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     

Discrimination and classification of beet and cane inverts in honey by FT-Raman spectroscopy

As a natural product, honey has been prone to adulteration. Adulteration of honey by substituting with cheap invert sugars is a critical issue in the honey industry. Fourier Transform (FT) Raman Spectroscopy was used to detect adulterants such as cane and beet invert in honey. FT Ra man spectrum of adulterated samples were characterized and the region between 200 and 1600 cm⁻¹ (representing carbohydrates and amino acid fractions) was used for quantitative and discriminant analysis. Partial least squares, and principal component regression analysis were used for quantitative analysis while linear discriminant analysis and canonical variate analysis (CVA) were used for discriminant analysis. FT-Raman spectroscopy was efficient in predicting beet and cane invert adulterants (R²>0.91) in all three floral types of honey considered. Classification of adulterants in honey using CVA gave a minimum classification accuracy of about 96%.     

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.     

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     

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.     

Fast aroma profiling to detect invert sugar adulteration with zNose™

Rapid aroma profiling of food products is a potential technique for at‐line food quality evaluation. In this work the potential of zNose^?, a surface acoustic wave‐based sensor, was tested for honey quality assessment. Buckwheat honey was purposely adulterated with different levels of beet and cane invert sugar, and its aroma profile was measured after different periods of headspace equilibration. PCA using the relative peak areas as well as the full zNose^? spectra resulted in a clear separation between honey, and beet and cane invert sugar adulterants in the mixtures. PLS models were developed for quantitative estimation of adulterants using the entire spectra as well as the relative peak areas. Better predictions were obtained with the PLS models based on spectra than with those based on relative peak areas. A correlation of validation of 0.98 was obtained between predicted and measured percentage of adulteration. This model was also successfully validated with an external set of honey mixtures, resulting in an average deviation of 3% adulteration between the predicted and reference values. Copyright © 2004 Society of Chemical Industry     

Physico‐chemical and technological studies on sugar beet roots

The morphological and chemical characteristics of ten varieties of sugar beet roots were evaluated during the season of 1996–1997. The best morphological characteristics were found in Top, Ito and Pamela varieties. The highest expected technological yield of sugar was found in Pamela and Top. The chemical constituents of different varieties of sugar‐beet roots showed significant differences. The suitability of sugar beet juice for preparing beet syrup as a new product was also evaluated and compared with sugar cane syrup. Purified beet‐syrups concentrated under vacuum or under atmospheric pressure showed more stability during storage than sugar cane syrup. The effect of storage conditions (at cold storage and at room temperature) and packaging materials (glass and polyethylene high‐density bottles) on properties of beet‐syrup and sugar cane syrup were also studied.     

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.     

Application of FTIR-HATR spectroscopy and multivariate analysis to the quantification of adulterants in Mexican honeys

Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) accessory was used to quantify three different adulterants (corn syrup, high fructose corn syrup and inverted sugar) in honeys of four different locations of México (Chiapas, Oaxaca, Estado de México and Morelos). The optimal calibrations for the three adulterants were developed with partial least squares (PLS). The developed models were validated with different independent data sets being the standard error of prediction (SEP) between 1.5 and 2.1 for corn syrup, 2.1–3.0 for high fructose corn syrup and 1.4–2.5 for inverted sugar, showing the applicability of these models to the detection and quantification of adulterants in honey bee. Classification of the Mexican honeys from the four different states was carried out with soft independent modeling class analogy giving 100% correct classification rate and no false positive results were obtained.     

Detection of honey adulteration with beet sugar using stable isotope methodology

A usual aspect of our work involves the analysis of honey samples for later sale, following current Spanish legislation. Such analyses essentially consist of studying pollen sediments, and sensory and physicochemical analyses. With this background, it seemed appropriate to investigate possible adulterations due to the addition of sugar (beet and cane). To do this, we selected 49 samples of honey obtained from 14 floral types and used them for pollinic and sensory analyses and to detect possible adulterations due to the addition of beet sugar products (treating the oligosaccharide fraction contained in the honey with the galactose oxidase reaction) or due to corn syrup addition (with normal δ¹³C stable carbon isotope ratios). After classifying the samples according to the results of the pollen and sensory analyses, further assays were conducted. From the results it was concluded that 15% of the samples had been adulterated with beet sugar and 4% with cane sugar. The implementation of many analyses for each sample means that the results can be intercorrelated very well.     

The use of Fourier transform mid infrared (FT-MIR) spectroscopy for detection and quantification of adulteration in virgin coconut oil

Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000–650 cm⁻¹ on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R²) of 0.999.     

First Break Forward Interval PLS (FB-FiPLS) Procedure as Potential Tool in Analysis of FTIR Data for Fast and Robust Quantitative Determination of Food Adulteration

Ternary mixtures of sugar solutions containing maple syrup were studied quantitatively using Fourier transform infrared (FTIR) attenuated total reflectance (ATR) technique coupled with partial least squares regression (PLS) and selection of spectral variables. Two ternary mixtures were analyzed; first ternary mixture contained maple syrup, white sugar solution, and fully inverted sugar solution; second ternary mixture comprised maple syrup, white, and brown sugar solutions. In this paper, a procedure for selection of spectral variables with PLS, called first break forward interval PLS (FB-FiPLS), is tested on maple syrup adulteration. The method achieved almost exactly the same performance as synergy interval PLS (SiPLS) but with much shorter computational time. The upper limit of number of latent variables (LVs), which is the critical factor for both interval PLS methods, was determined using repeated double cross-validation on whole spectral region of calibration set for each analyzed component in each analyzed ternary mixture set. FB-FiPLS procedure for selection of spectral variables, using only root mean square error of cross validation (RMSECV) values for whole optimization of spectral variables, is fast and robust. After spectral variables and LVs for each particular model had been selected with minimum RMSECV of FB-FiPLS procedure, final results in terms of RMSECV and RMSEP for FB-FiPLS were in most cases statistically significantly better than PLS on whole spectral region and on selected spectral regions. Predictions of each component in analyzed ternary mixture set is promising (R ²(training set)?>?0.98, R ²(test set)?>?0.97), especially for fully inverted sugar solution (RMSEP?=?0.142 % w/w).     

拉曼光谱法快速鉴别蜂蜜中掺入甜菜糖浆的可行性研究

对蜂蜜用各种廉价的糖浆掺假,一直是蜂蜜行业的严重问题。本文利用拉曼光谱结合化学计量学方法对蜂蜜中掺入甜菜糖浆进行鉴别。用airPLS法扣除拉曼荧光背景,用自归一化法预处理光谱,在全谱范围(4000～10000cm^-1)内建立偏最小二乘-线性判别分析（PLS-LDA）模型,并进行预测。训练集10折交互验证的判别总正确率为90.4%,预测集的判别总正确率为95.4%。实验结果表明拉曼光谱结合化学计量学方法可快速鉴别蜂蜜中掺入的甜菜糖浆。     

Approaches to Adulteration Detection in Instant Coffees using Infrared Spectroscopy and Chemometrics

Fourier transform infrared (FTIR) spectroscopy is examined as a rapid alternative to wet chemistry methods for the detection of adulteration of freeze-dried instant coffees. Spectra have been collected of pure coffees, and of samples adulterated with glucose, starch or chicory in the range 20–100 g kg⁻¹. Two different FTIR sampling methods have been employed: diffuse reflectance, and attenuated total reflectance. Three different statistical treatments of the spectra were carried out. Firstly, the spectra were compressed by principal component analysis and a linear discriminant analysis performed. With this approach, a 98% successful classification rate was achieved. Secondly, a simultaneous partial least square regression was carried out for the content of three added carbohydrates (xylose, glucose and fructose) in order to assess the potential of FTIR spectroscopy for determining the carbohydrate profile of instant coffee. Lastly, the discrimination of pure from adulterated coffee was performed using an artificial neural network (ANN). A perfect rate of assignment was obtained. The generalization ability of the ANN was tested on an independent validation data set; again, 100% correct classifications were achieved.     

Combined use of HMF and furosine to assess fresh honey quality

BACKGROUND: The quality of honey can be affected by practices such as adulteration, inadequate storage or the application of severe heat treatments. Because hydroxymehylfurfural (HMF) is an indicator of honey freshness and furosine (ε‐2‐furoylmethyl lysine) has proved to be a useful chemical indicator of the progress of the Maillard reaction in foods, the aim of this work was to assess their usefulness as indicators of fresh honey quality. The effect of heat treatment, storage and adulteration with different types of syrups on HMF and furosine content has been studied. RESULTS: In fresh honey, HMF and furosine values ranged from 0.9 to 14.6 mg kg^?1 of product and from 3.06 to 12.06 g kg^?1 of protein, respectively. Heating of honey samples with different pH (3.76 and 5.14) produced slight increases in HMF content and negligible changes were detected in furosine values. The storage of fresh honey for 2 years caused a high increase in the HMF level, reaching values above EU limits. However, furosine showed a different behavior depending on the type of honey sample. Adulteration assays using different syrups produced an increase in HMF and a decrease of furosine values by dilution effect. HMF content of adulterated honey samples with syrup of known origin did not exceed EU limits. CONCLUSION: These results show the influence of long periods of storage or adulteration, using different percentages of corn or invert sugar syrups, on HMF and furosine content of fresh honey. This seems to indicate that the combination of HMF and furosine may be useful for evaluating the quality of fresh honey. Copyright © 2009 Society of Chemical Industry     

Rapid Determination of Invert Cane Sugar Adulteration in Honey Using FTIR Spectroscopy and Multivariate Analysis

ABSTRACT: Fourier transform infrared spectroscopy with an attenuated total reflection sampling accessory was combined with multivariate analysis to determine the level (1% to 25%, wt/wt) of invert cane sugar adulteration in honey. On the basis of the spectral data compression by principal component analysis and partial least squares, linear discriminant analysis (LDA), and canonical variate analysis (CVA), models were developed and validated. Two types of artificial neural networks were applied: a quick back propagation network (BPN) and a radial basis function network (RBFN). The prediction success rates were better with LDA (93.75% for validation set) and BPN (93.75%) than with CVA (87.50%) and RBFN (81.25%).     

Authentication analysis of cod liver oil from beef fat using fatty acid composition and FTIR spectra

This study aimed to authenticate cod liver oil (CLO) from beef fat (BF) by determining the level of BF as a fat adulterant in CLO. Two instrumental techniques, namely GC-FID for fatty acid analysis and Fourier transform infrared (FTIR) spectroscopy, were exploited for such authentication. The decreased level of some fatty acids, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), could be used as an indicative means to detect the adulteration of CLO with BF. In addition, FTIR spectroscopy combined with partial least-squares (PLS) at frequency regions of 1200–1000?cm^?1 was successfully developed for the quantification of BF in CLO. Using the PLS model, the errors obtained in calibration and prediction samples were 0.55% and 0.82% v/v, respectively.     

Solid-Phase Extraction and Procedure for Determination of Phenolic Compounds in Maple Syrup

A solid phase extraction procedure was developed for the extraction of phenolic compounds from maple syrup. The list of targeted chemicals contains phenolic acids as well as aldehydes, flavanols and others such as coniferyl alcohol and 5-hydroxymethyl furfural. The procedure consists in passing a small quantity of maple syrup, 1 g diluted in 2 ml deionized water, through an Oasis HLB cartridge of 200 mg. The cleanest extracts were obtained by rinsing the cartridge load with formic acid 2 %/methanol (9:1). The analytes eluted with methanol were passed in an high-performance liquid chromatography (HPLC)-DAD system for analysis. The method performances show good recoveries; excluding gallic acid measured at 49 %, the chemical recoveries ranged from 81 to 119 %. Moreover, the method repeatability is less than 12 % (RSD) relative standard deviation for all chemicals except for epicatechin (20 %). The analysis method was applied for the determination of phenolic compounds in maple syrups from different color classes (Extra Light to Amber). Results show that concentrations of phenolic compounds vary among syrup classes and the greatest concentration was observed for the Amber syrups.     

Partial demineralization of maple sap by electrodialysis: impact on syrup sensory and physicochemical characteristics

In this project, samples of osmosed maple saps were demineralized to 12.5 and 25% levels by electrodialysis (ED). The effect of this treatment on the composition and the physicochemical and sensory properties of maple syrups obtained from demineralized maple sap was evaluated. The ED technology was efficient to decrease levels of malic acid and calcium in osmosed maple saps. Effectively, 38% and 24% decreases in malic acid and calcium respectively were reached for ED with a demineralization level of 25% without any changes in the other measured components of osmosed maple saps. The demineralization process had no effect on the yield of syrups produced and on their characteristics: no significant difference was observed during sensory analysis and viscosity. Moreover, the percentage of light transmission of syrups produced from demineralized osmosed saps was higher than for the control. This work suggests that ED could be a potential technology to decrease or avoid sugar sand formation during maple syrup production. Copyright © 2007 Society of Chemical Industry