Classification of simple and complex sugar adulterants in honey by mid-infrared spectroscopy

Adulteration of honey with sugars is the most crucial quality assurance concern to the honey industry. The application of Fourier transform infrared spectroscopy as a screening tool for the determination of the type of sugar adulterant in honey was investigated. Spectra of honey adulterated with simple and complex sugars were recorded in the mid-infrared range using the attenuated total reflectance accessory of a Fourier transform infrared spectrometer. Adulterants considered were sugars (glucose, fructose and sucrose) and invert sugars (cane invert and beet invert). Predictive models were developed to classify the adulterated honey samples using discriminant analysis. Spectral data were compressed using principal component analysis and partial least-square methods. Linear discriminant analysis was used to discriminate the type of adulterant in three different honey varieties. An optimum classification of 100% was achieved for honey samples adulterated with glucose, fructose, sucrose and beet and cane invert sugars. Results demonstrated that discriminant analysis of the spectra of adulterated honey samples could be used for rapid detection of adulteration in honey.     

Detection of inverted beet sugar adulteration of honey by FTIR spectroscopy

A combination of Fourier transform infrared (FTIR) spectroscopy and multivariate statistics as a screening tool for the determination of beet medium invert sugar adulteration in three different varieties of honey is discussed. Honey samples with different concentrations of beet invert sugar were scanned using the attenuated total reflectance (ATR) accessory of the Bio‐Rad FTS‐6000 Fourier transform spectrometer. The spectral wavenumber region between 950 and 1500 cm^?1 was selected for partial least squares (PLS) regression to develop calibration models for beet invert sugar determination in honey samples. Results from the PLS (first derivative) models were slightly better than those obtained with other calibration models. Predictive models were also developed to classify beet sugar invert in three different varieties of honey samples using discriminant analysis. Spectral data were compressed using the principal component method, and linear discriminant and canonical variate analyses were used to detect the level of beet invert sugar in honey samples. The best predictive model for adulterated honey samples was achieved with canonical variate analysis, which successfully classified 88–94 per cent of the validation set. The present study demonstrated that Fourier transform infrared spectroscopy could be used for rapid detection of beet invert sugar adulteration in different varieties of honey. © 2001 Society of Chemical Industry     

Discrimination and classification of adulterants in maple syrup with the use of infrared spectroscopic techniques

Food adulteration is a profit‐making business for some unscrupulous manufacturers. Maple syrup is a soft target of adulterators owing to its simplicity of chemical composition. In this study the use of Fourier transform infrared (FTIR) spectroscopy and near‐infrared (NIR) spectroscopy to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar solutions in maple syrup was investigated. The FTIR spectrum of adulterated samples was characterised and the regions 800–1200 cm^?1 (carbohydrates) and 1200–1800 and 2800–3200 cm^?1 (carbohydrates, carboxylic acids and amino acids) were used for detection. The region between 1100 and 1660 nm in the NIR spectrum was used for analysis. Linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis, while partial least squares (PLS) and principal component regression (PCR) were used for quantitative analysis. FTIR was more accurate in predicting adulteration using two different regions (R² > 0.93 and >0.98) compared with NIR (R² > 0.93). Classification and quantification of adulterants in maple syrup show that NIR and FTIR can be used for detecting adulterants such as pure beet and cane sugar solutions, but FTIR was superior to NIR in detecting invert syrups. © 2003 Society of Chemical Industry     

A Rapid Spectroscopic Technique for Determining Honey Adulteration with Corn Syrup

ABSTRACT: A combination of Fourier transform infrared spectroscopy with multivariate procedures was used for determining the level of sugar addition to honey. Spectra of honey adulterated with different levels of glucose, fructose, sucrose, and corn syrup were recorded in the mid-infrared range using the attenuated total reflectance accessory. The standard error of prediction (SEP) in validation set was between 1.99% and 2.22% using partial least square (PLS) on first derivative transformed data. Results showed that the combined model for 3 different varieties of honey gave lower correlation. It is demonstrated that Fourier transform infrared spectroscopy has good potential for detecting corn-syrup adulteration in honey in less than 5 min.     

Prediction of Inverted Cane Sugar Adulteration of Honey by Fourier Transform Infrared Spectroscopy

Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflection (ATR) sampling accessory has been used to determine the cane medium invert sugar in 3 different varieties of honey. Predictive models were developed to classify the cane sugar-adulterated honey samples, using discriminant analysis. Linear discriminant and canonical variate analysis were used to discriminate adulterated honey samples. The optimum classification of 88 to 96.4% was achieved in a validation set, using linear discriminant analysis with the partial least squares (PLS) data compression technique. Calibrations developed to predict the spiked inverted cane sugar concentration in honey with PLS-1st derivative method gave standard error of prediction (SEP) between 2.8 to 3.6 % w/w.     

Comparison of FTIR, FT-Raman, and NIR Spectroscopy in a Maple Syrup Adulteration Study

ABSTRACT: Maple syrup is prone to adulteration with cheaper sugars, such as corn syrup, due to its simplicity in chemical composition. The adulterated samples were characterized by Fourier Transform infrared (FTIR) spectroscopy in the region of 400 to 4000 cm_-1. Other techniques used for detection and in characterization of samples were the near infrared (NIR; 600 to 1700nm) and Fourier Transform-Raman (FT-Raman; 400 to 4000cm_-1) spectroscopy. Quantifying and classifying adulterants using chemometrics shows that all spectroscopic methods adopted were efficient, but FTIR and FT-Raman were superior to NIR in quantitative characterization of adulterants in maple syrup.     

Discrimination and classification of adulterants in maple syrup with the use of infrared spectroscopic techniques

Food adulteration is a profit‐making business for some unscrupulous manufacturers. Maple syrup is a soft target for adulterators owing to its simplicity of chemical composition. The use of infrared spectroscopic techniques such as Fourier transform infrared (FTIR) and near‐infrared (NIR) as a tool to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar solutions in maple syrup was investigated. The FTIR spectra of adulterated samples were characterised and the regions of 800–1200 cm^?1 (carbohydrates) and 1200–1800 and 2800–3200 cm^?1 (carbohydrates, carboxylic acids and amino acids) were used for detection. The NIR spectral region between 1100 and 1660 nm was used for analysis. Linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis, while partial least squares (PLS) and principal component regression (PCR) were used for quantitative analysis. FTIR was more accurate in predicting adulteration using the two different regions (R² > 0.93 and 0.98) compared with NIR (R² > 0.93). Classification and quantification of adulterants in maple syrup show that both NIR and FTIR can be used for detecting adulterants such as pure beet and cane sugar solutions, but FTIR was superior to NIR in detecting invert syrups. © 2002 Society of Chemical Industry     

Monitoring Chemical Changes in Some Foods Using Fourier Transform Photoacoustic Spectroscopy

The potential of Fourier transform infrared photoacoustic spectroscopy (FTIR‐PAS) to characterize some common foods was studied. Lard, peanut butter, mayonnaise, and whipped topping were heated to 60 and 90 °C separately, and the spectra were obtained periodically for a period of up to 32 and 16 d, respectively. Key bands in the mid‐infrared spectral region were examined to monitor changes presumably due to lipid oxidation. Spectral data were analyzed, using principal component analysis (PCA) correlation, and linear discriminate analysis (LDA) techniques with Mahalanobis distances to estimate the extent of deterioration attributable to oxidation. The PAS was found to be simple, rapid, and nondestructive. It required limited sample preparation, and proved highly desirable for analyzing low‐moisture samples.     

Rapid determination of tetracycline in milk by FT-MIR and FT-NIR spectroscopy

The feasibility of measuring tetracycline at the ppb levels in milk was investigated by Fourier transform mid-infrared (FT-MIR) and Fourier transform near-infrared (FT-NIR) spectroscopic techniques. Milk samples spiked with different concentrations of tetracycline were scanned using FT-MIR and FT-NIR spectroscopy. Suitable spectral wave number regions were selected for principal least square (PLS) regression models development. Prediction errors were high when the calibration model was developed using the wide range of tetracycline concentrations (4 to 2000 ppb) in milk. Maximum correlation coefficient (R2) value of about 0.89 was obtained for the validation models developed using different concentration ranges. Prediction errors were high for FT-NIR method. Results indicated that FT-MIR spectroscopy could be used for rapid detection of tetracycline hydrochloride residues in milk.     

Analysis of potato chips using FTIR photoacoustic spectroscopy

The suitability of Fourier transform infrared photoacoustic spectroscopy (FTIR‐PAS) for analysing potato chips was investigated. The functional groups, vibration modes and intensities corresponding to frequencies related to moisture, fat and protein in PA spectra were labelled. Oxidation experiments were carried out by heating home‐made chips in a convection oven at 80 °C. Changes in chemical groups related to fat and oil were observed visually and statistically. Spectral data were analysed using PCA correlation and a linear discriminant analysis technique with squared Mahalanobis distance metric to estimate the extent of oxidation. Results showed that deterioration indeed could be monitored by photoacoustic spectroscopy. Depth profile analysis of the samples showed that a spectral difference in the fat, moisture and protein bands at different layers exists. Results demonstrated that FTIR‐PAS with its depth‐profiling capability could be used for qualitative analysis. © 2000 Society of Chemical Industry