TY  - CONF
AU  - Ranđelović, Predrag
AU  - Đorđević, Vuk
AU  - Miladinović, Jegor
AU  - Ćeran, Marina
AU  - Prodanović, Slaven
AU  - Jaćimović, Simona
AU  - Đukić, Vojin
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/3657
AB  - The combined power of remote sensing and photogrammetry can be used to assess significant information about plant development. The canopy cover (CC) and height (HT) are important for defining the growth patterns of the plants and their reaction to different environmental conditions. The objective of this study was to utilize the technology of high-throughput phenotyping (HTPP) for the temporal screening of soybean CC and HT. The trial was set in 2020 and 2021 at the experimental fields of the Institute of Field and Vegetable Crops, Novi Sad, Serbia. In total, 206 soybean genotypes divided into early (ED) and late (LD) were grown in drought simulation environments. As a control, the same set of genotypes (EC and LC) was grown in favorable conditions. The CC and HT were determined from the images collected with the unmanned aerial vehicle (UAV). In both years, the photos were taken four times at approximately 274, 390, 706, and 917 growing degree days (GDDs) after emergence.
PB  - Vienna : University of Natural Resources and Life Sciences (BOKU)
C3  - Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023
T1  - High-throughput phenotyping for temporal screening of soybean canopy cover and height assessed in different environments
EP  - 114
SP  - 114
DO  - 10.5281/zenodo.7974681
ER  - 

@conference{
author = "Ranđelović, Predrag and Đorđević, Vuk and Miladinović, Jegor and Ćeran, Marina and Prodanović, Slaven and Jaćimović, Simona and Đukić, Vojin",
year = "2023",
abstract = "The combined power of remote sensing and photogrammetry can be used to assess significant information about plant development. The canopy cover (CC) and height (HT) are important for defining the growth patterns of the plants and their reaction to different environmental conditions. The objective of this study was to utilize the technology of high-throughput phenotyping (HTPP) for the temporal screening of soybean CC and HT. The trial was set in 2020 and 2021 at the experimental fields of the Institute of Field and Vegetable Crops, Novi Sad, Serbia. In total, 206 soybean genotypes divided into early (ED) and late (LD) were grown in drought simulation environments. As a control, the same set of genotypes (EC and LC) was grown in favorable conditions. The CC and HT were determined from the images collected with the unmanned aerial vehicle (UAV). In both years, the photos were taken four times at approximately 274, 390, 706, and 917 growing degree days (GDDs) after emergence.",
publisher = "Vienna : University of Natural Resources and Life Sciences (BOKU)",
journal = "Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023",
title = "High-throughput phenotyping for temporal screening of soybean canopy cover and height assessed in different environments",
pages = "114-114",
doi = "10.5281/zenodo.7974681"
}

Ranđelović, P., Đorđević, V., Miladinović, J., Ćeran, M., Prodanović, S., Jaćimović, S.,& Đukić, V.. (2023). High-throughput phenotyping for temporal screening of soybean canopy cover and height assessed in different environments. in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023
Vienna : University of Natural Resources and Life Sciences (BOKU)., 114-114.
https://doi.org/10.5281/zenodo.7974681

Ranđelović P, Đorđević V, Miladinović J, Ćeran M, Prodanović S, Jaćimović S, Đukić V. High-throughput phenotyping for temporal screening of soybean canopy cover and height assessed in different environments. in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023. 2023;:114-114.
doi:10.5281/zenodo.7974681 .

Ranđelović, Predrag, Đorđević, Vuk, Miladinović, Jegor, Ćeran, Marina, Prodanović, Slaven, Jaćimović, Simona, Đukić, Vojin, "High-throughput phenotyping for temporal screening of soybean canopy cover and height assessed in different environments" in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023 (2023):114-114,
https://doi.org/10.5281/zenodo.7974681 . .

TY  - JOUR
AU  - Ranđelović, Predrag
AU  - Đorđević, Vuk
AU  - Miladinović, Jegor
AU  - Prodanović, Slaven
AU  - Ćeran, Marina
AU  - Vollmann, Johann
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/4064
AB  - Biomass accumulation as a growth indicator can be significant in achieving high and stable soybean yields. More robust genotypes have a better potential for exploiting available resources such as water or sunlight. Biomass data implemented as a new trait in soybean breeding programs could be beneficial in the selection of varieties that are more competitive against weeds and have better radiation use efficiency. The standard techniques for biomass determination are invasive, inefficient, and restricted to one-time point per plot. Machine learning models (MLMs) based on the multispectral (MS) images were created so as to overcome these issues and provide a non-destructive, fast, and accurate tool for in-season estimation of soybean fresh biomass (FB). The MS photos were taken during two growing seasons of 10 soybean varieties, using six-sensor digital camera mounted on the unmanned aerial vehicle (UAV). For model calibration, canopy cover (CC), plant height (PH), and 31 vegetation index (VI) were extracted from the images and used as predictors in the random forest (RF) and partial least squares regression (PLSR) algorithm. To create a more efficient model, highly correlated VIs were excluded and only the triangular greenness index (TGI) and green chlorophyll index (GCI) remained.
PB  - Springer Nature
T2  - Plant Methods
T1  - High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data
VL  - 19
DO  - 10.1186/s13007-023-01054-6
ER  - 

@article{
author = "Ranđelović, Predrag and Đorđević, Vuk and Miladinović, Jegor and Prodanović, Slaven and Ćeran, Marina and Vollmann, Johann",
year = "2023",
abstract = "Biomass accumulation as a growth indicator can be significant in achieving high and stable soybean yields. More robust genotypes have a better potential for exploiting available resources such as water or sunlight. Biomass data implemented as a new trait in soybean breeding programs could be beneficial in the selection of varieties that are more competitive against weeds and have better radiation use efficiency. The standard techniques for biomass determination are invasive, inefficient, and restricted to one-time point per plot. Machine learning models (MLMs) based on the multispectral (MS) images were created so as to overcome these issues and provide a non-destructive, fast, and accurate tool for in-season estimation of soybean fresh biomass (FB). The MS photos were taken during two growing seasons of 10 soybean varieties, using six-sensor digital camera mounted on the unmanned aerial vehicle (UAV). For model calibration, canopy cover (CC), plant height (PH), and 31 vegetation index (VI) were extracted from the images and used as predictors in the random forest (RF) and partial least squares regression (PLSR) algorithm. To create a more efficient model, highly correlated VIs were excluded and only the triangular greenness index (TGI) and green chlorophyll index (GCI) remained.",
publisher = "Springer Nature",
journal = "Plant Methods",
title = "High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data",
volume = "19",
doi = "10.1186/s13007-023-01054-6"
}

Ranđelović, P., Đorđević, V., Miladinović, J., Prodanović, S., Ćeran, M.,& Vollmann, J.. (2023). High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data. in Plant Methods
Springer Nature., 19.
https://doi.org/10.1186/s13007-023-01054-6

Ranđelović P, Đorđević V, Miladinović J, Prodanović S, Ćeran M, Vollmann J. High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data. in Plant Methods. 2023;19.
doi:10.1186/s13007-023-01054-6 .

Ranđelović, Predrag, Đorđević, Vuk, Miladinović, Jegor, Prodanović, Slaven, Ćeran, Marina, Vollmann, Johann, "High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data" in Plant Methods, 19 (2023),
https://doi.org/10.1186/s13007-023-01054-6 . .

TY  - JOUR
AU  - Koren, Anamarija
AU  - Sikora, Vladimir
AU  - Milovac, Željko
AU  - Mitrović, Petar
AU  - Miladinović, Dragana
AU  - Prodanović, Slaven
AU  - Marjanović-Jeromela, Ana
PY  - 2022
UR  - http://fiver.ifvcns.rs/handle/123456789/3437
AB  - Several winter and spring alternative crops are grown in our country. Similar to the yield of staple field crops, the yield of minor cultivated crops is affected by complex climate-soil interactions, abiotic and biotic stress and cultivation technology. If grown solely for the production of plant raw materials (aboveground biomass, grain and/or root) for conversion into biofuels and bioenergy, the alternative crops are energy - crops. Although they have different botanical affiliations, morphologies and origins, energy - crops can be: oilseeds (oil rapeseed, camelina, white mustard, castor), starch-sugar (sorghum, Sudanese grass, corn) and lignocellulosic (miscanthus, hemp). From the point of view of agronomy, the prerequisite for increasing the area under energy - plant species for the production of biofuels in Serbia is the improvement of assortment, cultivation technology and mechanization. The paper provides an overview of agronomic forms and cultivation technology of several specific alternative plant species in the context of using crop biomass for energy purposes.
PB  - Novi Sad : Institute of Field and Vegetable Crops
T2  - Alternative Crops and Cultivation Practices
T1  - Cultivation of alternative crops as energy crops
EP  - 20
SP  - 17
VL  - 4
UR  - https://hdl.handle.net/21.15107/rcub_fiver_3437
ER  - 

@article{
author = "Koren, Anamarija and Sikora, Vladimir and Milovac, Željko and Mitrović, Petar and Miladinović, Dragana and Prodanović, Slaven and Marjanović-Jeromela, Ana",
year = "2022",
abstract = "Several winter and spring alternative crops are grown in our country. Similar to the yield of staple field crops, the yield of minor cultivated crops is affected by complex climate-soil interactions, abiotic and biotic stress and cultivation technology. If grown solely for the production of plant raw materials (aboveground biomass, grain and/or root) for conversion into biofuels and bioenergy, the alternative crops are energy - crops. Although they have different botanical affiliations, morphologies and origins, energy - crops can be: oilseeds (oil rapeseed, camelina, white mustard, castor), starch-sugar (sorghum, Sudanese grass, corn) and lignocellulosic (miscanthus, hemp). From the point of view of agronomy, the prerequisite for increasing the area under energy - plant species for the production of biofuels in Serbia is the improvement of assortment, cultivation technology and mechanization. The paper provides an overview of agronomic forms and cultivation technology of several specific alternative plant species in the context of using crop biomass for energy purposes.",
publisher = "Novi Sad : Institute of Field and Vegetable Crops",
journal = "Alternative Crops and Cultivation Practices",
title = "Cultivation of alternative crops as energy crops",
pages = "20-17",
volume = "4",
url = "https://hdl.handle.net/21.15107/rcub_fiver_3437"
}

Koren, A., Sikora, V., Milovac, Ž., Mitrović, P., Miladinović, D., Prodanović, S.,& Marjanović-Jeromela, A.. (2022). Cultivation of alternative crops as energy crops. in Alternative Crops and Cultivation Practices
Novi Sad : Institute of Field and Vegetable Crops., 4, 17-20.
https://hdl.handle.net/21.15107/rcub_fiver_3437

Koren A, Sikora V, Milovac Ž, Mitrović P, Miladinović D, Prodanović S, Marjanović-Jeromela A. Cultivation of alternative crops as energy crops. in Alternative Crops and Cultivation Practices. 2022;4:17-20.
https://hdl.handle.net/21.15107/rcub_fiver_3437 .

Koren, Anamarija, Sikora, Vladimir, Milovac, Željko, Mitrović, Petar, Miladinović, Dragana, Prodanović, Slaven, Marjanović-Jeromela, Ana, "Cultivation of alternative crops as energy crops" in Alternative Crops and Cultivation Practices, 4 (2022):17-20,
https://hdl.handle.net/21.15107/rcub_fiver_3437 .

TY  - JOUR
AU  - Radinović, Irena
AU  - Vasiljević, Sanja
AU  - Branković, Gordana
AU  - Živanović, Tomislav
AU  - Prodanović, Slaven
PY  - 2022
UR  - http://fiver.ifvcns.rs/handle/123456789/3672
AB  - Red clover (Trifolium pratense L.) is a meadow and pasture species in natural habitats and also a cultivated species used for animal nutrition. The aim of this research was the assessment of the diversity of 46 red clover accessions based on morphoproductive traits. The traits were investigated according to the UPOV descriptors for red clover – number of internodes, number
of branches, stem length, stem thickness, middle leaflet length, middle leaflet width, green matter yield and dry matter yield.The principal components analysis (PCA) explained 74% of the variance of the standardized data and showed relationships between 46 red clover accessions and eight morpho-productive traits, associations among traits and performance of accessions. Among the determined Euclidean distances, the smallest value was obtained for the accessions Rotra and Titus (0.048), the largest value was 1.099 for a pair of NCPGRU2 and Čortanovci accessions, and the average value was 0.380. Two clusters of 46 red clover accessions were separated in the dendrogram based upon UPGMA (Unweighted Pair-Group Method with Arithmetic mean)
for eight morpho-productive traits. The first cluster included two subclusters, while the second cluster contained four subclusters. The grouping of the accessions from the red clover collection by the UPGMA cluster analysis can be linked to the geographical origin of the accessions: central and southern Europe for three subclusters and north-eastern Europe for one subcluster.
AB  - Crvena detelina (Trifolium pratense L.) jeste livadsko-pašnjačka vrsta na prirodnim staništima, a i kultivisana vrsta koja se koristi u ishrani životinja. Svrha ovog istraživanja je bila procena diverziteta 46 genotipova crvene deteline na osnovu morfološko-produktivnih osobina. Proučavane su osobine na osnovu UPOV deskriptora – broja internodija, broja grana, dužine stabla, širine stabla, dužine centralne liske, širine centralne liske, prinosa zelene mase i prinosa suve materije. Analizom glavnih komponenti (PCA) morfo-produktivnih osobina crvene deteline objašnjeno je 74% varijanse standardizovanih podataka i prikazani su odnosi 46 genotipova crvene deteline i osam morfološko-produktivnih osobina, povezanost osobina i performansa genotipova. Među utvrđenim Euklidovim distancama, najmanja vrednost je izračunata za genotipove Rotra i Titus (0,048), najveća je bila 1,099 za par NCPGRU2 i Čortanovci, a prosečna vrednost je iznosila 0,380. Primenom neponderisanog metoda parnih grupa sa aritmetičkim prosecima (UPGMA), dendrogramom 46 genotipova crvene deteline konstruisanim na osnovu osam morfo-produktivnih osobina izdvojena su dva klastera. Prvi klaster je sadržao dva potklastera, dok se drugi klaster sastojao od četiri potklastera. Grupisanje genotipova crvene deteline pomoću UPGMA klaster analize moglo se dovesti u vezu sa geografskim poreklom genotipova: centralna i južna Evropa za tri potklastera i severoistočna Evropa za jedan potklaster.
PB  - Čačak : Univerzitet u Kragujevcu, Agronomski fakultet u Čačku
T2  - Acta Agriculturae Serbica
T1  - Biodiversity of a red clover collection based on morpho-productive traits
EP  - 65
IS  - 53
SP  - 57
VL  - 27
DO  - 10.5937/AASer2253057R
ER  - 

@article{
author = "Radinović, Irena and Vasiljević, Sanja and Branković, Gordana and Živanović, Tomislav and Prodanović, Slaven",
year = "2022",
abstract = "Red clover (Trifolium pratense L.) is a meadow and pasture species in natural habitats and also a cultivated species used for animal nutrition. The aim of this research was the assessment of the diversity of 46 red clover accessions based on morphoproductive traits. The traits were investigated according to the UPOV descriptors for red clover – number of internodes, number
of branches, stem length, stem thickness, middle leaflet length, middle leaflet width, green matter yield and dry matter yield.The principal components analysis (PCA) explained 74% of the variance of the standardized data and showed relationships between 46 red clover accessions and eight morpho-productive traits, associations among traits and performance of accessions. Among the determined Euclidean distances, the smallest value was obtained for the accessions Rotra and Titus (0.048), the largest value was 1.099 for a pair of NCPGRU2 and Čortanovci accessions, and the average value was 0.380. Two clusters of 46 red clover accessions were separated in the dendrogram based upon UPGMA (Unweighted Pair-Group Method with Arithmetic mean)
for eight morpho-productive traits. The first cluster included two subclusters, while the second cluster contained four subclusters. The grouping of the accessions from the red clover collection by the UPGMA cluster analysis can be linked to the geographical origin of the accessions: central and southern Europe for three subclusters and north-eastern Europe for one subcluster., Crvena detelina (Trifolium pratense L.) jeste livadsko-pašnjačka vrsta na prirodnim staništima, a i kultivisana vrsta koja se koristi u ishrani životinja. Svrha ovog istraživanja je bila procena diverziteta 46 genotipova crvene deteline na osnovu morfološko-produktivnih osobina. Proučavane su osobine na osnovu UPOV deskriptora – broja internodija, broja grana, dužine stabla, širine stabla, dužine centralne liske, širine centralne liske, prinosa zelene mase i prinosa suve materije. Analizom glavnih komponenti (PCA) morfo-produktivnih osobina crvene deteline objašnjeno je 74% varijanse standardizovanih podataka i prikazani su odnosi 46 genotipova crvene deteline i osam morfološko-produktivnih osobina, povezanost osobina i performansa genotipova. Među utvrđenim Euklidovim distancama, najmanja vrednost je izračunata za genotipove Rotra i Titus (0,048), najveća je bila 1,099 za par NCPGRU2 i Čortanovci, a prosečna vrednost je iznosila 0,380. Primenom neponderisanog metoda parnih grupa sa aritmetičkim prosecima (UPGMA), dendrogramom 46 genotipova crvene deteline konstruisanim na osnovu osam morfo-produktivnih osobina izdvojena su dva klastera. Prvi klaster je sadržao dva potklastera, dok se drugi klaster sastojao od četiri potklastera. Grupisanje genotipova crvene deteline pomoću UPGMA klaster analize moglo se dovesti u vezu sa geografskim poreklom genotipova: centralna i južna Evropa za tri potklastera i severoistočna Evropa za jedan potklaster.",
publisher = "Čačak : Univerzitet u Kragujevcu, Agronomski fakultet u Čačku",
journal = "Acta Agriculturae Serbica",
title = "Biodiversity of a red clover collection based on morpho-productive traits",
pages = "65-57",
number = "53",
volume = "27",
doi = "10.5937/AASer2253057R"
}

Radinović, I., Vasiljević, S., Branković, G., Živanović, T.,& Prodanović, S.. (2022). Biodiversity of a red clover collection based on morpho-productive traits. in Acta Agriculturae Serbica
Čačak : Univerzitet u Kragujevcu, Agronomski fakultet u Čačku., 27(53), 57-65.
https://doi.org/10.5937/AASer2253057R

Radinović I, Vasiljević S, Branković G, Živanović T, Prodanović S. Biodiversity of a red clover collection based on morpho-productive traits. in Acta Agriculturae Serbica. 2022;27(53):57-65.
doi:10.5937/AASer2253057R .

Radinović, Irena, Vasiljević, Sanja, Branković, Gordana, Živanović, Tomislav, Prodanović, Slaven, "Biodiversity of a red clover collection based on morpho-productive traits" in Acta Agriculturae Serbica, 27, no. 53 (2022):57-65,
https://doi.org/10.5937/AASer2253057R . .

TY  - CONF
AU  - Glogovac, Svetlana
AU  - Belović, Miona
AU  - Nagl, Nevena
AU  - Gvozdanović-Varga, Jelica
AU  - Takač, Adam
AU  - Prodanović, Slaven
AU  - Živanović, Tomislav
PY  - 2017
UR  - http://fiver.ifvcns.rs/handle/123456789/3786
AB  - Importance of tomato, being considered as "functional food" is reflected by the rising trend of harvested areas and consumption per capita, in recent decades. Beside specific demands, fruit quality is common for both, consumers of fresh fruits and processing industry. The objective of this study was to characterize 20 tomato genotypes based on physical and chemical quality characteristics and to segregate perspective genotypes for improvement of tomato quality by breeding programs. The experiment was carried out during three consecutive years (2010-2012) at experimental fields at Rimski Šančevi site, near Novi Sad. Five landraces, four old varieties, eight breeding lines and three commercial cultivars were chosen for the investigation. Following fruit characteristics were analyzed: average weight (g), length (cm), width (cm), pericarp thickness (mm), locule number, moisture content (%), total soluble solids (°Brix), ash content (%), total acidity (%) and pH value. Diversity of genotypes in all analized traits was found. Four principal components explained 90,6% of total variance or 36,5%, 24,2%, 19,8% and 10,1, respectively. Along the axis of the first main component, genotypes were classified into three groups. Genotypes
with the thickest pericarp, highest total soluble solids, ash content, and acidity were identified, as promising for quality improvement in tomato breeding programs.
PB  - Novi Sad : Institute of Field and Vegetable Crops
C3  - Book of Abstracts, COST WG1 / EPPN2020 workshop, 29-30 September 2017, Novi Sad
T1  - PCA Classification of tomato genotypes based on physical and chemical fruit characteristics
EP  - 53
SP  - 53
UR  - https://hdl.handle.net/21.15107/rcub_fiver_3786
ER  - 

@conference{
author = "Glogovac, Svetlana and Belović, Miona and Nagl, Nevena and Gvozdanović-Varga, Jelica and Takač, Adam and Prodanović, Slaven and Živanović, Tomislav",
year = "2017",
abstract = "Importance of tomato, being considered as "functional food" is reflected by the rising trend of harvested areas and consumption per capita, in recent decades. Beside specific demands, fruit quality is common for both, consumers of fresh fruits and processing industry. The objective of this study was to characterize 20 tomato genotypes based on physical and chemical quality characteristics and to segregate perspective genotypes for improvement of tomato quality by breeding programs. The experiment was carried out during three consecutive years (2010-2012) at experimental fields at Rimski Šančevi site, near Novi Sad. Five landraces, four old varieties, eight breeding lines and three commercial cultivars were chosen for the investigation. Following fruit characteristics were analyzed: average weight (g), length (cm), width (cm), pericarp thickness (mm), locule number, moisture content (%), total soluble solids (°Brix), ash content (%), total acidity (%) and pH value. Diversity of genotypes in all analized traits was found. Four principal components explained 90,6% of total variance or 36,5%, 24,2%, 19,8% and 10,1, respectively. Along the axis of the first main component, genotypes were classified into three groups. Genotypes
with the thickest pericarp, highest total soluble solids, ash content, and acidity were identified, as promising for quality improvement in tomato breeding programs.",
publisher = "Novi Sad : Institute of Field and Vegetable Crops",
journal = "Book of Abstracts, COST WG1 / EPPN2020 workshop, 29-30 September 2017, Novi Sad",
title = "PCA Classification of tomato genotypes based on physical and chemical fruit characteristics",
pages = "53-53",
url = "https://hdl.handle.net/21.15107/rcub_fiver_3786"
}

Glogovac, S., Belović, M., Nagl, N., Gvozdanović-Varga, J., Takač, A., Prodanović, S.,& Živanović, T.. (2017). PCA Classification of tomato genotypes based on physical and chemical fruit characteristics. in Book of Abstracts, COST WG1 / EPPN2020 workshop, 29-30 September 2017, Novi Sad
Novi Sad : Institute of Field and Vegetable Crops., 53-53.
https://hdl.handle.net/21.15107/rcub_fiver_3786

Glogovac S, Belović M, Nagl N, Gvozdanović-Varga J, Takač A, Prodanović S, Živanović T. PCA Classification of tomato genotypes based on physical and chemical fruit characteristics. in Book of Abstracts, COST WG1 / EPPN2020 workshop, 29-30 September 2017, Novi Sad. 2017;:53-53.
https://hdl.handle.net/21.15107/rcub_fiver_3786 .

Glogovac, Svetlana, Belović, Miona, Nagl, Nevena, Gvozdanović-Varga, Jelica, Takač, Adam, Prodanović, Slaven, Živanović, Tomislav, "PCA Classification of tomato genotypes based on physical and chemical fruit characteristics" in Book of Abstracts, COST WG1 / EPPN2020 workshop, 29-30 September 2017, Novi Sad (2017):53-53,
https://hdl.handle.net/21.15107/rcub_fiver_3786 .