Discrimination and classification of beet and cane sugars and their inverts in maple syrup by FT-Raman

M. M. Paradkar; Josephi Irudayaraj; S. Sakhamuri

Discrimination and classification of beet and cane sugars and their inverts in maple syrup by FT-Raman

M. M. Paradkar, Josephi Irudayaraj, S. Sakhamuri

Research output: Contribution to journal › Article › peer-review

Abstract

Maple syrup is a soft target of adulterators due to its simplicity in chemical composition. Fourier Transform (FT) Raman spectroscopy was used to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar presence in maple syrup. FT-Raman spectrum of adulterated samples was characterized and the regions 400 to 1500 and 2800 to 3000 cm^-1 were used for quantitative and discriminant analysis. Partial least square (PLS) and principal component regression (PCR) analysis were used for quantitative analysis (R² > 0.92) while linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis. Classification of adulterants in maple syrup using LDA and CVA gave a classification accuracy of 95%.

Original language	English (US)
Pages (from-to)	379-383
Number of pages	5
Journal	Applied Engineering in Agriculture
Volume	18
Issue number	3
State	Published - May 1 2002
Externally published	Yes

Keywords

Beet sugar
Cane sugar
Chemometrics
Economic adulteration
FT-Raman spectroscopy
Inverts
Maple syrup

ASJC Scopus subject areas

Engineering(all)

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AU - Paradkar, M. M.

AU - Irudayaraj, Josephi

AU - Sakhamuri, S.

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AB - Maple syrup is a soft target of adulterators due to its simplicity in chemical composition. Fourier Transform (FT) Raman spectroscopy was used to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar presence in maple syrup. FT-Raman spectrum of adulterated samples was characterized and the regions 400 to 1500 and 2800 to 3000 cm-1 were used for quantitative and discriminant analysis. Partial least square (PLS) and principal component regression (PCR) analysis were used for quantitative analysis (R2 > 0.92) while linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis. Classification of adulterants in maple syrup using LDA and CVA gave a classification accuracy of 95%.

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KW - Cane sugar

KW - Chemometrics

KW - Economic adulteration

KW - FT-Raman spectroscopy

KW - Inverts

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Discrimination and classification of beet and cane sugars and their inverts in maple syrup by FT-Raman

Abstract

Keywords

ASJC Scopus subject areas

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