Michelle R Toutounji

Matthew P Van Leeuwen

James D Oliver

Ashok K Shrestha

Patrice Castignolles
email: p.castignolles@uws.edu.au

Marianne Gaborieau

Quantification of sugars in breakfast cereals using capillary electrophoresis

Keywords: Breakfast cereals, Sugars, Sucrose, Glucose, Capillary electrophoresis (CE), Fehling method, 3,5-dinitrosalicylic acid (DNS) assay, High performance liquid chromatography (HPLC)

About 80 % of the Australian population consumes breakfast cereal (BC) at least five days a week. With high prevalence rates of obesity and other diet-related diseases, improved methods for monitoring sugar levels in breakfast cereals would be useful in nutrition research. The heterogeneity of the complex matrix of BCs can make carbohydrate analysis challenging or necessitate tedious sample preparation leading to potential sugar loss or starch degradation into sugars. A recently established, simple and robust free solution capillary electrophoresis (CE) method was used in a new application to 13 BCs (in Australia) and compared with several established methods for quantification of carbohydrates. Carbohydrates identified in BCs by CE included sucrose, maltose, glucose and fructose. The CE method is simple requiring no sample preparation or derivatization and carbohydrates are detected by direct UV detection. CE was shown to be a more robust and accurate method for measuring carbohydrates than Fehling method, DNS (3,5-dinitrosalicylic acid) assay and HPLC (high performance liquid chromatography).

Introduction

About 80 % of the Australian adult population consume breakfast cereal, either cooked or ready-toeat, at least five days a week. 1 Breakfast cereals, like most food products, contain a variety of carbohydrates as well as lipids, proteins and minerals. The heterogeneity of this complex matrix can make sugar analysis in breakfast cereals challenging. 2,3 For sugars, total content is all that is required for the nutrition information panel (NIP), a mandatory labelling requirement of all processed foods in Australia. 3 Methods for the measurement of sugar in foodstuffs were often developed before carbohydrate chemistry was established. 4 Earlier quantitative chemical analytical assays often relied upon the reducing properties of aldehyde or keto group found in monosaccharides and short-chain oligosaccharides. In alkaline solutions, at elevated temperatures, these reducing sugars tautomerize to enediol forms which are then readily oxidized by oxygen and oxidizing agents (such as metallic salts). An estimate of glucose content was based on the colorimetric measurement of the oxide or the free metal formed. The empirical nature of this reaction allowed analysts to develop methods such as the Fehling method and the 3,5-dinitrosalicylic (DNS) assay which can produce reproducible and accurate results for samples with simple matrices. Such methods are also inexpensive, technically easy to perform and highly applicable to routine quantification. However, a strict control of experimental conditions (rate of heating, alkalinity and strength of the reagent) in a non-automated setting is necessary to obtain repeatable and reproducible results. 5 Due their specificity and ease of operation, enzymatic assays are the preferred reducing sugar method over Fehling method and DNS assay. Glucose and sucrose content has been determined in 79 dry, North American BCs using the glucose-oxidase peroxidase (GOD-POD) method. 6,[START_REF] Shannon | Brand name guide to sugar : sucrose content of over 1,000 common foods and beverages[END_REF] The sugar content of these samples was previously assayed by the colorimetric condensation reaction with anthrone, which gave unsatisfactory reproducibility.

Most foods, including BCs, contain a mixture of sugars rather than a single type of sugar. Therefore, the methods previously discussed are innately flawed by being either glucose-specific (e.g. GOD-POD) or unable to distinguish between different reducing sugars as is the case for the Fehling method and the DNS assay. [START_REF] Fitzgerald | [END_REF] In reducing-sugar assays the quantity of product formed and measured is not exactly equivalent to sugar content, and different sugars yield different color intensities; this shows that the chemistry involved in the assay is considerably more complicated than it appears. 9 For certain foods in which the composition of the sugars is known and the requirement of the analysis is routine, e.g. quality control, an estimate of total sugar values expressed as invert sugar or glucose may be sufficient. However, most BCs have sucrose added during manufacture and thus total sugar determination requires a preliminary hydrolysis of non-starch polysaccharides (by acid or enzyme) which may cause sample loss or overestimation of reducing sugars. In addition, mineral ions have been reported to interfere with some reducing-sugar assays, 10,11 a problem for most Australian BCs which have been fortified.

In the area of nutrition research, the intrinsic accuracy of the quantities of the different carbohydrates present in a diet is often required for correlation with their metabolic behavior. 4 Separation is used for this purpose. Separation methods have allowed for greater accuracy of sugar analysis in foods. Individual sugars measurements can be summed to calculate the 'total sugar content' for the NIP. Gas chromatography (GC) is a popular method for carbohydrate analysis and is very sensitive. It is the only chromatography method published in the peer-reviewed literature so far for sugar quantification of BCs. [12][13][14][15] The sample preparation requires multiple steps: grinding to pass through a 30-mesh (0.59 mm) screen, drying under vacuum, defatting with n-hexane, extraction with water for some of the sample and with aqueous methanol for the rest, centrifugation. In order to make the carbohydrate volatile a multistep derivatization was then needed: concentration under nitrogen flow and then drying under vacuum, reaction with pyridine, hexamethylsilazane in presence of trifluoroacetic acid, followed by another centrifugation. The sample preparation for GC is thus time consuming, laborious and has a significant probability of sample loss. 3 High performance liquid chromatography (HPLC) is the other established analytical method for measuring individual sugars in many foods. A number of columns have been tested for normal phase HPLC of carbohydrates, for example ion-exchange columns for BCs, 16,17 but they all have their own disadvantages including coelution, tedious sample preparation and intolerance to salt or acid leading to short column life. 18,19 For starchy-food sample matrices, such interfering substances not only disrupt the analysis, they can damage the column leading to a high running cost. High performance anion exchange chromatography (HPAEC) is solving a number of these issues and is rapidly developing for food analysis 3 because of its high sensitivity without any required derivatization and its speed in carbohydrates separation. 20,21 Released sugars from non-starch polysaccharides in a range of raw and processed foods (including BCs) were determined by HPAEC. 13 Capillary electrophoresis (CE) is becoming increasingly popular for carbohydrate analysis. [START_REF] Klampfl | Analysis of Simple Carbohydrates by Capillary Electrophoresis and Capillary Electrophoresis-Mass Spectrometry[END_REF] The most useful and simple separation mechanism of CE is free solution (devoid of a gel or polymer network medium). Free solution CE (FSCE), also known as capillary zone electrophoresis (CZE), involves the flushing of an electrophoresis buffer through a narrow-bore capillary prior to sample injection, application of voltage and separation. [START_REF] Camilleri | Capillary electrophoresis : theory and practice[END_REF] Like HPLC, FSCE is a fast and repeatable analytical tool for the qualitative and quantitative analysis of carbohydrates in food and beverage samples, [START_REF] Jager | [END_REF][25][26][27] including in foodomics 28 . FSCE sensitivity can be greatly increased using on-line pre-concentration methods. 29 One FSCE method has been applied to a BC sample (flaked cereals) by coating the capillary with cetrimonium bromide (CTAB). [START_REF] Jager | [END_REF] This dynamic coating is non-selective for sugars whereby interaction with lipids and other components can become a problem for quantification in complex matrices. Until recently, indirect UV detection of underivatized carbohydrates was considered superior to direct UV detection; detection at low wavelengths after borate complexation generated poor sensitivity. However, direct UV detection at 270 nm in high alkaline conditions has been discovered for the FSCE of sucrose, glucose and fructose in beverage samples 30 and the detection has been shown to be specific to carbohydrates 31,32 The method is considered robust by definition: "a method that can be applied to analytes in a wide variety of matrices" 33 and despite the complex matrix, no filtration is necessary during sample preparation 34 . FSCE with direct UV detection has been applied to acid hydrolyzed plant fiber, fermentation, beverage, pharmaceutical and forensic samples. 18,19,[35][36][37] The CE method was shown to be cost effective, robust and repeatable.

The aim of this research was to analyze 13 Australian breakfast cereals using FSCE with direct UV detection 18 and to compare quantitative results with that from traditional chemical analytical methods: Fehling method and DNS assay. Available data from the Food Standards Australia New Zealand (FSANZ) NUTTAB database [START_REF]Explanatory Notes for use with NUTTAB[END_REF] of individual sugar quantities for relevant Australian breakfast cereals was also included for a comparison to our findings.

Results and discussion

Detection of individual sugars in breakfast cereals using capillary electrophoresis (CE)

The ground breakfast cereals (BC) were simply suspended in water and injected in CE. The sugars in breakfast cereals were separated (Figure 1) by CE. Identification of sugars was validated by comparison of the electrophoretic mobility of observed peaks with that of a standard sugar solution and previous literature (Table 1). A double correction was used to precisely determine the electrophoretic mobility of each sugar peak. The first correction was using a neutral species (DMSO) as an EOF marker (see Equation S-2). The second correction involved a homothetic transformation with an electrophoretic mobility marker (Equation S-3). 30 Table 1 demonstrates how the mobility value of a sugar, much like elution time in HPLC, is useful in peak identification. Sucrose was detected in all BCs, while lactose, maltose, glucose and fructose were detected in some. Other components are not detected even though the matrix is complex: proteins, lipids are also present but the direct UV detection has been shown to be specific to carbohydrates since it is due to a photo-oxidation reaction taking place at the detection window 32 . To identify the carbohydrates, electrophoretic mobility is used, and not migration time, since the former has a higher repeatability than the latter (Table 1). Preliminary sugar identification was confirmed by spiking BC samples (December 2012, see Figure S-2 and S-3). The samples, 'Corn Flakes', 'Froot Loops' and 'Weet-Bix Multigrain' were selected as they contained the greatest number of peaks among the seven BCs used in the first set of experiments (October 2012).

Repeatability within the standards was sufficient with relative standard deviation (RSD) values of no more than 1.3 %, providing a reliable set of values on which to base sugar identification. In the analysis of BC samples, higher RSD values were observed in MRT1 'Nutri-Grain' and MVL 'Weet-Bix', yielding measurement errors of 5.6 % and 2.4 % respectively (see also Figure S-1). Apart from these isolated cases, the repeatability of BC sample analysis was good with RSD ≤1.5 %.

Reproducibility of the electrophoretic mobility values has been investigated by comparing the results

obtained by two different operators, MVL and MRT, or by the same operator with different sample preparation (differing only in dilution), MRT1 and MRT2, or in the literature. Comparison of analyzed samples shows a reasonable level of reproducibility between values reported in reference 30 , and those obtained by operator MVL and MRT1, showing a maximum variance between mobilities of approx. 5% (sucrose), with MRT reporting consistently higher mobilities. Identical operator with diluted sample (MRT2) showed reduced repeatability, yielding mobility value variance of 5-10 % compared to MRT1, while comparison with MVL showed variance of 1-5 %, with two values yielding a 10 % variance (glucose and fructose in 'Weet-Bix'). Results for diluted 'Coco-Pops' lacked the identification of both glucose and fructose, present in previous experiments, indicating dilution to reduce impacts of overloading is negatively affecting the sensitivity for low concentration sugar identification. Results reported by Oliver et al. 18 present significantly higher electrophoretic mobilities for both glucose and xylose. This illustrates the importance of a standard solution to establish the mobility values of sugars in each session to account for variations between operators, equipment and sessions.

The results obtained in this work by both operators MVL and MRT showed a sufficient level of reproducibility between operators to yield identical sugar identifications in all cases. Same operator, with dilution showed a reduced reproducibility, yielding slightly higher variance in mobility, though still indicates a sufficient level for the identification of sugars. CE is thus a viable method for the identification of sugars in breakfast cereals. # mobility correction using methanol as an EOF marker $ mobility double correction using DMSO as an EOF marker and lactose as an electrophoretic mobility marker ^ mobility double correction using DMSO as an EOF marker and sucrose as an electrophoretic mobility marker + mobility double correction using DMSO as an EOF marker and xylose as an electrophoretic mobility marker Table 2. Calibration of response at 266 nm (y) as a function of sugar concentration (x) with its correlation coefficient (R 2 ), for the sugars in standard (capillary of 61.8 cm total length). Xylose (0.5 g⋅L -1 ) was used as the internal standard.

Sugar

Quantification of individual sugars in breakfast cereals using capillary electrophoresis (CE)

The calibration curve for each sugar was prepared with the sequential analyses of six sugar mixtures injected in triplicate. The linearity and repeatability were determined for 5 sugars, with xylose (0.5 g⋅L -1 ) used as the internal standard. Sufficient linearity was achieved for all tested sugars with correlation coefficient (R 2 ) greater than 0.99 (Table 2) and reasonable standard error on the y estimates (see Figure S-4 to S-6 in supplementary data), as achieved in the literature applying this CE method to different matrices. 18,[START_REF] Oliver | [END_REF] The calibration for disaccharides, maltose, lactose and sucrose, had slightly better linearity than that for monosaccharides glucose and fructose. The sugar concentrations determined by CE also show good repeatability (see error bars on Figure 2) of the peak area ( normalized with respect to the peak area of the internal standard, each peak area being also divided with the corresponding migration time) consistent with the literature (see Table S-3). 18,30 The use of an electro-osmotic flow marker and the addition of an internal standard are recommended for optimal repeatability of the peak area. The high pH of the NP200 buffer made it prone to carbonation 40 and it is thus recommended to use buffer within 13 h (or 19 h) of its preparation to be within 10 % (or 15 %) of initial current measurement (Equation S-5 to S-8, Table S-4 and Figure S-7 in supplementary data). Table 2 lists the relative sensitivity of the detection of different sugars along through the limit of detection (LOD) and limit of quantification (LOQ). LOD and LOQ were calculated from the signal-to-noise ratio (SNR) obtained with 32 Karat software. The sensitivity of the direct detection in this study, with LOD values between 2.4 and 30 mg•L -1 , was comparable to studies that had used the same CE method on different types of analytes, 31,41 (see Table S-1). The method was applied to the quantification of sugars in several commercial breakfast cereals. Since fewer than six sugars have been identified in BCs previously, a short capillary, total length 61.8 cm, was employed for all experiments to decrease analysis time to 40 min (including xylose internal standard). Figure 2 presents the sugar concentration results for ten BCs determined by CE. Each BC contained sucrose at a higher concentration than any other sugar detected (lactose, maltose, glucose and fructose). This is likely due to the amount of sugar added during manufacture of the product. BCs with high sucrose concentrations (measured above 15 g / 100 g), including 'Oats Apple & Blueberry Bake', Nutrigrain', 'Coco Pops', listed sugar as the second highest ingredient after the cereal component on their packaging.

Nutritionally insignificant concentrations of maltose, glucose and fructose were detected in 9 of the 11 BCs analyzed by CE. Barley malt extract is listed as an ingredient on BCs 'Sustain', 'Corn Flakes' and 'Sultana Bran' thus the low concentration values (1.8, 0.9 and 0.6 g / 100 g respectively) for maltose could be expected. Similarly, trace levels of lactose detected in 'Oats Apple & Blueberry Bake' (0.5 g / 100 g) and 'Oats Banana Bake' (0.3 g / 100 g) are in agreement with the addition of the milk powder ingredient in these BCs.

Problems were reported with the sugar quantification in GC of North American BCs with sampling and/or measuring aliquots of individual cereals. 12 The correlation of variation of most samples, however, was not greater than the standards. They state that RSD was not greater than 2 % for glucose and sucrose and not greater than 5 % for lactose and maltose. The average RSD from CE reported in this work is approximately 7 % for lactose, glucose and fructose and about 13 % for sucrose and maltose concentrations. The average overall error of CE at ± 9 % is comparable to that of the reported GC method at ± 7 % .

Comparison of CE and HPLC for determination of individual sugars

The quantity of individual sugars in Australian BCs as measured by HPLC is available on the Food Standards Australia New Zealand (FSANZ) NUTTAB 2010 database. [START_REF]Explanatory Notes for use with NUTTAB[END_REF] This data was compared with CE results from this work (see Figure 345). Among the eight BCs included in this comparison, both methods determined 'Oats Traditional', 'Weet-Bix' and 'Corn Flakes' to have the lowest sucrose concentrations. For these cereals, the HPLC method did not detect any sugar in Oats Traditional whereas CE measured 0.2 % sucrose. CE also detected approximately 36 % more sucrose in' Weet-Bix' and 48 % more in 'Corn Flakes' compared to HPLC (see Figure 3A). The sucrose content of 'Rice Bubbles' as measured by CE was not significantly different from that from HPLC data. For the two BCs with the highest sucrose concentration ('Nutri-Grain' and 'Coco Pops'), less sucrose was measured by CE compared to HPLC. [START_REF]Explanatory Notes for use with NUTTAB[END_REF] Some of these variations may be due to changes in the recipes or even batch to batch variations. The HPLC data from individual quantification of sugars in BCs are available online to the public. However, the exact methodology is unpublished and unreported. It is very likely that some filtration and / or centrifugation is required to prepare samples for carbohydrate analysis by HPLC. Thus sample loss could have occurred during sample preparation and may have caused an underestimation of sugar content for 'Weet-Bix' and 'Corn Flakes'. CE analysis also yielded a significantly higher sucrose concentration of 12.5 g / 100 g for 'Sustain' compared to HPLC data 38 at 0.2 g / 100 g (see Figure 3A). In addition, CE data for glucose and fructose concentrations in 'Sustain' were significantly lower (0.9 and 1.1 g / 100 g) compared to HPLC data (7.4 and 8.7 g / 100 g), see Figure 3B. This may be due to differing sample preparation, in a sample which is even more heterogeneous than the other BCs due to the presence of pieces of fruit. During initial sample preparation of BCs for all experimental methods in this study, the fruit pieces and some other large particulate ingredients were resisting grinding and did not pass through laboratory sieves. Thus BCs with added pieces of fruit measured in this study, such as 'Sustain' and 'Sultana Bran', are acknowledged as not being representative of the whole sample. The free form of glucose and fructose is found naturally in plants, including many fruits and vegetables. Typical sugar composition of Australian sultanas, for example, is 38 % fructose and 35 % glucose by dry weight [START_REF] Bennion | The Technology of Cake Making[END_REF] . The majority of sultanas and other pieces of fruit were selectively removed from the BC samples in this study. This likely caused an underestimation of glucose and fructose concentration, as seen in 'Sustain' and 'Sultana Bran' (Figure 3B). More extensive sample preparation of BCs that contained fruit led however to up to 55 % error on the measured sugars in the case of GC. 12 The extraction procedures of the BCs including fruits for GC requires aqueous methanol. However, this still led to larger error, especially for maltose quantification. 12 As the total sugar measured by CE and HPLC for 'Sustain' is similar, 16.3 and 18.2 g / 100 g respectively (see Figure 5), the significantly lower sucrose levels by HPLC (see Figure 3A) may be attributed again to sample loss during preparation for HPLC or to a change in the BC composition due to different time of purchase. Lower level of individual sugars quantified by HPLC compared to CE with direct UV detection has been observed for other samples with complex matrices, namely plant fiber 18 and ethanol fermentation 19 .

Estimation of total sugar by CE and Fehling (Lane-Eynon) method

Total sugar content is a legal measurement requirement for food labelling in Australia and many other countries. Total sugar content of 11 BCs was determined by the traditional Fehling (Lane-Eynon) method and the high performance CE separation method, and compared with the NIP on the BC packaging label as well as with available HPLC data. [START_REF]Explanatory Notes for use with NUTTAB[END_REF] Comparison of methods is important to determine the accuracy of sugar content in BCs, both to ensure label information is correct and to highlight differences between method in cost and efficiency.

The 11 BCs presented in Figure 4 can be grouped into three categories for total sugar content: (high (>12.5 g / 100 g), medium (5 -12.5 g / 100 g) and low (<5 g / 100 g) sugar content. The high sugar content cereals as measured by CE, in increasing order, were 'Sultana Bran', 'Sustain', 'Nutri-Grain', 'Coco Pops' and 'Oats Apple and Blueberry Bake'. 'Sultana Bran' and 'Sustain' had lower levels of total sugar measured by CE and Fehling method in this work compared to the packaging and available HPLC data [START_REF]Explanatory Notes for use with NUTTAB[END_REF] likely due to removal of fruit during sample preparation (as mentioned in section, 2.3). 'Nutrigrain' was consistently ranked amongst the top three BCs for high sugar content among all methods compared. The total sugar content for 'Coco Pops' measured by CE had a relatively high RSD of 20 % and was therefore not significantly different from that measured with other methods in the comparison. 'Oats Apple and Blueberry Bake' was determined to have the highest total sugar content of all BCs by CE, 15% more than labelled on the NIP.

The medium sugar content BCs as determined by CE, in increasing order, were 'Rice Bubbles' , 'Corn Flakes', 'Oats Banana Bake' and 'All Bran Fibre Toppers'. All methods, except Fehling which gave a large degree of variability between replicates, determined 'Rice Bubbles' to have between 6 and 9 g/ 100 g total sugar. The CE results for 'Corn Flakes' were in agreement with the NIP which was more than double the amount reported by HPLC; no conclusions could be drawn from Fehling data of this BC due to the large degree of error. Sugar content of 'Oats Banana Bake' and 'All Bran Fibre Toppers' measured by CE was approximately half of that reported on label or measured by Fehling.

The low sugar content BCs determined by CE were 'Oats Traditional' and 'Weet-Bix'. 'Oats Traditonal' had the lowest sugar content measured by CE at 0.2 g/ 100 g. Interestingly, the NIP labelled this BC to have 1 g/ 100 g total sugar, however HPLC data [START_REF]Explanatory Notes for use with NUTTAB[END_REF] reported no sugar at all. Also, sugar contained in 'Oats Traditional' was below the limit of detection for the Fehling method. The total sugar content of 'Weet-Bix' was consistent between the NIP, the HPLC data and the CE method in this study. At this low level of sugar, the Fehling method had very poor repeatability (RSD = 89 %) as one of the repeats was below LOD. [START_REF]Explanatory Notes for use with NUTTAB[END_REF] The overall error for the quantification of sugars in BCs by the CE method was much lower than that of the Fehling method, especially for the BCs with low sugar content. The error for the Fehling method is mainly caused by human technique (such as over-titration), whereas CE is automated and is more affected by operation error. In the case of the low sugar content BCs, the Fehling method was not sensitive enough to produce precise and accurate results. The most criticized aspect of CE in terms of operation error is related to volume variation between injections. Injections in CE are achieved by inserting a capillary into a sample solution vial and using pressure to draw sample solution into the capillary (hydrodynamic injection). Pressure variations lead to differences in injection volume and thus to relatively poor peak area precision. As previously mentioned, an internal standard was used in this work (to correct the peak area) and this eliminated this type of error and greatly improved precision as it had been observed with the CE method applied to plan fibers 18 or fermentation monitoring 19 . There was no available data on the precision of the NIP and HPLC measurements. However, CE was more comparable to HPLC than NIP or the Fehling method.

Figure 4.

Total sugar content of 7 BCs by CE, Fehling method, available HPLC data [START_REF]Explanatory Notes for use with NUTTAB[END_REF] and packaging label information (NIP). No HPLC data was available for 'All Bran Fibre Toppers' and 'Oats Apple and Blueberry Bake'.

Estimation of reducing sugar by CE and DNS assay compared with HPLC

A reducing sugar is classified as any sugar that contains or is capable of forming an aldehyde functional group that can be oxidized to a carboxylic acid functional group. Though the largest proportion of sugar contained in BCs is sucrose, rather than reducing sugars (lactose, maltose, glucose and fructose), the quantification of these sugars is important -especially glucose (key product of digestion). The same ground samples (with fruit removed) were used to measure reducing sugars with both CE and DNS methods (Figure 5), which may explain the significantly lower content in reducing sugars in 'Sultana Bran' and 'Sustain' measured by CE and DNS compared to HPLC data. As previously discussed, individual CE results confirmed the reducing sugars quantified by HPLC [START_REF]Explanatory Notes for use with NUTTAB[END_REF] were fructose and glucose (see Figure 3B). The use of the DNS assay for the estimation of reducing sugars is a widely practiced assay and also recommended by the International Union of Pure and Applied Chemistry (IUPAC) [START_REF] Ghose | [END_REF] . There was no significant difference between the sugar concentrations from CE and DNS assay. The sugar concentrations were found to agree with that from CE and HPLC in some cases, but not for the most complex matrices (plant fiber) 41 . Overall, the repeatability of the CE results was better than that of the DNS data in this work. During the DNS assay, relatively harsh reaction conditions (pH 13.0, 100 °C, 5 -10 min) is likely to cause starch degradation. In addition, other side reactions (especially involving minerals) may compete for the availability of the DNS reagent 10,11 . The simple suspension in water used for sample preparation in CE ensure no or much more limited degradation for the use of CE on starch food.

Conclusion

FSCE with direct UV detection was shown to be advantageous for measuring sugar content in breakfast cereals compared to traditional reducing sugar and glucose-specific methods for several reasons: (1) BCs can contain as many as 5 sugars; CE is able to separate and quantify all sugars in a sample compared to traditional methods which give an estimate of total sugar after inversion of sucrose (a great disadvantage when sample composition is unknown), (2) BCs with the lowest measured sugar levels, 'Oats Traditional' and 'Weet-Bix Original', had sugar contents below the LOD of the Fehling method, (3) the precision of data collected by CE is greater than that from traditional methods likely due to automation of the CE. While GC has been used to measure individual sugars in BCs, multi-step sample preparation involving derivatization 12 or enzymatic removal of starch and acid hydrolysis of the non-starch polysaccharides 13,14 is time consuming and presents a high risk of sample loss. At present, high performance liquid chromatography (HPLC) is the gold standard for measuring individual sugars in food. This study showed that, for all BCs (excluding those containing fruit), CE was able to detect and quantify more sugars compared to data measured with HPLC [START_REF]Explanatory Notes for use with NUTTAB[END_REF] . CE is also more flexible, has a much lower running cost and requires much less sample preparation than HPLC. High performance anion exchange chromatography (HPAEC) has some of the inherent disadvantages associated with normal phase HPLC, but has a greater sensitivity range than CE. In summary, FSCE is, with HPAEC, the method to recommend for the analysis of carbohydrates in breakfast cereals. Future applications of this simple and robust CE method in foodstuffs could be enzymatic hydrolysis monitoring (in vitro digestibility studies) as previously done by NMR 44 4. Materials and methods

Materials

Milli Q quality (Millipore, Bedford, MA, USA) water was used throughout the analysis. Sodium hydroxide pellets (NaOH), disodium monohydrogen phosphate powder (Na2HPO4 stored in a desiccator), 100 % pure glacial acetic acid, calcium chloride dihydrate ≥98 %, magnesium chloride ≥99 %, sodium acetate ≥99 %, potassium chloride ≥99 %, sodium hydrogen carbonate and sulfuric acid were obtained from Univar (Ingleburn, NSW, Australia); hydrochloric acid and methylene blue (C.I. 52015) were sourced from Ajax Chemicals (Auburn, NSW, Australia). Copper (II) sulfate was purchased from Fisons (Homebush, NSW, Australia). Citric acid (anhydrous) was obtained from Chem-Supply Pty Ltd (Gillman, SA, Australia). Zinc acetate ≥99 % was supplied by BDH AnalaR, Merck Pty Limited (Poole, Dorset, England). Sodium potassium tartrate 99 %, sodium bisulfite, phenol, 3,5dinitrosalicyclic acid, Glucose ≥99.5 % and dimethyl sulfoxide (DMSO) ≥99.5% were supplied by Sigma-Aldrich (Castle Hill, NSW, Australia). Xylose ≥99 % was from Alfa Aesar (Ward Hill, MA, USA). Fused-silica capillaries (50 µm internal diameter, 360 µm outside diameter) were obtained from Polymicro (Phoenix, AZ, USA). Infinity™ glucose oxidase liquid stable reagent, pH 7.5 ± 0.1 at 20 °C, was obtained from Thermo Scientific (TR-15221, Worthing, West Sussex, UK).

Initial sample preparation

Thirteen breakfast cereals (BC) products were purchased from a local Woolworths supermarket (Marayong, NSW, Australia). Approximately 80-150 g of each BC was milled in a K-mart, m-mini glass jug blender for 20 sec, speed level 1. The ground cereal was passed through a laboratory sieve with pore size 1000 µm and retained in a 500 µm sized sieve, producing BC samples with particle size between 500 to 1000 µm. Samples were stored in a cold room at 4 °C. Basic information of the 13 BC samples, including sugar content, is shown in Table 3. Oats banana bake (Uncle Tobys®) 22.7

Capillary electrophoresis

For CE separations, disodium hydrogen phosphate (NP200 -130 mM NaOH and 36 mM Na2HPO4) buffer was prepared according to 30 . This buffer was prepared on the day of use, sonicated for 5 min and filtered with a Millipore membrane syringe filter (0.2 µm). A stock solution of sugars (standard) was prepared containing 1.5 g⋅L -1 sucrose and 0.5 g⋅L -1 of each maltose, glucose and fructose in water. Standard curves were obtained using an undiluted standard and standards diluted by factors of 2, 4, 8, 16, and 32. Sample solutions of 10.0 g⋅L -1 were prepared by adding 15.0 mg of ground sample (500-1000 μm particle size) to 1.500 mL of water. To each of the standards and samples, 0.50 g⋅L -1 xylose was added as an internal standard as well as DMSO (5 μL per 500 μL) to mark the electroosmotic flow.

Separations were performed on a Beckman P/ACE MDQ capillary electrophoresis system (AB Sciex Separations, Mount Waverley, Australia) monitoring at 191 nm, 266 nm and 270 nm with a 10 nm bandwidth. A capillary with a total length of 61.8 cm (51.8 cm effective length) was used. The capillary was preconditioned before use by flushing with 1 M NaOH, 0.1 M NaOH, water and NP200 buffer for 20 min each. The cassette temperature was set to 15 ˚C. Samples were injected by applying 34 mbar for 4 s followed by injection of NP200 buffer in the same manner. A voltage of 16 kV was ramped up over 2 min. Between consecutive separations, the capillary was flushed with NP200 buffer for 5 min. After the final injection, the capillary was flushed with 1 M NaOH for 1 min, followed by water and then air (10 min each). Carbohydrates were monitored at 266 and 270 nm and the EOF was monitored at 191 nm by 32 Karat software. The data was processed first using either Origin 8.5.1 ('manual' treatment) or 32 Karat ('automated' treatment). Quantification of the carbohydrates was not done at 270 nm as in earlier literature but at 266 nm since it gave the optimal signal-to-noise ratio as also observed in the most recent literature. 19,32,[START_REF] Oliver | [END_REF] Both data treatment yielding the same results (data not shown) the latter treatment was used for all the results presented in this work. Concentration of identifiable sugars in BCs was determined from normalized peak area (relative to the internal standard) and the standard curve. Outliers were removed, where relevant, after applying a Grubb test (see Equation S-4).

DNS assay in micro plate format

Reducing sugars in BCs were quantified by the DNS assay in microplate format. The DNS reagent was prepared exactly according to 9 . Sample solutions of 10.0 g⋅L -1 were prepared by adding 15 mg of ground sample (500-1000 μm particle size) to 1.5 mL of water. Triplicates of 100 μL were made up as both undiluted samples and diluted samples (with dilution factors of 1, 2, 4, 8, 16, 32). Glucose standard solutions of 0.2, 0.4, 0.6, 0.8, 1.0 g⋅L -1 were prepared in triplicates for the purpose of procuring a standard curve. A blank and a set of standards were included with the samples tested on each microtitre plate. The contents of the plates were then mixed on a plate mixer for 5 s, sealed and incubated at 100 ˚C in a water bath for 10 min. The plates were then cooled to room temperature to stop the reaction by being placed on ice. Absorbance values were measured at 640 nm on a microplate reader with the standard containing no glucose as the blank.

Fehling (Lane-Eynon) method

Estimation of total sugar content in BCs was carried out using Fehling's solution reagents as described in [START_REF] Ranganna | Handbook of Analysis and Quality Control for Fruit and Vegetable products[END_REF] . Fehling solution A contained 69.3 g of copper sulfate in 1 L of water, Fehling solution B contained 346 g of Rochelle salt (potassium sodium tartrate) in 1 L of water. Carrez solution 1 contained 21.9 g of zinc acetate and 3 mL of glacial acetic acid in 100 mL of water, Carrez solution 2 contained 10.6 g of potassium ferrocyanide in 100 mL of water. Each ground BC sample (5 g) was added to 100 mL water, mixed with 5 mL each of Carrez solutions 1 and 2 and made up to a total volume of 250 mL with water. The mixture was then decanted and filtered through Whatman® 540 filter paper. The clarified solution (25 mL of it) was transferred to a conical flask, mixed with 2.5 g citric acid and gently boiled on a hot plate for 5 min to ensure the inversion of any sucrose present. The sample solution was then neutralized to pH 6.5 -7.5 with 1 M NaOH and made up to a total volume of 250 mL with water. This gave an approximate sample concentration in sample preparation of 2 g⋅L -1 . Fehling's solution was titrated against the sample solution as reported previously for the standard glucose solution. The total sugars content was calculated following Equation S-1 (see supplementary data).

Standardization of Fehling's solutions was carried out using a 10 g•L -1 glucose solution. Fehling's solutions (2.5 mL each of A and B) were mixed with 30-50 mL water in a ceramic crucible and heated to 100 ˚C over a Bunsen burner for 15 s. Three drops of methylene blue indicator were added followed by dropwise addition of the standard glucose solution until only a faint blue color remained.

Figure 1 .

 1 Figure 1. Migration time electropherogram (A) and mobility electropherogram (B) of 'Weet-Bix Multigrain'. From the left to the right, peaks correspond to sucrose, (unknown), maltose, glucose and fructose.

Figure 2 .

 2 Figure 2. Individual sugar quantification of 11 BCs by CE (n=3 or 5 for all BCs).

Figure 3 .

 3 Figure 3. Quantification of sucrose (A) and glucose and fructose (B) in BCs by CE (this work) compared to available HPLC data[START_REF]Explanatory Notes for use with NUTTAB[END_REF]

Figure 5 .

 5 Figure 5. Reducing sugar content of 7 BCs by CE, DNS assay and available HPLC data 38 .

Table 1 .

 1 Reproducibility of the separation of sugars in five breakfast cereal samples with CE. Operator MVL (n=2) and Operator MRT (n=3).

			Average µep (10 -8 m 2 V 1 s -1 )
	Breakfast Cereal	Operator or publication	(RSD in %) Sucrose Lactose Maltose Glucose Fructose Xylose
		Ref. 30 #	-0.772 (u*)	-	-	-1.176 (u*)	-	-1.365 (u*)
	Standard sugar	Ref. 18 $	-	-	-	-1.518 (0.45)	-	-1.754 (0.40)
	solution	MVL ^	-0.720 (1.08)	-	-1.116 (0.49)	-1.181 (0.30)	-1.265 (0.30)	-1.395 (1.07)
		MRT +	-0.801 (1.29)	-1.003 (0.77)	-1.172 (0.40)	-1.224 (0.74)	-1.285 (0.40)	-1.419 (u*)
		MVL	-0.720 (u*)	-	-	-1.152 (0.77)	1.237 (0.83)	-
	'Coco Pops'	MRT (series 1)	-0.810 (0.109)	-	-	-1.223 (0.006)	-1.289 (0.029)	-1.419 (u*)
		MRT (series 2)	-0.733 (0.470	-	-	-	-	-1.329 (u)
		MVL	-0.720 (u*)	-	-	-1.188 (0.77)	-1.283 (0.79)	-
	'Nutri-Grain'	MRT(series 1)	-0.788 (5.59)	-	-	-1.212 (1.18)	-1.276 (0.792)	-1.419 (u*)
		MRT (series 2)	-0.730 (0.49)	-	-	-1.118 (0.93)	-1.201 (0.19)	-1.333 (u)
	'Sustain'	MVL MRT (series 1)	-0.720 (u) -0.805 (0.070)	--	-1.124 (1.06) -1.172 (0.051)	-1.195 (1.15) -1.224 (0.038)	-1.288 (1.46) -1.285 (0.047)	--1.419 (u*)
		MVL	-0.720 (u*)	-	-	-1.240 (2.20)	1.348 (2.39)
	'Weet-Bix'	MRT (series 1)	-0.798 (0.119)	-	-	-1.221 (0.062)	-1.285 (0.026)	-1.419 (u*)
		MRT (series 2)	-6.834 (1.48)	-	-	-1.090 (0.21)	-1.161 (0.11)	1.272 (u)
	'Oats: Apple and Blueberry Bake'	MRT (series 1)	-0.808 (1.061)	-1.025 (1.230)	-	-	-	-1.419 (u*)
	* u stands for unavailable

Table 3 .

 3 Breakfast cereal samples according to total sugar content as listed on Nutrition Information Panel (NIP, or packaging label information). Sugar quantity is listed in g per 100 g of BC

	Sample Name (Brand Name)	Sugar
		(g / 100 g)
	All Bran Fibre Toppers™ (Kellogg's®)	19.6
	Coco Pops® (Kellogg's®)	36.5
	Corn Flakes® (Kellogg's®)	7.9
	Froot Loops® (Kellogg's®)	38.0
	Nutri-Grain® (Kellogg's®)	32.0
	Rice Bubbles® (Kellogg's®)	9.0
	Sultana Bran (Kellogg's®)	22.7
	Sustain® (Kellogg's®)	20.4
	Weet-Bix™ (Sanitarium™)	3.3

Acknowledgements

The authors acknowledge a UWS School of Science and Health Equipment Grant for the CE instrument.

Supplementary data

The supplementary data includes the details of the calculation of total sugars in Fehling method, CE electropherograms with spiked BC samples, repeatability of CE electropherograms and tables with the RSDs of the electrophoretic mobility, the comparison of LODs and LOQs with published values and the statistics applied to detect outliers.

SUPPLEMENTARY DATA

For

Quantification of sugars in breakfast cereals using capillary electrophoresis

Michelle R. Toutounji a,b,c , Matthew P. Van Leeuwen a,c , James D. Oliver a , Ashok K. Shrestha b , Patrice Castignolles* ,a , and Marianne Gaborieau Supplementary information relating to the Fehling method and then Capillary Electrophoresis is given below.

Calculation of total sugars in Fehling method.

The total sugar content was determined as total invert sugars (IS tot , in g per 100 g of BC) as a function of the mass of invert sugars in the standard (IS stan , in g), the dilution factor D f , the measured titre T (in mL), and the mass of the BC sample (m BC , in g) according to Equation S-1. The initial volume of the sugar solution is 100 mL.

2. Capillary electrophoresis.

Sample preparation and ageing

Suspensions of breakfast cereals in water were injected as 1 to 2 days old samples throughout this work. It was observed that samples aged for several months contain additional peaks (data not shown) which are assumed to be degradation products.

Electrophoretic mobility

Electrophoretic mobility (μ) is calculated relative to the migration of a neutral molecule representing the electro-osmotic flow, calculated by equation S-2.

where l d is the capillary length to the detection window (effective length), l t is the total capillary length, V is voltage, t m is migration time, t eof is migration time of the electroosmostic flow (EOF) marker.

Double correction of electrophoretic mobility:

Electrophoretic mobility is then normalized using a mobility marker as shown in equation S-3.

where µ is the electrophoretic mobility (calculated with Equation S-2) which has already been corrected according to the EOF marker, µ normalized refers to the electrophoretic mobility normalised by a reference mobility marker, µ mobility marker is the electrophoretic mobility of the mobility marker, µ ref mobility marker refers to the electrophoretic mobility of the reference mobility marker (taken as an average of all mobility markers for a set of injections).

Sensitivity

Table S-1. Limit of detection (LOD) and limit of quantification (LOQ) of the CE with direct UV detection used in this work and in comparison with the literature (see page before last for reference list). LOD is defined as the concentration for which the signal-to-noise ratio (SNR) is equal to 3, LOQ as the concentration for which SNR is equal to 10.

Linearity of the calibration curves

Determination of outlier -Grubbs Test.

This test was used to determine outliers for CE data. The mean, 𝑥̅ , and standard deviation, s, were calculated of the sample with the point included. If more than one point was a possible outlier, then the furthest from the mean was taken in priority.

Hypothesis -statement of truth "selected data point comes from the same sample as all data points in set" i.e. the point, in question, is not an outlier.

Calculation of G, the statistic value which represents the "number of standard deviation" the point in question is from the mean, see Equation S-2.

If G > critical value, the hypothesis is false and the suspect point is an outlier and is omitted. ^ BDL stands for "below detection limit".

NP200 Buffer Decompositionchange in current over time

The plateau value of the current, c, for a given CE experiment, was measured and plotted against time that had lapsed since the preparation of the buffer (see