Major Components of Honey Analysis by Near-Infrared Transflectance Spectroscopy

García-Alvarez, M; Huidobro, J. F.; Hermida, Marcelo Antonio Martínez; Rodríguez-Otero, J. L.

doi:10.1021/jf000170v

Cited by 57 publications

(43 citation statements)

References 13 publications

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“…2). The SEP is in the same range between 0.16 and 0.41 g/100 g as shown by a number of authors [7][8][9][10][11][12][13].…”

Section: Water Contentmentioning

confidence: 55%

“…Accurate predictions were obtained for fructose, glucose, sucrose, maltose, water and ash content as well as for the fructose/glucose and glucose/water ratios in honey samples from different crops [7][8][9][10][11][12][13]. Furthermore, noncompositional characteristics of honey such as electrical conductivity, colour and polarimetric properties (direct polarisation, polarisation after inversion, specific rotation in dry matter and polarisation due to non-monosaccharides) have also been successfully calibrated [10,14].…”

Section: Introductionmentioning

confidence: 99%

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Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry

Ruoff

Luginbühl²,

Bogdanov³

et al. 2007

Eur Food Res Technol

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Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated to quantitatively determine 24 different measurands in honey. The reference values of 421 honey samples of different botanical origins were determined by classical physical and chemical methods. Partial least squares regression was used to develop the calibration models for the measurands studied. These calibrations were then validated using independent samples and proved satisfying accuracies for the determination of water (standard error of prediction: 0.3 g/100 g), glucose (1.3 g/100 g), fructose (1.6 g/100 g), sucrose (0.4 g/100 g), total monosaccharide content (2.6 g/100 g) as well as fructose/glucose ratio (0.09) and glucose/water ratio (0.12). The prediction accuracy for hydroxymethylfurfural, proline, pH-value, electrical conductivity, free acidity and the minor sugars maltose, turanose, nigerose, erlose, trehalose, isomaltose, kojibiose, melezitose, raffinose, gentiobiose, melibiose, maltotriose was poor and unreliable. The results demonstrate that near-infrared spectrometry is a valuable, rapid and non-destructive tool for the quantitative analysis of some measurands related to the main components in honey.

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“…2). The SEP is in the same range between 0.16 and 0.41 g/100 g as shown by a number of authors [7][8][9][10][11][12][13].…”

Section: Water Contentmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry

Ruoff

Luginbühl²,

Bogdanov³

et al. 2007

Eur Food Res Technol

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“…Other researchers (Cho and Hong, 1998;Ha et al, 1998;Quiu et al, 1999;García-Alvarez et al, 2000) have shown that near infrared spectroscopy could be method for honey analysis. They obtained similar results for the determination of the sugar components.…”

Section: Discussionmentioning

confidence: 99%

“…Other researchers (Cho and Hong, 1998;Ha et al, 1998;Quiu et al, 1999;García-Alvarez et al, 2000) have already shown that it is possible to analyse the main sugars and moisture in honey by using near-infrared spectroscopy (NIR). Quiu and coworkers failed to determine the free acids by NIR and published no results for the physical parameters such as electrical conductivity and pH.…”

Section: Introductionmentioning

confidence: 99%

Infrared spectroscopy in routine quality analysis of honey

2002

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-Fourier-transform infrared spectroscopy (FT-IR) was used as a rapid, simple and reliable method for quality analysis of honey. More than 1600 samples of honey were analysed using FT-IR and reference methods to develop a partial least-square regression based calibration model for the major components of honey (sugars, proline, free acids, invertase, moisture, hydroxymethylfurfural, pH and electrical conductivity). The coefficient of determination R 2 ranging from 0.84-0.98 indicates an acceptable calibration for most of the parameters. Statistical verification of the spectral analysis in routine analysis showed a high correlation (0.81-0.99), good repeatability (0.84-0.99), no environmental influences (P > 0.05) and no significant statistical differences to the reference methods. This study shows that not only chemical composition but also the physical properties can be determined by FT-IR. The calibrations can be adapted to different analytical standards and honey sources. Fourier-transform infrared spectroscopy / FT-IR / honey quality/ sugar analysis

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“…Handling each analysis individually also increases time, required sample amount and therefore the expenses needed to complete the analyses (Cozzolino et al, 2011). Hence, today's methods are unable to meet the increasing demands and provide inexpensive solutions (Garcia-Alvarez et al, 2000). Because of potential mislabeling and adulteration risks, regulatory agencies and industry have promoted research to find new, simple and economical methods for the determination of honey quality (Ruiz-Matute et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Quality Control of Honey Using New Generation Infrared Spectrometers

Ayvaz

2017

Turkish JAF Sci.Tech.

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The objective of this study was to develop a rapid infrared technique to determine 10 key quality parameters (sucrose, glucose, fructose, reducing sugar, 5-HMF, °Brix, moisture content, water activity, pH and free acidity) in honey by using new generation portable and handheld devices. The composition of honey samples (n=59) collected from different parts of Turkey was analyzed by using established reference methods, giving wide range of concentrations for each parameter. The levels of sucrose and 5-HMF in some samples were above the established regulatory limits (Codex Alimentarius and European Union standards), indicating possible adulteration or process and storage abuse. Spectra were collected by using portable Fourier-Transformed infrared (FTIR) and handheld NIR (Near Infrared) spectrometers. Partial least squares regression (PLSR) approach was used to correlate the spectral features with compositional reference values, giving strong linear correlation coefficients and standard errors of prediction. Although both systems performed similarly, portable FTIR system was superior in predictions of sucrose, 5-HMF and free acidity while portable NIR system performed noticeably better for °Brix and moisture content. The data indicates that all of the 10 parameters can be measured within the minutes using both systems, providing reliable screening capabilities, flexibility and the potential for in-field applications.

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Major Components of Honey Analysis by Near-Infrared Transflectance Spectroscopy

Cited by 57 publications

References 13 publications

Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry

Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry

Infrared spectroscopy in routine quality analysis of honey

Quality Control of Honey Using New Generation Infrared Spectrometers

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