TY  - JOUR
AU  - Kolašinac, Stefan
AU  - Pećinar, Ilinka
AU  - Danojević, Dario
AU  - Stevanović Dajić, Zora
PY  - 2022
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/6077
AB  - Five Balkan paprika varieties at physiological maturity were investigated by means of Raman spectroscopy in order to discriminate the differences which stemmed from their genetic variability since the plants were grown under the same experimental conditions. The spectra were obtained using the 532 nm wavelength. In an effort to find the best classification power, several pre-processing methods were applied: 1) baseline correction, unit vector normalization; 2) baseline correction, unit vector normalization and first Savitzky-Golay derivative; 3) baseline correction, unit vector normalization and second Savitzky-Golay derivative; 4) baseline correction, unit vector normalization and third Savitzky-Golay derivative. All of the pre-processing methods were followed by making PCA-LDA (Principal Component Analysis-Linear Discriminant Analysis), QDA (Quadratic Discriminant Analysis), and PLS-DA (Partial Least Square - Discriminant Analysis) classification models. QDA showed the best discrimination power (83.87–100% and 89.47–100% for the training and the test data, respectively), then PCA-LDA (0.00–100 and 0.00–100% for the training and the test data, respectively) and PLS-DA (19.35–100% and 0.00–100.00% for the training and the test data, respectively). The results pointed out the applicability of chemometric modeling associated with Raman spectroscopy in the assessment of nutritionally similar samples, such as the studied red paprika varieties.
PB  - Academic Press
T2  - LWT
T1  - Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity
SP  - 113402
VL  - 162
DO  - 10.1016/j.lwt.2022.113402
ER  - 

@article{
author = "Kolašinac, Stefan and Pećinar, Ilinka and Danojević, Dario and Stevanović Dajić, Zora",
year = "2022",
abstract = "Five Balkan paprika varieties at physiological maturity were investigated by means of Raman spectroscopy in order to discriminate the differences which stemmed from their genetic variability since the plants were grown under the same experimental conditions. The spectra were obtained using the 532 nm wavelength. In an effort to find the best classification power, several pre-processing methods were applied: 1) baseline correction, unit vector normalization; 2) baseline correction, unit vector normalization and first Savitzky-Golay derivative; 3) baseline correction, unit vector normalization and second Savitzky-Golay derivative; 4) baseline correction, unit vector normalization and third Savitzky-Golay derivative. All of the pre-processing methods were followed by making PCA-LDA (Principal Component Analysis-Linear Discriminant Analysis), QDA (Quadratic Discriminant Analysis), and PLS-DA (Partial Least Square - Discriminant Analysis) classification models. QDA showed the best discrimination power (83.87–100% and 89.47–100% for the training and the test data, respectively), then PCA-LDA (0.00–100 and 0.00–100% for the training and the test data, respectively) and PLS-DA (19.35–100% and 0.00–100.00% for the training and the test data, respectively). The results pointed out the applicability of chemometric modeling associated with Raman spectroscopy in the assessment of nutritionally similar samples, such as the studied red paprika varieties.",
publisher = "Academic Press",
journal = "LWT",
title = "Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity",
pages = "113402",
volume = "162",
doi = "10.1016/j.lwt.2022.113402"
}

Kolašinac, S., Pećinar, I., Danojević, D.,& Stevanović Dajić, Z.. (2022). Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity. in LWT
Academic Press., 162, 113402.
https://doi.org/10.1016/j.lwt.2022.113402

Kolašinac S, Pećinar I, Danojević D, Stevanović Dajić Z. Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity. in LWT. 2022;162:113402.
doi:10.1016/j.lwt.2022.113402 .

Kolašinac, Stefan, Pećinar, Ilinka, Danojević, Dario, Stevanović Dajić, Zora, "Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity" in LWT, 162 (2022):113402,
https://doi.org/10.1016/j.lwt.2022.113402 . .

TY  - JOUR
AU  - Glogovac, Svetlana
AU  - Takač, Adam
AU  - Belović, Miona
AU  - Gvozdanović-Varga, Jelica
AU  - Nagl, Nevena
AU  - Cervenski, Janko
AU  - Danojević, Dario
AU  - Trkulja, Dragana
AU  - Prodanovic, Slaven
AU  - Živanović, Tomislav
PY  - 2022
UR  - https://www.researchgate.net/publication/360237772_Characterization_of_tomato_genetic_resources_in_the_function_of_breeding_Characterization_of_tomato_genetic_resources_in_the_function_of_breeding
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/6104
AB  - Focusing on the importance of tomato in human nutrition and the problem of its narrowed genetic variability, the aim of the study was to assess morphological and chemical diversity in IFVCNS germplasm collection. Twenty genotypes were analysed for the following morphological and chemical fruit traits: average mass (g), length (cm), diameter (cm), pericarp thickness (mm), locules number, moisture content (%), total soluble solids (°Brix), ash content (%), total acidity (%) and pH value. Differences among tomato genotypes in all fruit traits were determined. Fruit mass and locules number had the highest coefficient of variation. Four principal components accounted for 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. Hybridization between genotypes from different groups was proposed in order to create new hybrids and varieties and to increase tomato germplasm diversity.
T2  - Field Crops Research
T2  - Field Crops ResearchField Crops Research
T1  - Characterization of tomato genetic resources in the function of breeding
VL  - 59
DO  - 10.5937/ratpov59-36776
ER  - 

@article{
author = "Glogovac, Svetlana and Takač, Adam and Belović, Miona and Gvozdanović-Varga, Jelica and Nagl, Nevena and Cervenski, Janko and Danojević, Dario and Trkulja, Dragana and Prodanovic, Slaven and Živanović, Tomislav",
year = "2022",
abstract = "Focusing on the importance of tomato in human nutrition and the problem of its narrowed genetic variability, the aim of the study was to assess morphological and chemical diversity in IFVCNS germplasm collection. Twenty genotypes were analysed for the following morphological and chemical fruit traits: average mass (g), length (cm), diameter (cm), pericarp thickness (mm), locules number, moisture content (%), total soluble solids (°Brix), ash content (%), total acidity (%) and pH value. Differences among tomato genotypes in all fruit traits were determined. Fruit mass and locules number had the highest coefficient of variation. Four principal components accounted for 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. Hybridization between genotypes from different groups was proposed in order to create new hybrids and varieties and to increase tomato germplasm diversity.",
journal = "Field Crops Research, Field Crops ResearchField Crops Research",
title = "Characterization of tomato genetic resources in the function of breeding",
volume = "59",
doi = "10.5937/ratpov59-36776"
}

Glogovac, S., Takač, A., Belović, M., Gvozdanović-Varga, J., Nagl, N., Cervenski, J., Danojević, D., Trkulja, D., Prodanovic, S.,& Živanović, T.. (2022). Characterization of tomato genetic resources in the function of breeding. in Field Crops Research, 59.
https://doi.org/10.5937/ratpov59-36776

Glogovac S, Takač A, Belović M, Gvozdanović-Varga J, Nagl N, Cervenski J, Danojević D, Trkulja D, Prodanovic S, Živanović T. Characterization of tomato genetic resources in the function of breeding. in Field Crops Research. 2022;59.
doi:10.5937/ratpov59-36776 .

Glogovac, Svetlana, Takač, Adam, Belović, Miona, Gvozdanović-Varga, Jelica, Nagl, Nevena, Cervenski, Janko, Danojević, Dario, Trkulja, Dragana, Prodanovic, Slaven, Živanović, Tomislav, "Characterization of tomato genetic resources in the function of breeding" in Field Crops Research, 59 (2022),
https://doi.org/10.5937/ratpov59-36776 . .

TY  - JOUR
AU  - Kolašinac, Stefan
AU  - Pećinar, Ilinka
AU  - Danojević, Dario
AU  - Aćić, Svetlana
AU  - Dajić-Stevanović, Zora
PY  - 2021
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/5932
AB  - The main goal of the present study is validation of different chemometric models in Raman spectroscopic monitoring of different maturity phases of the red pepper fruit. Successive ripening stages commonly corresponding with different fruit coloration (green, green-brown, brown-red, and deep red) were assessed. The fruit maturation process in red pepper is related to alteration in composition and content of different primary and secondary metabolites, including the most represented carotenoid, the capsanthin. Raman microspectroscopy with wavelength of 532 nm was used to obtain the spectra of the pericarp of different maturation phases. Several multivariate classification methods, such as Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Soft Independent Modeling of Class Analogy (SIMCA) were tested to determine the model which best fits the target ripening phases related to composition and the content of the most represented carotenoids. Concerning different fruit ripening phases, several characteristic bands were obtained, including those at 1514–1517, 1151, and 1003 cm−1, all assigned to carotenoids with nine conjugated double bonds in the main polyene chain (e.g., lutein, beta carotene, beta cryptoxanthin, zeaxanthin, capsorubin, and capsanthin). All tested classification chemometric models had a high rate of prediction accuracy (between 95% and 100%). The SIMCA showed the best result, probably because of using a different algorithm compared with the other tested models.
PB  - John Wiley and Sons Ltd
T2  - Journal of Raman Spectroscopy
T1  - Raman spectroscopic-based chemometric modeling inassessment of red pepper ripening phases and carotenoidsaccumulation
EP  - 1605
IS  - 9
SP  - 1598
VL  - 52
DO  - 10.1002/jrs.6197
ER  - 

@article{
author = "Kolašinac, Stefan and Pećinar, Ilinka and Danojević, Dario and Aćić, Svetlana and Dajić-Stevanović, Zora",
year = "2021",
abstract = "The main goal of the present study is validation of different chemometric models in Raman spectroscopic monitoring of different maturity phases of the red pepper fruit. Successive ripening stages commonly corresponding with different fruit coloration (green, green-brown, brown-red, and deep red) were assessed. The fruit maturation process in red pepper is related to alteration in composition and content of different primary and secondary metabolites, including the most represented carotenoid, the capsanthin. Raman microspectroscopy with wavelength of 532 nm was used to obtain the spectra of the pericarp of different maturation phases. Several multivariate classification methods, such as Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Soft Independent Modeling of Class Analogy (SIMCA) were tested to determine the model which best fits the target ripening phases related to composition and the content of the most represented carotenoids. Concerning different fruit ripening phases, several characteristic bands were obtained, including those at 1514–1517, 1151, and 1003 cm−1, all assigned to carotenoids with nine conjugated double bonds in the main polyene chain (e.g., lutein, beta carotene, beta cryptoxanthin, zeaxanthin, capsorubin, and capsanthin). All tested classification chemometric models had a high rate of prediction accuracy (between 95% and 100%). The SIMCA showed the best result, probably because of using a different algorithm compared with the other tested models.",
publisher = "John Wiley and Sons Ltd",
journal = "Journal of Raman Spectroscopy",
title = "Raman spectroscopic-based chemometric modeling inassessment of red pepper ripening phases and carotenoidsaccumulation",
pages = "1605-1598",
number = "9",
volume = "52",
doi = "10.1002/jrs.6197"
}

Kolašinac, S., Pećinar, I., Danojević, D., Aćić, S.,& Dajić-Stevanović, Z.. (2021). Raman spectroscopic-based chemometric modeling inassessment of red pepper ripening phases and carotenoidsaccumulation. in Journal of Raman Spectroscopy
John Wiley and Sons Ltd., 52(9), 1598-1605.
https://doi.org/10.1002/jrs.6197

Kolašinac S, Pećinar I, Danojević D, Aćić S, Dajić-Stevanović Z. Raman spectroscopic-based chemometric modeling inassessment of red pepper ripening phases and carotenoidsaccumulation. in Journal of Raman Spectroscopy. 2021;52(9):1598-1605.
doi:10.1002/jrs.6197 .

Kolašinac, Stefan, Pećinar, Ilinka, Danojević, Dario, Aćić, Svetlana, Dajić-Stevanović, Zora, "Raman spectroscopic-based chemometric modeling inassessment of red pepper ripening phases and carotenoidsaccumulation" in Journal of Raman Spectroscopy, 52, no. 9 (2021):1598-1605,
https://doi.org/10.1002/jrs.6197 . .