Lactose, galactose and glucose determination in naturally “lactose free” hard cheese: HPAEC-PAD method validation

Food Chemistry 220 (2017) 18–24

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Analytical Methods

Lactose, galactose and glucose determination in naturally ‘‘lactose free” hard cheese: HPAEC-PAD method validation Lucia Monti a,⇑, Stefano Negri a, Aurora Meucci a, Angelo Stroppa b, Andrea Galli a, Giovanna Contarini a a Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria – Centro di ricerca per le Produzioni Foraggere e Lattiero-Casearie (CREA-FLC), Via A. Lombardo 11, 26900 Lodi (LO), Italy b Consorzio Tutela Grana Padano, Via XXIV Giugno 8, 25015 San Martino Della Battaglia, (BS), Italy

a r t i c l e

i n f o

Article history: Received 30 May 2016 Received in revised form 28 September 2016 Accepted 28 September 2016 Available online 29 September 2016 Chemical compounds studied in this article: Lactose (PubChem CID: 440995) Galactose (PubChem CID: 6036) Glucose (PubChem CID: 5793)

a b s t r a c t A chromatographic method by HPAEC-PAD was developed and in-house validated for the quantification of low sugar levels in hard cheese, specifically Grana Padano PDO cheese. Particular attention was paid to the extraction procedure, due to residual microbial and enzymatic activities. Specificity in detection and linearity were verified. Recoveries ranged from 93% for lactose to 98% for glucose and galactose. The obtained LOD and LOQ values were, respectively, 0.25 and 0.41 mg/100 g for lactose, 0.14 and 0.27 mg/100 g for galactose, and 0.16 and 0.26 mg/100 g for glucose. The method was applied to 59 samples of Grana Padano PDO cheese: galactose showed the highest concentration and variability among the samples (1.36 ± 0.89), compared to both lactose (0.45 ± 0.12) and glucose (0.46 ± 0.13). Considering the very low levels of sugars detected, authentic PDO Grana Padano could be safely included in the diet of people suffering from lactose intolerance. Ó 2016 Elsevier Ltd. All rights reserved.

Keywords: Lactose Galactose Glucose HPAEC-PAD Method validation Grana Padano PDO cheese

1. Introduction The inability to metabolise lactose, due to the absence or reduced production of the enzyme lactase, is a widespread condition. The frequency of lactose intolerance varies considerably between different ethnic groups and populations, the lowest rates in North European, North American and Australasian people (5–18%) and the highest ones in South America, Africa and Asia with approximately 50% of the population affected and almost 90% in some Far East countries (Lomer, Parkes, & Sanderson, 2008). The alteration or the reduction in the expression of the lactase gene is the cause of primary lactase deficiency, while damage of the epithelium of the small intestine, due to different intestinal diseases, is responsible for the secondary lactase deficiency. The

⇑ Corresponding author. E-mail addresses: [email protected] (L. Monti), [email protected] (S. Negri), [email protected] (A. Meucci), [email protected] (A. Stroppa), [email protected] (A. Galli), [email protected] (G. Contarini). http://dx.doi.org/10.1016/j.foodchem.2016.09.185 0308-8146/Ó 2016 Elsevier Ltd. All rights reserved.

latter is often reversible with the correction of the underlying disease (EFSA, 2010). As a consequence, lactose tolerance varies widely among individuals with lactose maldigestion. A single threshold of lactose for all lactose intolerant subjects cannot be determined owing to the great variation in individual tolerances. In the last decades, in order to allow the consumption of dairy products also by people suffering from lactose intolerance, without experiencing discomfort, lactose-free or lactose-reduced dairy products have been developed. In dairy products, lactose content can be reduced by both lactic acid fermentation and enzymatic hydrolysis by lactase (Harju, Kallioinen, & Tossavainen, 2012). The enzymatic process leads to the reduction of lactose through its hydrolysis to glucose and galactose, thus increasing the sweetness of the product. The lactic acid microbial fermentation determines the reduction not only of lactose, but also of galactose and glucose, which are metabolized by microflora. As a result, long fermented products, as ripened hard cheese, contain very low amounts of all the sugars. There is no legal definition for the terms ‘‘lactose free” or ‘‘lactose-reduced”, either in USA or in EU legislation, except for

L. Monti et al. / Food Chemistry 220 (2017) 18–24

infant and follow-on formula in which lactose should be 610 mg/100 kcal (Commission Directive, 2006). Some EU Member States have set thresholds at national level for the use of the terms ‘‘lactose-free”, ‘‘very low lactose” and ‘‘low lactose” for foodstuffs other than products intended for infants. These threshold levels vary from 0.01 to 0.1 g/100 g of final product (EFSA, 2010). Unfortunately, to our knowledge, no official methods are available for the determination of low concentration of lactose in dairy products, and particularly in long ripened cheese. The Standard method 22662 (ISO, 2007) reports the reference HPLC method for the determination of lactose content of raw milk, heat-treated milk, dried milk and raw and pasteurised cream and the precision parameters are referred to a lactose content varying from 1.5–50 g/100 g of product. In addition, both ISO 26462 (ISO, 2010) and ISO 9622 (ISO, 2013), based on differential pH measurement and infrared spectroscopy, respectively, are only applicable to milk and liquid milk products with full lactose content. The field of application of the ISO enzymatic methods (ISO, 2002a and ISO, 2002b) is likewise restricted to dried milk and ice-mixes in dry form (IDF Bulletin International Dairy Federation., 1993) having a lactose concentration 10–50 g/100 g. Traditional approach to the analysis and detection of milk sugars is HPLC coupled with Refractive Index (RI) detector (Chavez-Servin, Castellote, & Lopez-Sabater, 2004; Pirisino, 1983; Pereira da Costa & Conte-Junior, 2015; Silveira et al., 2015) because neither fluorophore nor chromophore is necessary. However, RI has some disadvantages: it is non-specific, quite sensitive to changes in temperature, pressure, and solvent composition, and it does not allow gradients. Moreover, this detector has low sensitivity when compared to other detection methods. In order to overcome some of the above-cited disadvantages, the anion exchange chromatography coupled with the pulsed amperometric detection (HPAEC-PAD) was successfully applied to the sugar determination, also in milk and dairy products (Cataldi, Angelotti, & Bianco, 2003; Gopal & Richardson, 1996; Mullin & Emmons, 1997; Perati, De Borba, & Rohrer, 2014; Pollman, 1989; Van Calcar et al., 2014; Van Riel & Olieman, 1991). Together with chromatographic methods, the spectrophotometric/enzymatic measurement was applied to lactose and galactose determination (Lynch, Barbano, & Fleming, 2007; Portnoi & MacDonald, 2009, 2011, 2013). Despite both HPAEC-PAD and spectrophotometric/enzymatic methods improved the sensitivity (Cataldi, Campa, Angelotti, & Bufo, 1999; Cataldi et al., 2003; Portnoi & Macdonald, 2011), it still remains the problem of a precise sugar measurement in dairy products naturally containing very low amount of glucose, galactose and lactose, i.e. medium and long ripened cheeses. The aim of this research was the development and the validation of a method able to determine the real content of sugars in ripened hard cheese. This method could be successfully adopted to define the concentration limits allowing the term ‘‘naturally lactose free” to be used for labelling purposes. Moreover, it could provide more precise data on the composition of Grana Padano PDO cheese and its possible inclusion in the diet of people suffering from galactosemia, which unlike lactose intolerance, causes permanent and severe damages (EFSA, 2010). 2. Materials and methods 2.1. Chemicals and reagents Methanol, (analytical grade, >99%), potassium hexacyanoferrate (III) (purity 99%), zinc acetate (purity 99%), and the carbonate-free 50% NaOH solution for ionic chromatography were purchased from Sigma Aldrich Chemical Co., St. Louis, MO, USA. The deionized water was always obtained by Milli-QÒ system (Merck KgaA, Darmstadt, Germany). The three stock standard solutions of glucose,

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galactose and lactose, were prepared by diluting 0.1 g of each sugar (99% purity-Sigma Aldrich Chemical Co.) in 1 L of deionized water. The Carrez solutions I and II were prepared by dissolving 15.0 g of potassium hexacyanoferrate (III) and 22 g of zinc acetate in 100 mL of deionized water, respectively. The mobile phase for anionic exchange chromatography, consisting of NaOH 200 mM, was prepared as follow: one liter of deionized water, in a plastic bottle, was sonicated for 30 min and then 10.4 mL were removed and substituted with the same amount of the 50% NaOH solution. Single standards, containing different concentrations of glucose and galactose, were prepared by diluting the corresponding stock solution to yield concentrations of 0.125, 0.25, 0.5, 1, 2 and 5 mg/L. Due to high variability observed in the preliminary analyses of the lactose standard solution at a concentration of 0.125 mg/L, it was excluded from the calibration data set. 2.2. Samples To develop and validate the analytical procedure, six samples of Grana Padano PDO cheese were purchased at the local market. After removing the rind (3 mm) in such a way as to provide a sample representative of the cheese as it is usually consumed, the cheese was grinded. After the validation of the method, several Grana Padano PDO cheese samples (slices of about 1 kg each) were taken directly at producers, by the technicians of the Grana Padano Protection Consortium. All the samples belonged to the categories excellent (E) and good (G), i.e. all the cheeses met the requirements requested by the Product Specifications and were fire-branded with the PDO mark by the technicians of the Consortium. The samples ranged from 9 (period at which the cheese can be commercialized) to 23 months of ripening. Moreover, to verify the possible influence of lysozyme, additive usually adopted in the production of Grana Padano to prevent the Clostridia development, some samples produced without this additive (EnL) were collected, as well. 2.3. Sugar extraction Thirty milliliters of deionized water were added to 10 g of grinded cheese in a 100 mL flask. The flask was heated in microwave and, when the boiling started, it was immediately cooled under fresh water. The sample was then submitted to 3 cycles of sonication by probe (9.5 mm tip diameter, 23 kHz output frequency, 22% amplitude; Soniprep 150, MSE, UK) for 1 min with 30 s gaps between each cycle and homogenized by Ultraturrax (IKA-Werke GmbH & Co, Staufen, Germany) for 2 min. The sample was then quantitatively transferred into a 50 mL volumetric flask and diluted to mark with deionized water. After filtration and centrifugation at 6000g for 10 min at room temperature, 20 mL of supernatant were mixed with 400 lL of Carrez I and 500 lL of Carrez II and diluted to mark (50 mL) with deionized water. At the appearance of a thick precipitate, usually 15 min, the sample was filtered and 4 mL were loaded onto a SPE sulfonic acid bonding column (Discovery DSC-SCX, 6-ml volume, 1 g sorbents, 50 lm particle size, Sigma Aldrich Chemical Co), previously washed with 5 mL of methanol and 10 mL of deionized water. The first milliliter of eluate was discarded and the next 3 mL were recovered, filtered through a 0.45 lm nylon membrane and 25 lL of this final clarified extract was injected into the HPAEC-PAD system for analysis. 2.4. HPAEC-PAD analysis A UltiMate 3000 chromatography system (Dionex, Sunnyvale, CA) consisting of a LPG 3400 SD pump and an ECD 3000 RS

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electrochemical detector and cell outfitted with a Au working electrode and a PdH reference electrode was used for all experiments. Injections were made by an ACC 3000 autosampler (Dionex) equipped with a 25 lL sample loop. The entire system was controlled by Chromeleon chromatography software (Dionex). A CarboPac PA-20 anion-exchange column (150
3 mm) in combination with a CarboPac PA-20 guard column (30
3 mm) (Thermo Fisher Scientific Inc. Waltham, MA USA) was used to separate the cheese sugars. Ultrapure deionized water and 200 mM NaOH were used as eluents A and B, respectively, and the whole analytical cycle lasted 60 min. It included the separation step (25 min, 96% of A and 4% of B), the regeneration step (10 min, 100% B) and finally, the equilibration step applying the same conditions as the separation step. The flow rate was 0.5 mL/min. The content of each sugar (Si) in the cheese sample, expressed as mg/100 g was calculated as follow:

Si ¼

ci
RF i
12:5 m

where ci is the value, expressed in mg/L, of the sugar obtained from the calibration line, RFi is the recovery factor, 12.5 is the dilution factor and m is the mass, in grams, of the cheese portion. 2.5. Statistical analysis The method was in-house validated according to the indications of ICH Harmonized Tripartite Guidelines (ICH, 2005). At this scope, the following parameters were calculated: specificity, linearity, recovery, limit of detection (LOD), limit of quantification (LOQ) and repeatability. The detailed description of the statistical tests applied is reported together with the results. The XLSTATÒ 7.5 package (Addinsoft, France) was used. 3. Results and discussion 3.1. Analytical background 3.1.1. Chromatographic separation In the current study, Carbo Pac PA20 column was chosen for its ability to separate mixtures of simple sugars, especially mono and disaccharides, as recommended by the manufacturer. Analytes were eluted isocratically using 8 mM sodium hydroxide solution: these conditions enabled separation with good resolution of closely related carbohydrates, such as galactose and glucose, and lactose and lactulose. At high pH, decreasing pKa values of sugars correlate with an increase in retention times; unfortunately, lactose elutes later than others do, and this causes peak broadening and a slight increase in detection limits. Baseline to valley, valley to baseline, and baseline to baseline were the integration criteria adopted for galactose, glucose and lactose, respectively. Detection was performed by a rapid sequence of potentials (waveform) which were suggested by Dionex experts, considering instrument is equipped with an Au working electrode and a PdH reference one. The separation of sugars was optimized on mixed carbohydrate standard solutions, stabilized with 0.1% sodium azide to prevent bacterial growth. 3.1.2. Extraction step Microbial and enzymatic activities were noticed in samples fortified with sugars to test recovery of the extraction and analysis method. In particular, the first experiments of addition of 5 and 10 mg/100 g of standard of lactose to Grana Padano cheese provided very low increasing values of lactose (+0.11 and +0.05 mg) for the two levels, respectively. At the same time, the concentration

of both glucose and galactose showed an increase, with respect to the natural content, corresponding to the hydrolysis of the added lactose, (+2.18 and +2.06 mg for 5 mg addition and +4.11 mg and 4.28 for the 10 mg addition). It suggested a possible re-activation of beta-galactosidase. Consequently, a further step, consisting in 3 cycles of sonication, was applied to the aqueous cheese extracts, after the microwave heating, and it was effective at inactivating the enzymatic hydrolysis of lactose. Moreover, in order to protect the analytical column and to reduce potential interferences, Carrez clearing reagents accomplished removal of proteins and fats from cheese extracts. Other possible interfering contaminants were removed by using clean up procedures with solid phase extraction cartridges. Strong base anion exchange resins (Dionex OnGuard II A Cartridges 2.5 cc) were tried, but no changes were observed in the chromatogram. On the contrary, cation exchange columns (DSC-SCX) greatly simplified chromatogram, removing interfering peaks and facilitating lactose peak identification, as already observed by Gopal and Richardson (1996). 3.2. Method validation 3.2.1. Specificity Specificity is the ability to assess unequivocally the analyte in the presence of components, which may be expected to be present, e.g. impurities, degradants and matrix. The HPAEC-PAD is a very specific detector because only certain compounds will undergo a redox reaction under specific pH or voltage. Under these conditions, other compounds do not respond or respond so weakly that they do not interfere. As the scope of this method was the detection of very low amounts of sugars, it was important to confirm the specificity. This characteristic is usually verified by analysing a certified reference material with known sugar content, or a blank matrix equal to that subjected to the method, but not containing the analyte. In this case, neither certified material, nor blank matrix were available. To demonstrate the identity of galactose, glucose and lactose, the extract of a sample of Grana Padano cheese was dried under nitrogen, derivatized to obtain the silylderivatives and analyzed by GC/MS according to Becker et al. (2013)). As expected, two peaks corresponding to the lactose anomeric forms (a and b), deriving from the mutarotation occurring in water solution, were detected and recognized with a reliability higher than 90%, when compared with both the library spectra (Wiley, 2009) and that of the authentic standard, analyzed under the same conditions. Glucose and galactose were identified likewise. The identity of the three sugars was also confirmed by comparison with the retention time of authentic standards. Moreover, the double abundance of galactose with respect to both glucose and lactose, calculated on the total ion chromatogram, was comparable with that obtained by HPAEC-PAD on the same sample. 3.2.2. Linearity A linear regression analysis was performed for each sugar by using the area values of the above-mentioned standards. The calibration was repeated twice within one week. Results of the first calibration were compared with those of the second one and, for all the sugars, both intercept and slope did not show significant differences when t-test, at probability level of 0.05, was applied. Thus, a full regression line was calculated by using all the data (Table 1). As reported by Araujo (2009), it does not exist a specific test to check the linearity and the evaluation of the closeness of the coefficient of determination to unity is not sufficient to state the linearity. To that purpose three different tests were then applied: i) the F ratio between the pure experimental variance and the lack-of-fit variance (vare/varlof) (Araujo, 2009), ii) the comparison between r2 and cross-validated r2cv (Cozzoli et al., 1991) and iii) the Durbin

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L. Monti et al. / Food Chemistry 220 (2017) 18–24 Table 1 HPAEC-PAD regression parameters.

Range of concentration (mg/L) No.of levels Replicates/level Slope Standard error of slope Intercept Standard error of intercept Standard error of regression r2 F = varlof/vare r2cv Test of Durbin – Watson

Table 3 Recovery of lactose from cheese spiked with 3 different levels. Lactose

Galactose

Glucose

0.25–5.00 5 4 1.514 0.010 0.080 0.025 0.080 0.9997 2.11 0.9992 1.73

0.125–5.00 6 4 3.140 0.021 0.082 0.048 0.175 0.9990 2.23 0.9972 1.73

0.125–5.00 6 4 3.114 0.025 0.117 0.056 0.206 0.9986 2.49 0.9956 1.64

Table 2 Recovery of sugars from standard solutions submitted to the whole extraction procedure. Recovery%

mg/L

Mean ± standard deviation (n = 3) Lactose

1 2 5 10 Mean

92.9 ± 0.8 93.6 ± 1.8 93.2 ± 0.03 93.3 ± 0.9

Mean ± standard deviation (n = 3) Galactose

Mean ± standard deviation (n = 3) Glucose

97.6 ± 0.6 98.0 ± 1.5 98.7 ± 3.8

97.6 ± 1.1 98.2 ± 0.9 98.8 ± 1.3

98.1 ± 1.9

98.2 ± 1.0

–Watson test (Durbin & Watson, 1951) useful to test for the presence of serial correlation among the residuals. Results, showed in Table 1, demonstrated that there was a straight line relationship between the sugar concentration and the PAD response, within the working range.

Lactose added (mg/100 g)

0 (Blank) 2 5 10 Mean

Recovery%

Mean ± standard deviation (n = 3)

Lactose corrected by recovery factor (0.93) and blank subtraction Mean ± standard deviation (n = 3)

0.18 ± 0.002 2.00 ± 0.042 4.84 ± 0.002 9.39 ± 0.072

1.96 ± 0.045 5.00 ± 0.002 9.90 ± 0.077

98.08 ± 2.27 100.15 ± 0.05 99.00 ± 0.77 99.08 ± 1.42

Lactose detected (mg/100 g)

Mean ± standard deviation (n = 3)

The F ratio between the variances was always lower than that tabulated for the corresponding degrees of freedom at P < 0.05 (3.41 for lactose and 2.87 for glucose and galactose). The decreasing of the coefficient of determination, after the cross-validation, was very small, ranging from 0.05% (lactose) to 0.39% (glucose). Finally, the Durbin – Watson coefficient was always higher than the critical upper limit (1.39 for lactose and 1.43 for glucose and galactose).

3.2.3. Recovery The recovery of the analytical procedure was tested by submitting standard solutions, at different concentrations, to the whole extraction procedure (Table 2). The minimum value of the range of concentration of lactose was higher than that of both glucose and galactose because, due to the unavoidable dilution caused by the extraction procedure, it could not be determined with suitable precision and accuracy (see LOD and LOQ paragraph). Whereas glucose and galactose exhibited an almost complete recovery (about 98%), lactose showed a lower value (93%); nevertheless the standard deviation was comparable for all the three molecules. The recovery of these sugars, was also verified by spiking Grana Padano cheese with three different levels of lactose

Fig. 1. Partial HPAEC-PAD chromatograms of elution profile region of standard solutions of galactose/glucose, on the left, and lactose, on the right. All the samples, including blank, have been submitted to the whole extraction procedure.

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L. Monti et al. / Food Chemistry 220 (2017) 18–24

(2, 5, 10 mg/100 g) and one level (5 mg/100 g) of glucose and galactose. The spiked samples were submitted to the whole procedure. As far as the lactose is concerned, data obtained by the calibration curve were subtracted of the blank value (cheese not spiked) and corrected by applying the recovery factor previously calculated and reported in Table 2. The recovery of lactose ranged from 98 to 100% (Table 3), and demonstrated that the recovery factor obtained by applying the procedure to the standard solutions was right, and that the cheese matrix did not affect the extraction procedure. As for cheese sample added with 5 mg/100 g of glucose and galactose, results of three replicates after blank subtraction, but without application of recovery factors, confirmed the negligible influence of the whole extraction process on the quantification of the two monosaccharides (98.9 ± 0.9 for glucose and 99.1 ± 1.4 for galactose). 3.2.4. LOD and LOQ LOD is the smallest amount of analyte in the test sample that can be reliably distinguished from zero, and LOQ is the lowest concentration of analyte, which can be quantitatively determined with suitable precision and accuracy (Currie, 1995; ICH, 2005). A wide range of mathematical expressions has been used to define these concepts, resulting in different ways of calculating LOD and LOQ. The most common procedures applied are based on visual evaluation of samples with known concentrations of analyte, on Signal-to-Noise ratio, obtained by comparing samples with known low concentrations of analyte with those of blank samples and on the ratio between the standard deviation of the response and the slope of the regression line. Detailed description of the different procedures are reported in the ICH Harmonised Tripartite Guideline (ICH, 2005). The application of the above-cited approaches lead to different results, and, in order to reduce the risk of false positive results, it was decided to select the highest ones. The obtained LOD and LOQ values were 0.25 and 0.41 mg/100 g for lactose, 0.14 and 0.27 mg/100 g for galactose, and 0.16 and 0.26 mg/100 g for glucose. The reliability of these results was directly verified by analysing standard solutions at concentrations close to LOD and LOQ values (Fig. 1). The lowest baseline noise in the elution region of both glucose and galactose, together with their narrowest peak shape, justified and confirmed the lowest LOD and LOQ values obtained for these sugars with respect to those of lactose. 3.2.5. Repeatability In the full method validation, the true repeatability is calculated by the two replicate values obtained by analysing the same samples in different laboratories (ISO, 1994). In the single-laboratory validation, more replicates should be carried out, according to the indications of the Eurachem Laboratory Guide to Method Validation (Eurachem Guide, 2014). At this scope, six independent sugar measurements were performed on the same cheese by a single analyst, using the same equipment, over a short timescale. The results of the repeatability, expressed as relative standard deviation (RSD), were comparable for the three sugars (2.76, 2.47 and 2.79 for lactose, galactose and glucose, respectively) and the repeatability limit (0.04, 0.12 and 0.05 for lactose, galactose and glucose, respectively) was proportional to the sugar concentration (0.42, 1.33 and 0.45 mg/100 g for lactose, galactose and glucose, respectively). 3.3. Sugar concentration in long ripened Grana Padano PDO cheese Fig. 2 reports the plot of the results obtained on the 59 samples of Grana Padano PDO cheese, with respect to the ripening months. Ten samples provided values of lactose lower than the LOD (0.25)

Fig. 2. Concentration of lactose, galactose and glucose in the 59 samples of Grana Padano PDO cheese. Full and dotted lines indicate LOD and LOQ values, respectively.

and were not reported. Among the other results, 20 samples showed concentrations ranging between LOD and LOQ, and these values, even though not quantified with a correct precision, were included in the calculation of mean and standard deviation reported in Table 4. As far as the results of galactose and glucose are concerned, no samples provided values lower than the corresponding LOD and LOQ. Galactose showed the highest concentration together with the highest variability among the samples (1.36 ± 0.89), with respect to both lactose (0.45 ± 0.12) and glucose (0.46 ± 0.13), which provided comparable data. No relationship with the ripening time was observed, for all the three sugars. Before testing the possible differences among the cheese categories, the normality of the distribution was verified by applying the Shapiro-Wilk test to all the sugars and categories (E, EnL and G). Only lactose resulted well-modeled by a normal distribution (p < 0.05); as a consequence, the differences among the categories

L. Monti et al. / Food Chemistry 220 (2017) 18–24

Table 4 Mean ± standard deviation of the sugar concentration (mg/100 g) in the different cheese categories. Quality category (n.of samples)

Lactose* Galactose Glucose

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Conflict of interest The authors declare no competing financial interest.

Overall

E(28)

EnL(15)

G(16)

0.44 ± 0.11a 1.16 ± 0.66 a 0.42 ± 0.11 a

0.43 ± 0.17 a 1.92 ± 1.19b 0.52 ± 0.11 b

0.47 ± 0.09 1.20 ± 0.74 0.46 ± 0.17

Acknowledgements a a ab

0.45 ± 0.12 1.36 ± 0.89 0.46 ± 0.13

* Values lower than LOD (10 samples: 4 of category E, 5 of category EnL and 1 of category G) were excluded; a Means in the same row without a common superscript letter differ significantly (P < 0.05).

were tested by applying the Levene test to the lactose results, and the Kruskal-Wallis test, to galactose and glucose data (Table 4). The different cheese categories did not influence the lactose concentration. On the contrary, the absence of lysozyme in the Grana Padano production process, seemed able to slightly reduce both galactose and glucose degradation, resulting in a significantly higher concentration of these sugars in the EnL cheese. The presence of small defects, such as micro-holes or microslits, in the cheese paste of category G, did not affect the sugar concentration, which resulted not significantly different from that of samples of category E. Bibliographic data about sugar content of the most important Italian PDO hard cheeses, i.e. Grana Padano and Parmigiano Reggiano, are scarce and difficult to compare due to the different analytical techniques applied, not always able to detect sugars at very low levels. Pollman (1989) analyzed grated hard cheese using ion chromatography with pulsed amperometric detection and found no levels of lactose in excess of 10 mg/100 g and of galactose more than 30 mg/100 g, in authentic PDO hard cheese. More recently, Portnoi and MacDonald (2013) summarized results of lactose and galactose content of cheeses analyzed since 2001, mainly by enzymatic analysis (LOD of lactose and galactose 7 and 3.5 mg/100 g, respectively) and only recently by HPAEC-PAD (LOD of lactose and galactose 1 mg/100 g). All the analyzed samples, apart one, contained no detectable lactose, and only two samples showed amount of galactose higher than LOD. Our results are in agreement with the literature data, and, the sensitivity of the method we applied allowed a more precise quantification of the sugar concentration. 4. Conclusions The extraction showed to be the most delicate step of the whole procedure developed for the determination of low sugar content in cheese. The inactivation of the residual enzymatic activity, by sonication and rapid heating by microwave, are mandatory to guarantee accurate results. The chromatographic system HPAEC-PAD allowed concentrations of lactose, glucose and galactose lower than 1 mg/100 g of cheese, to be correctly measured. The application of this analytical method to a long ripened cheese demonstrated that lactose was naturally reduced from about 4.7 g/100 g (in milk) to 0.5 mg/100 g (in cheese). At the same time, and contrary to ‘‘lactose free” or ‘‘lactose reduced” milk products obtained by the addition of beta-galactosidase, also galactose and glucose are quite completely metabolized. Thus, authentic PDO Grana Padano cheese could be safely included in the diet of people suffering from lactose intolerance. Moreover, the opportunity to introduce this cheese in the diet of people suffering from galactosaemia, can be also taken into consideration.

Funding for this research was provided by Grana Padano Protection Consortium.

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