Develooment and utilization of novel and traditional technologies in production of competitive food products with added valued for national and global market - CREATING WEALTH FROM THE WEALTH OF SERBIA

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Develooment and utilization of novel and traditional technologies in production of competitive food products with added valued for national and global market - CREATING WEALTH FROM THE WEALTH OF SERBIA (en)
Развој и примена нових и традиционалних технологија у производњи конкурентних прехрамбених производа са додатом вредношћу за европско и светско тржиште - Створимо богатство из богатства Србије (sr)
Razvoj i primena novih i tradicionalnih tehnologija u proizvodnji konkurentnih prehrambenih proizvoda sa dodatom vrednošću za evropsko i svetsko tržište - Stvorimo bogatstvo iz bogatstva Srbije (sr_RS)
Authors

Publications

Artificial neural network model in predicting the quality of fresh tomato genotypes

Pestorić, Mladenka; Mastilović, Jasna; Kevrešan, Žarko; Pezo, Lato; Belović, Miona; Glogovac, Svetlana; Škrobot, Dubravka; Ilić, Nebojša; Takač, Adam

(Novi Sad : University of Novi Sad, Institute of Food Technology, 2021)

TY  - JOUR
AU  - Pestorić, Mladenka
AU  - Mastilović, Jasna
AU  - Kevrešan, Žarko
AU  - Pezo, Lato
AU  - Belović, Miona
AU  - Glogovac, Svetlana
AU  - Škrobot, Dubravka
AU  - Ilić, Nebojša
AU  - Takač, Adam
PY  - 2021
UR  - http://fiver.ifvcns.rs/handle/123456789/2482
AB  - Sensory analysis is the best mean to precisely describe the eating quality of fresh foods. However, it is expensive and time-consuming method which cannot be used
for measuring quality properties in real time. The aim of this paper was to contribute to
the study of the relationship between sensory and instrumental data, and to define a proper model for predicting sensory properties of fresh tomato through the determination of the
physicochemical properties. Principal Component Analysis (PCA) was applied to the
experimental data to characterize and differentiate among the observed genotypes, explaining 73.52% of the total variance, using the first three principal components.
Artificial neural network (ANN) model was used for the prediction of sensory properties
based on the results obtained by basic chemical and instrumental determinations. The
developed ANN model predicts the sensory properties with high adequacy, with the
overall coefficient of determination of 0.859.
AB  - Senzorska analiza predstavlja najbolje sredstvo za precizno opisivanje kvaliteta svežih namirnica. Međutim,to je skupa i dugotrajna metoda koja se ne može koristiti za merenje pokazatelja kvaliteta u realnom vremenu. Cilj ovog rada bio je da doprinese proučavanju odnosa između podataka dobijenih primenom senzorske analize i instrumentalnih metoda i da definiše odgovarajući model za predviđanje senzorskih svojstava svežeg paradajza pomoću određivanja fizičko-hemijskih svojstava. Analiza glavnih komponenti (RSA) primenjena je na eksperimentalne podatke da bi se okarakterisali i diferencirali posmatrani genotipovi, objašnjavajući 73,52% od ukupne varijanse, koristeći prve tri glavne komponente. Model veštačke neuronske mreže (ANN) korišćen je za predviđanje senzorskih svojstava na osnovu rezultata dobijenih osnovnim hemijskim i instrumentalnim određivanjima. Razvijeni ANN model predviđa senzorska svojstva sa visokom adekvatnošću, sa ukupnim koeficijentom determinacije od 0,859.
PB  - Novi Sad : University of Novi Sad, Institute of Food Technology
T2  - Food and Feed Research
T1  - Artificial neural network model in predicting the quality of fresh tomato genotypes
T1  - Veštačke neuronske mreže za predviđanje kvaliteta različitih genotipova paradajza
EP  - 21
IS  - 1
SP  - 9
VL  - 48
DO  - 10.5937/ffr48-29661
ER  - 
@article{
author = "Pestorić, Mladenka and Mastilović, Jasna and Kevrešan, Žarko and Pezo, Lato and Belović, Miona and Glogovac, Svetlana and Škrobot, Dubravka and Ilić, Nebojša and Takač, Adam",
year = "2021",
abstract = "Sensory analysis is the best mean to precisely describe the eating quality of fresh foods. However, it is expensive and time-consuming method which cannot be used
for measuring quality properties in real time. The aim of this paper was to contribute to
the study of the relationship between sensory and instrumental data, and to define a proper model for predicting sensory properties of fresh tomato through the determination of the
physicochemical properties. Principal Component Analysis (PCA) was applied to the
experimental data to characterize and differentiate among the observed genotypes, explaining 73.52% of the total variance, using the first three principal components.
Artificial neural network (ANN) model was used for the prediction of sensory properties
based on the results obtained by basic chemical and instrumental determinations. The
developed ANN model predicts the sensory properties with high adequacy, with the
overall coefficient of determination of 0.859., Senzorska analiza predstavlja najbolje sredstvo za precizno opisivanje kvaliteta svežih namirnica. Međutim,to je skupa i dugotrajna metoda koja se ne može koristiti za merenje pokazatelja kvaliteta u realnom vremenu. Cilj ovog rada bio je da doprinese proučavanju odnosa između podataka dobijenih primenom senzorske analize i instrumentalnih metoda i da definiše odgovarajući model za predviđanje senzorskih svojstava svežeg paradajza pomoću određivanja fizičko-hemijskih svojstava. Analiza glavnih komponenti (RSA) primenjena je na eksperimentalne podatke da bi se okarakterisali i diferencirali posmatrani genotipovi, objašnjavajući 73,52% od ukupne varijanse, koristeći prve tri glavne komponente. Model veštačke neuronske mreže (ANN) korišćen je za predviđanje senzorskih svojstava na osnovu rezultata dobijenih osnovnim hemijskim i instrumentalnim određivanjima. Razvijeni ANN model predviđa senzorska svojstva sa visokom adekvatnošću, sa ukupnim koeficijentom determinacije od 0,859.",
publisher = "Novi Sad : University of Novi Sad, Institute of Food Technology",
journal = "Food and Feed Research",
title = "Artificial neural network model in predicting the quality of fresh tomato genotypes, Veštačke neuronske mreže za predviđanje kvaliteta različitih genotipova paradajza",
pages = "21-9",
number = "1",
volume = "48",
doi = "10.5937/ffr48-29661"
}
Pestorić, M., Mastilović, J., Kevrešan, Ž., Pezo, L., Belović, M., Glogovac, S., Škrobot, D., Ilić, N.,& Takač, A.. (2021). Artificial neural network model in predicting the quality of fresh tomato genotypes. in Food and Feed Research
Novi Sad : University of Novi Sad, Institute of Food Technology., 48(1), 9-21.
https://doi.org/10.5937/ffr48-29661
Pestorić M, Mastilović J, Kevrešan Ž, Pezo L, Belović M, Glogovac S, Škrobot D, Ilić N, Takač A. Artificial neural network model in predicting the quality of fresh tomato genotypes. in Food and Feed Research. 2021;48(1):9-21.
doi:10.5937/ffr48-29661 .
Pestorić, Mladenka, Mastilović, Jasna, Kevrešan, Žarko, Pezo, Lato, Belović, Miona, Glogovac, Svetlana, Škrobot, Dubravka, Ilić, Nebojša, Takač, Adam, "Artificial neural network model in predicting the quality of fresh tomato genotypes" in Food and Feed Research, 48, no. 1 (2021):9-21,
https://doi.org/10.5937/ffr48-29661 . .
2

Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat

Živančev, Dragan

(Univerzitet u Novom Sadu, Tehnološki fakultet, 2014)

TY  - THES
AU  - Živančev, Dragan
PY  - 2014
UR  - http://nardus.mpn.gov.rs/handle/123456789/5434
UR  - http://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija141949700481512.pdf?controlNumber=(BISIS)84
UR  - http://www.cris.uns.ac.rs/record.jsf?recordId=84067&source=NaRDuS&language=sr
UR  - http://www.cris.uns.ac.rs/DownloadFileServlet/IzvestajKomisijeobrazac%206%20Dragan%20Zivancev.pdf?co
UR  - http://fiver.ifvcns.rs/handle/123456789/2105
AB  - In the Ph. D. Thesis was analyzed the impact of genetic, environmental and microclimatic factors that prevailed during the three production years on gluten composition and technological quality of 16 wheat varieties that are present in the assortment of Serbia. Also, all wheat varieties were produced at the same location. The traditional and sofisticated methods are used, electrophoretic analysis of glutenin and gliadin subunits was performed, the content of free-SH and-NH groups are determined, baking test and objective quality of the obtained bread are evaluated to examine the technological quality of wheat and composition of gluten. The gained results are used to established a database for statistical analysis. Due to the numerous data and the fact that the properties measured in different number of repetitions which are qualifed by sample amount, the usual number of repetitions, reproductivity method PCA was performed toward the selection of the most important properties. After that was done ANOVA in the respective to climatic factors that charatcterized the production year, the genetic factors that are caused by genetic similarity of the exmined cultivars of wheat and environmental factors that are reflected through the different levels of inseparable impurities, which are defined by frekvency analysis. Specific objectives of the study enable to: –determine how microclimatic conditions that prevailed in the three production years, especially the rainy and instable weather that prevailed from wheat flowering until full maturity of wheat kernel influence on the composition of gluten and wheat processing quality tested, –determine how environmental factors that are defined by the presence of three different levels of germinate kernels, kernels damaged by wheat bug, kernels infested by Fussarium molds and kernels infested by Alternaria alternata molds affect on the composition of gluten and technological quality of wheat cultivar and –determine how genetic factors which are defined through differences in HMW-GS on the Glu A1 and Glu D1 locus that cultivars contain or do not contain and identical HMW-GS composition which examined cultivars possess affect on the gluten composition and technological quality of tested wheat varieties. The achieved results represent a complex analysis of the impact of various factors on the composition of gluten and technological quality of wheat, which included a enormous database of properites and closely determine how individual microclimatic, genetic and environmental factors influence on the gluten composition and technological quality of wheat.
AB  - U okviru disertacije analiziran je uticaj genetskih, ekoloških i mikroklimatskih faktora tokom tri proizvodne godine na sastav glutena i tehnološki kvalitet 16 sorti pšenica koje su godinama zastupljene u sortimentu Srbije, a koje su bile proizvedene na istom lokalitetu. Da bi se ispitao tehnološki kvalitet i sastav glutena, upotrebljene su, kako tradicionalne, tako i savremene metode; urađena je elektroforetska analiza gluteninskih i glijadinskih podjedinica, sadržaj slobodnih –SH i –NH grupa, probno pečenje i objektivno je ocenjen kvalitet dobijenog hleba u cilju formiranja baze podataka za statističku analizu. Zbog obimnosti rezutata i činjenice da su pokazatelji određeni u različitom broju ponavljanja uslovljenim potrebnom količinom uzorka, uobičajenim brojem ponavljanja, reproduktivnošću metoda, urađena je PCA analiza na osnovu koje je izvršen odabir najvažnijih pokazatelja. Dodatno, primenjena je Analiza značajnosti u odnosnu na: klimatske faktore koji su uslovljeni proizvodnom godinom, genetske faktore koji su uslovljeni genetskom sličnošću ispitivanog sortimenta pšenice, kao i ekološkim faktorima koji se ogledaju preko različitog nivoa neodvojivih primesa koji su definisani frekvencionom analizom. Cilljevi istraživanja omogućili su da se: –utvrdi kako i na koji način mikroklimatski uslovi koji su vladali u tri proizvodne godine, a pogotovo kišno i nestabilno vreme u periodu od cvetanja pšenice pa sve do pune zrelosti, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice, –utvrdi kako i na koji način ekološki faktori, definisani prisutvom tri različita nivoa proklijalih, steničavih, fuzarioznih i tamnokličnih zrna, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice –utvrdi kako genetski faktori, definisani preko razlika u HMW–GS koje ispitivane sorte sadrže, odnosno ne sadrže na Glu A1, Glu D1 lokusu i identičnom HMW–GS sastavu, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice. Dobijeni rezultati predstavljaju jednu kompleksnu analizu koja je obuhvatila veliku bazu ispitivanih pokazatelja i bliže odredila kako pojedinačni genetski, mikroklimatski i ekološki faktori utiču na sastav glutena i tehnološki kvalitet pšenice.
PB  - Univerzitet u Novom Sadu, Tehnološki fakultet
T1  - Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat
T1  - Analiza uticaja genetskih, mikroklimatskih i ekoloških faktora na sastav glutena i tehnološki kvalitet sorti pšenice
UR  - https://hdl.handle.net/21.15107/rcub_nardus_5434
ER  - 
@phdthesis{
author = "Živančev, Dragan",
year = "2014",
abstract = "In the Ph. D. Thesis was analyzed the impact of genetic, environmental and microclimatic factors that prevailed during the three production years on gluten composition and technological quality of 16 wheat varieties that are present in the assortment of Serbia. Also, all wheat varieties were produced at the same location. The traditional and sofisticated methods are used, electrophoretic analysis of glutenin and gliadin subunits was performed, the content of free-SH and-NH groups are determined, baking test and objective quality of the obtained bread are evaluated to examine the technological quality of wheat and composition of gluten. The gained results are used to established a database for statistical analysis. Due to the numerous data and the fact that the properties measured in different number of repetitions which are qualifed by sample amount, the usual number of repetitions, reproductivity method PCA was performed toward the selection of the most important properties. After that was done ANOVA in the respective to climatic factors that charatcterized the production year, the genetic factors that are caused by genetic similarity of the exmined cultivars of wheat and environmental factors that are reflected through the different levels of inseparable impurities, which are defined by frekvency analysis. Specific objectives of the study enable to: –determine how microclimatic conditions that prevailed in the three production years, especially the rainy and instable weather that prevailed from wheat flowering until full maturity of wheat kernel influence on the composition of gluten and wheat processing quality tested, –determine how environmental factors that are defined by the presence of three different levels of germinate kernels, kernels damaged by wheat bug, kernels infested by Fussarium molds and kernels infested by Alternaria alternata molds affect on the composition of gluten and technological quality of wheat cultivar and –determine how genetic factors which are defined through differences in HMW-GS on the Glu A1 and Glu D1 locus that cultivars contain or do not contain and identical HMW-GS composition which examined cultivars possess affect on the gluten composition and technological quality of tested wheat varieties. The achieved results represent a complex analysis of the impact of various factors on the composition of gluten and technological quality of wheat, which included a enormous database of properites and closely determine how individual microclimatic, genetic and environmental factors influence on the gluten composition and technological quality of wheat., U okviru disertacije analiziran je uticaj genetskih, ekoloških i mikroklimatskih faktora tokom tri proizvodne godine na sastav glutena i tehnološki kvalitet 16 sorti pšenica koje su godinama zastupljene u sortimentu Srbije, a koje su bile proizvedene na istom lokalitetu. Da bi se ispitao tehnološki kvalitet i sastav glutena, upotrebljene su, kako tradicionalne, tako i savremene metode; urađena je elektroforetska analiza gluteninskih i glijadinskih podjedinica, sadržaj slobodnih –SH i –NH grupa, probno pečenje i objektivno je ocenjen kvalitet dobijenog hleba u cilju formiranja baze podataka za statističku analizu. Zbog obimnosti rezutata i činjenice da su pokazatelji određeni u različitom broju ponavljanja uslovljenim potrebnom količinom uzorka, uobičajenim brojem ponavljanja, reproduktivnošću metoda, urađena je PCA analiza na osnovu koje je izvršen odabir najvažnijih pokazatelja. Dodatno, primenjena je Analiza značajnosti u odnosnu na: klimatske faktore koji su uslovljeni proizvodnom godinom, genetske faktore koji su uslovljeni genetskom sličnošću ispitivanog sortimenta pšenice, kao i ekološkim faktorima koji se ogledaju preko različitog nivoa neodvojivih primesa koji su definisani frekvencionom analizom. Cilljevi istraživanja omogućili su da se: –utvrdi kako i na koji način mikroklimatski uslovi koji su vladali u tri proizvodne godine, a pogotovo kišno i nestabilno vreme u periodu od cvetanja pšenice pa sve do pune zrelosti, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice, –utvrdi kako i na koji način ekološki faktori, definisani prisutvom tri različita nivoa proklijalih, steničavih, fuzarioznih i tamnokličnih zrna, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice –utvrdi kako genetski faktori, definisani preko razlika u HMW–GS koje ispitivane sorte sadrže, odnosno ne sadrže na Glu A1, Glu D1 lokusu i identičnom HMW–GS sastavu, utiču na sastav glutena i tehnološki kvalitet ispitivanih sorti pšenice. Dobijeni rezultati predstavljaju jednu kompleksnu analizu koja je obuhvatila veliku bazu ispitivanih pokazatelja i bliže odredila kako pojedinačni genetski, mikroklimatski i ekološki faktori utiču na sastav glutena i tehnološki kvalitet pšenice.",
publisher = "Univerzitet u Novom Sadu, Tehnološki fakultet",
title = "Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat, Analiza uticaja genetskih, mikroklimatskih i ekoloških faktora na sastav glutena i tehnološki kvalitet sorti pšenice",
url = "https://hdl.handle.net/21.15107/rcub_nardus_5434"
}
Živančev, D.. (2014). Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat. 
Univerzitet u Novom Sadu, Tehnološki fakultet..
https://hdl.handle.net/21.15107/rcub_nardus_5434
Živančev D. Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat. 2014;.
https://hdl.handle.net/21.15107/rcub_nardus_5434 .
Živančev, Dragan, "Analysis of the impact of genetic, microclimatic and environmental factors on the composition of gluten and technological quality of wheat" (2014),
https://hdl.handle.net/21.15107/rcub_nardus_5434 .

Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models

Mastilović, Jasna; Kevrešan, Žarko S.; Torbica, Aleksandra; Janić-Hajnal, Elizabet; Živančev, Dragan

(Wiley, Hoboken, 2014)

TY  - JOUR
AU  - Mastilović, Jasna
AU  - Kevrešan, Žarko S.
AU  - Torbica, Aleksandra
AU  - Janić-Hajnal, Elizabet
AU  - Živančev, Dragan
PY  - 2014
UR  - http://fiver.ifvcns.rs/handle/123456789/1314
AB  - The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values from standard protocol.
PB  - Wiley, Hoboken
T2  - International Journal of Food Science & Technology
T1  - Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models
EP  - 2691
IS  - 12
SP  - 2685
VL  - 49
DO  - 10.1111/ijfs.12601
ER  - 
@article{
author = "Mastilović, Jasna and Kevrešan, Žarko S. and Torbica, Aleksandra and Janić-Hajnal, Elizabet and Živančev, Dragan",
year = "2014",
abstract = "The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values from standard protocol.",
publisher = "Wiley, Hoboken",
journal = "International Journal of Food Science & Technology",
title = "Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models",
pages = "2691-2685",
number = "12",
volume = "49",
doi = "10.1111/ijfs.12601"
}
Mastilović, J., Kevrešan, Ž. S., Torbica, A., Janić-Hajnal, E.,& Živančev, D.. (2014). Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models. in International Journal of Food Science & Technology
Wiley, Hoboken., 49(12), 2685-2691.
https://doi.org/10.1111/ijfs.12601
Mastilović J, Kevrešan ŽS, Torbica A, Janić-Hajnal E, Živančev D. Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models. in International Journal of Food Science & Technology. 2014;49(12):2685-2691.
doi:10.1111/ijfs.12601 .
Mastilović, Jasna, Kevrešan, Žarko S., Torbica, Aleksandra, Janić-Hajnal, Elizabet, Živančev, Dragan, "Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models" in International Journal of Food Science & Technology, 49, no. 12 (2014):2685-2691,
https://doi.org/10.1111/ijfs.12601 . .
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