screw speed from 500 to 900 rpm) on bioactive compounds content (inulin, sesquiterpene lactones, and polyphenols) of gluten-free rice snacks. Chicory root is considered a potential carrier of food bioactives, while extrusion may produce a wide range of functional snack products. The mineral profiles were determined in all of the obtained extrudates in terms of Na, K, Ca, Mg, Fe, Mn, Zn, and Cu contents, while antioxidative activity was established through reducing capacity, DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) tests. Chicory root addition contributed to the improvement of bioactive compounds and mineral contents, as well as antioxidative activities in all of the investigated extrudates in comparison to the pure-rice control sample. An increase in moisture content raised sesquiterpene lactones and minerals, while high screw speeds positively affected polyphenols content. The achieved results showed the important impact of the extrusion conditions on the investigated parameters and promoted chicory root as an attractive food ingredient in gluten-free snack products with high bioactive value.
PB  - MDPI AG
T2  - Foods
T1  - Bioactive, Mineral and Antioxidative Properties of Gluten-Free Chicory Supplemented Snack: Impact of Processing Conditions
IS  - 22
VL  - 11
DO  - 10.3390/foods11223692
UR  - conv_1059
ER  - 

@article{
author = "Bokić, Jelena and Kojić, Jovana and Krulj, Jelena and Pezo, Lato and Banjac, Vojislav and Tumbas Saponjac, Vesna and Travicić, Vanja and Moreno, Diego A. and Bodroža-Solarov, Marija",
year = "2022",
abstract = "This study aimed to investigate the impact of chicory root addition (20-40%) and extrusion conditions (moisture content from 16.3 to 22.5%, and screw speed from 500 to 900 rpm) on bioactive compounds content (inulin, sesquiterpene lactones, and polyphenols) of gluten-free rice snacks. Chicory root is considered a potential carrier of food bioactives, while extrusion may produce a wide range of functional snack products. The mineral profiles were determined in all of the obtained extrudates in terms of Na, K, Ca, Mg, Fe, Mn, Zn, and Cu contents, while antioxidative activity was established through reducing capacity, DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) tests. Chicory root addition contributed to the improvement of bioactive compounds and mineral contents, as well as antioxidative activities in all of the investigated extrudates in comparison to the pure-rice control sample. An increase in moisture content raised sesquiterpene lactones and minerals, while high screw speeds positively affected polyphenols content. The achieved results showed the important impact of the extrusion conditions on the investigated parameters and promoted chicory root as an attractive food ingredient in gluten-free snack products with high bioactive value.",
publisher = "MDPI AG",
journal = "Foods",
title = "Bioactive, Mineral and Antioxidative Properties of Gluten-Free Chicory Supplemented Snack: Impact of Processing Conditions",
number = "22",
volume = "11",
doi = "10.3390/foods11223692",
url = "conv_1059"
}

Bokić, J., Kojić, J., Krulj, J., Pezo, L., Banjac, V., Tumbas Saponjac, V., Travicić, V., Moreno, D. A.,& Bodroža-Solarov, M.. (2022). Bioactive, Mineral and Antioxidative Properties of Gluten-Free Chicory Supplemented Snack: Impact of Processing Conditions. in Foods
MDPI AG., 11(22).
https://doi.org/10.3390/foods11223692
conv_1059

Bokić J, Kojić J, Krulj J, Pezo L, Banjac V, Tumbas Saponjac V, Travicić V, Moreno DA, Bodroža-Solarov M. Bioactive, Mineral and Antioxidative Properties of Gluten-Free Chicory Supplemented Snack: Impact of Processing Conditions. in Foods. 2022;11(22).
doi:10.3390/foods11223692
conv_1059 .

Bokić, Jelena, Kojić, Jovana, Krulj, Jelena, Pezo, Lato, Banjac, Vojislav, Tumbas Saponjac, Vesna, Travicić, Vanja, Moreno, Diego A., Bodroža-Solarov, Marija, "Bioactive, Mineral and Antioxidative Properties of Gluten-Free Chicory Supplemented Snack: Impact of Processing Conditions" in Foods, 11, no. 22 (2022),
https://doi.org/10.3390/foods11223692 .,
conv_1059 .