Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey
Само за регистроване кориснике
2021
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Introduction: Raman spectroscopy, as a powerful diagnostic technique for molecular analysis of food samples, was
used as a rapid and reliable method for the discrimination of honey according to their source, as well as for faster
detection of honey counterfeits. Since honey contains different proportions of sugars as the dominant components, the
certain characteristic vibrational mode is useful to differentiate structural-based changes in these carbohydrates.
Objective: In order to contribute to a comprehensive database of Raman bands obtained from food samples, the
present study aimed to detect and confirm differences in chemical composition between homemade and commercial
honey using Raman spectroscopy as a fast tool combined with multivariate analysis (PCA).
Materials & methods: Raman scattering was excited by a laser at a wavelength of 532 nm equipped with 1200
lines/mm grating. The spectra preprocessing was realized using Spectragryph software, version 1.2.13. Principal
c...omponent analysis (PCA) was performed using PAST software. Multivariate analysis, based on PCA, was applied in
order to detect a possible difference in the chemical composition of honey samples.
Results: Raman spectra of honey show bands at 334, 420, 517, 624, 702, 816, 863, 915, 1070 and 1123 cm-1, which
can be attributed to the sugars expected to occur in honey (glucose, fructose and sucrose). Glucose and fructose
have dominant vibrational modes of C–C–C, C–C–O, C–O and C–C reported in the range of 200–500 cm-1. The
higher intensity band at ~417 cm-1 and its shoulder at 448 cm-1 are probably attributed to the C–C–O vibration of α-
and β- glucose, respectively. The glucose band at 417 cm-1 and band at 420 cm-1 of fructose band overlap, while 624
cm-1 is related to ring deformation of fructose. The band at 517 cm-1 could be assigned to the skeletal vibration of
glucose. The medium intensity bands in the range from 816 to 975 cm-1 are related to vibrations of glucose and
fructose. The band at 1123 cm-1 is assigned to the C-OH deformation of the glucose and sucrose, while a lower
intensity band at 1370 cm-1 is assigned to the CH and OH bending mode of sucrose.
The minor contribution of other carbohydrates, proteins, amino acids and organic acids were confirmed by Raman
spectroscopy by the bands at 334, 1077, 1266 cm-1 and 1460 cm-1.
The PCA analysis was performed using about forty Raman spectra. The score plot of PC1 versus PC2 shows a
reasonably good separation between the samples, where the first and second principal components described
86.21% of data variance. The score plot suggests the clear existence of separation between traditional and
commercial honey samples along PC1 axis. The loading plot shows that the variables with the highest positive
contribution along PC1 axis corresponded to the signals at 284, 392, 682, 795, 890, 1118 and 1198 cm-1, while
signals at 436 and 1026 cm-1 have the highest negative effects. Traditional honey comparing with commercial differs
in a higher amount in β-glucose and fructose (assigned to pyranoid ring) content.
Conclusion: This study confirmed that Raman spectroscopy can be applied for the determination of chemical
composition and combined with chemometric methods could confirm the differentiation of honey samples.
Spectroscopic methods, comparing with standard analytical tools, are especially suitable for this kind of evaluation
since they are fast, non-destructive and require a small amount of sample for analysis.
Извор:
Microscopy Conference 2021, 2021, 395-Издавач:
- MCM
Институција/група
Poljoprivredni fakultetTY - CONF AU - Pećinar, Ilinka AU - Rančić, Dragana AU - Lević, Steva AU - Kilibarda, Sofija AU - Mačukanović-Jocić, Marina PY - 2021 UR - http://aspace.agrif.bg.ac.rs/handle/123456789/6783 AB - Introduction: Raman spectroscopy, as a powerful diagnostic technique for molecular analysis of food samples, was used as a rapid and reliable method for the discrimination of honey according to their source, as well as for faster detection of honey counterfeits. Since honey contains different proportions of sugars as the dominant components, the certain characteristic vibrational mode is useful to differentiate structural-based changes in these carbohydrates. Objective: In order to contribute to a comprehensive database of Raman bands obtained from food samples, the present study aimed to detect and confirm differences in chemical composition between homemade and commercial honey using Raman spectroscopy as a fast tool combined with multivariate analysis (PCA). Materials & methods: Raman scattering was excited by a laser at a wavelength of 532 nm equipped with 1200 lines/mm grating. The spectra preprocessing was realized using Spectragryph software, version 1.2.13. Principal component analysis (PCA) was performed using PAST software. Multivariate analysis, based on PCA, was applied in order to detect a possible difference in the chemical composition of honey samples. Results: Raman spectra of honey show bands at 334, 420, 517, 624, 702, 816, 863, 915, 1070 and 1123 cm-1, which can be attributed to the sugars expected to occur in honey (glucose, fructose and sucrose). Glucose and fructose have dominant vibrational modes of C–C–C, C–C–O, C–O and C–C reported in the range of 200–500 cm-1. The higher intensity band at ~417 cm-1 and its shoulder at 448 cm-1 are probably attributed to the C–C–O vibration of α- and β- glucose, respectively. The glucose band at 417 cm-1 and band at 420 cm-1 of fructose band overlap, while 624 cm-1 is related to ring deformation of fructose. The band at 517 cm-1 could be assigned to the skeletal vibration of glucose. The medium intensity bands in the range from 816 to 975 cm-1 are related to vibrations of glucose and fructose. The band at 1123 cm-1 is assigned to the C-OH deformation of the glucose and sucrose, while a lower intensity band at 1370 cm-1 is assigned to the CH and OH bending mode of sucrose. The minor contribution of other carbohydrates, proteins, amino acids and organic acids were confirmed by Raman spectroscopy by the bands at 334, 1077, 1266 cm-1 and 1460 cm-1. The PCA analysis was performed using about forty Raman spectra. The score plot of PC1 versus PC2 shows a reasonably good separation between the samples, where the first and second principal components described 86.21% of data variance. The score plot suggests the clear existence of separation between traditional and commercial honey samples along PC1 axis. The loading plot shows that the variables with the highest positive contribution along PC1 axis corresponded to the signals at 284, 392, 682, 795, 890, 1118 and 1198 cm-1, while signals at 436 and 1026 cm-1 have the highest negative effects. Traditional honey comparing with commercial differs in a higher amount in β-glucose and fructose (assigned to pyranoid ring) content. Conclusion: This study confirmed that Raman spectroscopy can be applied for the determination of chemical composition and combined with chemometric methods could confirm the differentiation of honey samples. Spectroscopic methods, comparing with standard analytical tools, are especially suitable for this kind of evaluation since they are fast, non-destructive and require a small amount of sample for analysis. PB - MCM C3 - Microscopy Conference 2021 T1 - Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey SP - 395 UR - https://hdl.handle.net/21.15107/rcub_agrospace_6783 ER -
@conference{ author = "Pećinar, Ilinka and Rančić, Dragana and Lević, Steva and Kilibarda, Sofija and Mačukanović-Jocić, Marina", year = "2021", abstract = "Introduction: Raman spectroscopy, as a powerful diagnostic technique for molecular analysis of food samples, was used as a rapid and reliable method for the discrimination of honey according to their source, as well as for faster detection of honey counterfeits. Since honey contains different proportions of sugars as the dominant components, the certain characteristic vibrational mode is useful to differentiate structural-based changes in these carbohydrates. Objective: In order to contribute to a comprehensive database of Raman bands obtained from food samples, the present study aimed to detect and confirm differences in chemical composition between homemade and commercial honey using Raman spectroscopy as a fast tool combined with multivariate analysis (PCA). Materials & methods: Raman scattering was excited by a laser at a wavelength of 532 nm equipped with 1200 lines/mm grating. The spectra preprocessing was realized using Spectragryph software, version 1.2.13. Principal component analysis (PCA) was performed using PAST software. Multivariate analysis, based on PCA, was applied in order to detect a possible difference in the chemical composition of honey samples. Results: Raman spectra of honey show bands at 334, 420, 517, 624, 702, 816, 863, 915, 1070 and 1123 cm-1, which can be attributed to the sugars expected to occur in honey (glucose, fructose and sucrose). Glucose and fructose have dominant vibrational modes of C–C–C, C–C–O, C–O and C–C reported in the range of 200–500 cm-1. The higher intensity band at ~417 cm-1 and its shoulder at 448 cm-1 are probably attributed to the C–C–O vibration of α- and β- glucose, respectively. The glucose band at 417 cm-1 and band at 420 cm-1 of fructose band overlap, while 624 cm-1 is related to ring deformation of fructose. The band at 517 cm-1 could be assigned to the skeletal vibration of glucose. The medium intensity bands in the range from 816 to 975 cm-1 are related to vibrations of glucose and fructose. The band at 1123 cm-1 is assigned to the C-OH deformation of the glucose and sucrose, while a lower intensity band at 1370 cm-1 is assigned to the CH and OH bending mode of sucrose. The minor contribution of other carbohydrates, proteins, amino acids and organic acids were confirmed by Raman spectroscopy by the bands at 334, 1077, 1266 cm-1 and 1460 cm-1. The PCA analysis was performed using about forty Raman spectra. The score plot of PC1 versus PC2 shows a reasonably good separation between the samples, where the first and second principal components described 86.21% of data variance. The score plot suggests the clear existence of separation between traditional and commercial honey samples along PC1 axis. The loading plot shows that the variables with the highest positive contribution along PC1 axis corresponded to the signals at 284, 392, 682, 795, 890, 1118 and 1198 cm-1, while signals at 436 and 1026 cm-1 have the highest negative effects. Traditional honey comparing with commercial differs in a higher amount in β-glucose and fructose (assigned to pyranoid ring) content. Conclusion: This study confirmed that Raman spectroscopy can be applied for the determination of chemical composition and combined with chemometric methods could confirm the differentiation of honey samples. Spectroscopic methods, comparing with standard analytical tools, are especially suitable for this kind of evaluation since they are fast, non-destructive and require a small amount of sample for analysis.", publisher = "MCM", journal = "Microscopy Conference 2021", title = "Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey", pages = "395", url = "https://hdl.handle.net/21.15107/rcub_agrospace_6783" }
Pećinar, I., Rančić, D., Lević, S., Kilibarda, S.,& Mačukanović-Jocić, M.. (2021). Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey. in Microscopy Conference 2021 MCM., 395. https://hdl.handle.net/21.15107/rcub_agrospace_6783
Pećinar I, Rančić D, Lević S, Kilibarda S, Mačukanović-Jocić M. Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey. in Microscopy Conference 2021. 2021;:395. https://hdl.handle.net/21.15107/rcub_agrospace_6783 .
Pećinar, Ilinka, Rančić, Dragana, Lević, Steva, Kilibarda, Sofija, Mačukanović-Jocić, Marina, "Raman spectroscopy coupled with multivariate analysis of homemade and commercial honey" in Microscopy Conference 2021 (2021):395, https://hdl.handle.net/21.15107/rcub_agrospace_6783 .