Article pubs.acs.org/JAFC
A Novel Approach to Monitor the Hydrolysis of Barley (Hordeum vulgare L) Malt: A Chemometrics Approach D. Cozzolino,* S. Degner, and J. Eglinton School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, South Australia 5064, Australia ABSTRACT: Malting barley is a process that has been profusely studied and is known to be influenced by several physical and biochemical properties of the grain. In particular, the amount of material that can be extracted from the malt (malt extract) is an important measure of brewing performance and end quality. The objectives of this study were (a) to compare the time course of hydrolysis of different malting barley (Hordeum vulgare L) varieties and (b) to evaluate the usefulness of mid-infrared (MIR) spectroscopy as high-throughput method to monitor malt hydrolysis. Differences in the pattern of hydrolysis were observed between the malt samples analyzed where samples from the same variety that have similar hot water extract (HWE) values tend to have the same pattern of hydrolysis. Principal component score plots based on the MIR spectra showed similar results. Partial least-squares discriminate analysis (PLS-DA) was used to classify malt samples according to their corresponding variety and time course of hydrolysis. The coefficient of determination (R2) and the standard error of cross validation (SECV) obtained for the prediction of variety and time course of hydrolysis were 0.67 (1.01) and 0.38 (19.90), respectively. These differences might be the result of the different composition in sugars between the barley varieties analyzed after malting, measured as wort density and not observed when only the HWE value at the end point is reported. This method offers the possibility to measure several parameters in malt simultaneously, reducing the time of analysis as well as requiring minimal sample preparation. KEYWORDS: hydrolysis, malt, barley, sugars, principal component analysis, mid-infrared
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INTRODUCTION Malting of barley and the use of barley (Hordeum vulgare L) malt to produce fermented beverages are among the earliest biotechnological process used by humans, with records dating back to the beginnings of agriculture.1−4 Malt is defined as a barley grain that has been germinated under controlled conditions for 4 to 6 days, in which germination has been interrupted by the kilning process, and dried, hydrolyzing its starch into fermentable sugars.3,7,8 This process has been profusely studied and is known to be influenced by several physical and biochemical grain properties most of which are controlled and regulated by both the genetic makeup of the barley and the environmental conditions under which it is grown, stored, or malted.4−7 Improving malt quality is one of the key objectives in many barley breeding programs where malt extract, usually reported as hot water extract (HWE), is considered the main quality characteristic. This parameter (malt extract, fine extract, HWE) is determined by laboratories in malthouses, breweries, and breeding programs across the world and is calculated as the amount of extract a malting cultivar can yield.8,9 Malt extract is of crucial economic importance, because it determines the amount of beer that can be produced and as a consequence is one of the main parameters used in breeding programs in order to develop varieties with high malt quality characteristics and is considered one of the most important quality parameter for purchasing malt.3,7−9 It is well recognized that in good malting quality cultivars, most of the starchy endosperm is converted into water extract with low viscosity.4,8,10 However, measuring malting quality is an expensive and complex process, limiting its use in barley © XXXX American Chemical Society
cultivar development and adding to the challenges in breeding.4,5,7 The available laboratory methods estimate the content of HWE by measuring the specific gravity of the wort and relating the strengths of sucrose solutions with their specific gravities, assuming that the dissolved changes in the extract solids measured as specific gravity are to the same extent related to sucrose.3,4,11 However, the amount of sucrose equivalent or the overall final density that is routinely used to calculate the HWE might not explain the observed differences in HWE between barley varieties yielding high malt extract values (HWE > 80%).5,12,13 Over the past years, the so-called process analytical technologies have proved to be one of the most efficient and advanced tools for continuous monitoring, controlling the processes and the quality of raw ingredients and products in several fields including food processing, petrochemical, and pharmaceutical industries.14−18 Several applications can be found on the use and implementation of instrumental methods such as those based on infrared (IR) combined with chemometrics for online and at-line analysis in the beverage industries.17,18 The driving force behind this transition from traditional laboratory analysis to process analysis is the need for more rapid process control information, as well as economical, safety, and environmental issues.14−18 Therefore, fast and reliable process quality control methods and techniques will provide the industry with real time information systems in Received: August 27, 2014 Revised: November 13, 2014 Accepted: November 13, 2014
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Figure 1. Patterns of hydrolysis in different malt varieties having different hot water extract values. (Hanna, HI 96801, Hanna Instruments, Inc. Rhode Island, USA) and converted to density. The supernatant (wort) samples were scanned using a platinum diamond attenuated total reflectance (ATR) single reflection sampling module cell, mounted in a Bruker Alpha instrument (Bruker Optics GmbH, Ettlingen, Germany). Duplicates of each sample were scanned twice, and the average ATR-mid-infrared (MIR) spectrum of each sample was used for further analysis. The ATR-MIR spectra were recorded on OPUS software version 7.0 provided by Bruker Optics. The spectrum for each sample was obtained by taking the average of 24 scans (resolution of 4 cm−1, between 4000 and 375 cm−1) with a scanner speed of 7.5 kHz (background of 24 scans). Air was used as reference background spectra. The ATR diamond surface was cleaned with ethanol (95% v/v) before each sample was scanned. The absorption region between 2500 and 2000 cm−1 due to carbon dioxide and the ATR diamond cell was discarded prior the calculation.21,22 The Unscrambler X software (v. 10.1, CAMO ASA, Norway) was used for preprocessing and chemometric analysis. Principal component analysis (PCA) was performed to determine any relevant and interpretable structure in the data, to detect outlier samples, and to visualize the changes in the MIR spectra related to the time course of the hydrolysis.23,24 The ATR-MIR spectral data was preprocessed using Savitzky−Golay second derivative (40 smoothing points and second polynomial order) in order to remove and correct for baseline effects.25 The second derivative is a measure of the change in the slope of the curve ignoring the offset and is very effective in removing both baseline offset and slope from a spectrum.25 Classification models were developed separately for each variety and time course of hydrolysis. Discrimination models were developed using partial least-squares discriminant analysis (PLS-DA) (The Unscrambler X, CAMO ASA, Norway).23,24 Group membership of a new unknown sample was determined by its predicted value using PLS-DA.23,24 PCA and PLS-DA models were developed by using full cross validation (leave one out) where the number of terms
order to ensure the quality and consistency of raw materials and products, as well as allow screening of large quantities of samples.14−18 Therefore, the combination of multivariate data analysis and IR spectroscopy will be of interest in order to develop high-throughput methods to monitor different steps during malt production or rapid screening of varieties during selection or trade. The objectives of this study were (a) to compare the time course of hydrolysis of different malting barley varieties and (b) to evaluate the usefulness of mid-infrared (MIR) spectroscopy as high-throughput method to monitor malt hydrolysis.
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MATERIALS AND METHODS
Barley grain (Hordeum vulgare L) and corresponding malt samples were sourced from commercial varieties from the Barley Breeding Program (The University of Adelaide, Australia). The commercial barley malt varieties analyzed were Admiral (n = 6), Commander (n = 2), Flagship (n = 2), Gairdner (n = 2), Navigator (n = 6) and Schooner (n = 2), harvested in 2012 at one locality in South Australia (Charlick). Grain samples were malted using a Phoenix automatic micromalting system as reported previously.19 Hot water extract (HWE) was analyzed using small scale versions of the Analytica-EBC Official methods (European Brewery Convention Analytica-EBC 1998, HWE method 4.5.1).11,20 Malt samples (1 ± 0.05 g) were placed in polypropylene tubes (in duplicate), and 10 mL of hot water (65 ± 5 °C) was added to each tube. The tubes were stirred allowing the water to have total contact with the sample and then placed in a water bath (65 ± 5 °C) with continuous agitation. Tubes were taken sequentially at 5, 10, 15, 30, 40, and 60 min and placed immediately in a container with ice to stop any further biochemical reaction. Samples were centrifuged at 2500g for 20 min (Beckman, TJ6, USA). Total soluble solids (°Brix) were measured in the liquid (wort) using a digital portable refractometer B
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Figure 2. Attenuated total reflectance mid-infrared spectra of malt samples sourced from different time points during the malt hydrolysis. (eigenvectors/loadings) were defined by the prediction residual error sum of squares (PRESS) function in order to avoid overfitting of the models (The Unscrambler, CAMO AS, v. 10.1, Oslo, Norway).
same pattern of hydrolysis (Figure 1A,B). At 10 min was observed either a peak or trough in the trend of hydrolysis. These differences might be attributed to the different composition in sugars between the barley varieties analyzed. It is well-known that more than 90% of the solids present in wort are related to carbohydrates, where free sugars such as fructose, mannose, glucose, galactose, sucrose, and maltose are the most abundant. Nonstarch water-soluble sugars and cell wall components (e.g., hemicellulose) can also contribute to this.3,26 Variations in the proportion of free and water-soluble sugars in different varieties of barley grain have been reported by other authors might also explain the observed patterns.3,26 It has been reported that HWE extracts from the malt are lower than those for the corresponding polysaccharides from the same grain, indicating that cleavage of some glycosidic bonds has occurred during malting.3,26 However, all the reported studies on malt extract usually refer to the end point of HWE measured using the EBC method. The results of this study showed that the pattern or trend of starch hydrolysis might be more important than the end value. In particular, the amount of sucrose equivalent or the overall final density that is routinely used to calculate HWE might not explain the observed differences in HWE between barley varieties having high malt extract (HWE > 80%). The results from this study also suggested that the pool of sugars in the wort tend to have high density such as fructose (1.69 g/cm3) compared with glucose (1.54 g/cm3). The observed differences in density might explain the increases in HWE between the malt varieties analyzed and are in agreement with early reports by other authors.27−30 These authors reported that during kilning of the malt both glucose and sucrose increased, where the increase in sucrose is particularly well marked, indicating the important role that is played by kilning in altering the characteristics of the grain as well as the action of amylase that naturally becomes more important as malting progresses.27−30 Some other sugars or oligosaccharides tend also to increase, among these fructosans being the most important.30
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RESULTS AND DISCUSSION Patterns of Hydrolysis: Reference Method. Figure 1A− C shows the changes in density at different time points during
Figure 3. Principal component score plot (PC1 vs PC2) of all malt varieties analyzed using attenuated total reflectance mid-infrared spectroscopy.
the monitoring of the time course of starch hydrolysis in the different barley malt varieties analyzed. A nonlinear trend in the pattern of hydrolysis was observed between the different malt varieties. However, this pattern was not the same for all malt varieties analyzed. In malt varieties such as Admiral, Commander, and Flagship, an increase in density from 0 to 10 min was observed followed by a steady decrease in density after 15 min, after which time point density tends to increase until 60 min (end point). The opposite trend was observed for malting varieties such as Gairdner, Navigator, and Schooner. Moreover, malt samples from the same variety that have similar HWE (measured using the EBC method) tend to have the C
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Figure 4. Eigenvectors derived from the first three principal component analyses of all malt varieties analyzed using attenuated total reflectance midinfrared spectroscopy.
MIR spectra in the fingerprint region of the wort samples analyzed. The spectra were dominated by intense peaks around 1030, 1070, 1160, and 1630 cm−1 due to water, sugars, and nitrogen compounds. These peaks might be related to the CH−OH and alkyl frequencies for sugars mainly associated with glucose and fructose, between 1000 and 1200 cm−1.32−38 Most of the variation in the ATR-MIR spectra was observed between 1000 and 1200 cm−1 (related to stretching modes of C−C and C−O groups), and it has been mainly related to differences in the release of sugars (measured as density) as a function of the time course of the hydrolysis as reported by other authors.32−38 Figure 3 shows the principal component score plot of the time course of hydrolysis using all the malting varieties analyzed using ATR-MIR. The first three principal components explain more than 90% of the variation in the ATR-MIR spectra (PC1 = 79%, PC2 = 17%, and PC3 = 2%). Differences in the patterns of the scores between the malt varieties and within the samples from the same variety as a consequence of the time course of hydrolysis were observed. Figure 4 shows the eigenvectors derived from the score plot of the first three principal components obtained from the analysis of wort samples using ATR-MIR spectra. The analysis of the first three eigenvectors indicated that the MIR regions related to sugars explain most of the observed differences between the malt samples. The highset eigenvectors were observed at 1130 and 1025 cm−1 characteristic of sucrose and at 1032 cm−1 characteristic of glucose.32 Characteristic absorption bands of fructose are observed in the range between 1000 and 1100 cm−1, while the region between 1056 and 1116 cm−1 corresponds to the interference between
It is well-known that the major source of extract in malt wort is starch; however free sugars are also important, sucrose being one of the most abundant. Both mannose and galactose occur combined in malt, but neither is released during mashing. In wort samples, maltose, along with many other compounds, is produced during mashing by the partial hydrolysis of starch. There is some evidence that small amounts of fructans might also occur in malt.3 These can be regarded as sucrose molecules to which one or more fructose residues have been attached. However, because the levels of fructose do not increase appreciably during mashing, it is likely that the fructans, which are very soluble, are not hydrolyzed, and so they remain with the nonfermentable carbohydrates.3 Mashing constitutes the enzymatic hydrolysis of starch, resulting in the production of glucose, maltose, and glucose-based oligosaccharides.31 However, there are other starch based carbohydrates in malted barley, which also contains sucrose.31 In this context, the activity of the invertase enzyme facilitates the hydrolysis of sucrose to yield both glucose and fructose altering the density of the wort.31 Therefore, the accumulation of fructose can be similar to the hydrolysis of sucrose, while the accumulation of glucose during mashing can be up to five times greater than the theoretical yield from utilized sucrose alone.31 This large accumulation of glucose during mashing is most likely due to the combined activity of different enzymes such as invertases, glucoamylases, and α-amylase.31 Infrared Analysis: Spectra Interpretation. In order to further interpret the patterns related to the time course of hydrolysis and the fate of sugars, the ATR-MIR spectra of the wort were recorded and evaluated. Figure 2 shows the ATRD
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Figure 5. Principal component score plot (PC1 vs PC2) of Admiral, Navigator and Schooner malt samples analyzed using attenuated total reflectance mid-infrared spectroscopy labeled by the time course of hydrolysis.
Figure 6. Absorbance values at specific frequencies from different barley malt varieties analyzed using attenuated total reflectance mid-infrared spectroscopy.
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glucose and fructose as reported by other authors.32−38 Bands between 900 and 1100 cm−1 are assigned to C−O and C−C stretching modes, while those between 1300 and 1100 cm−1 are associated with the bending modes of O−C−H, C−C−H, and C−O−H. It has been reported by other authors that the spectra of aqueous solution of glucose show absorbance bands at 917 and 1034 cm−1, those of fructose at 1062 and 1151 cm−1, and those of sucrose at 926, 1005, 1048, and 1124 cm−1,32−38 while sucrose is characterized by a peak at 1005 cm−1 owing to the presence of glycosidic links.39,40 A major peak at 1034 and 1062 cm−1 was observed for glucose and fructose, respectively, while three distinct peaks were obtained for sucrose with the major peak being centered at 1048 cm−1. This shift in the frequencies of the major peaks can be explained by the difference in the chemical environment surrounding the atoms concerned with this vibrational band.41 Principal Component Analysis of the Time Course of Hydrolysis in Different Varieties. In an attempt to gain greater insight into the changes within the different malt varieties analyzed, PCA analysis was carried out for the single varieties separately (Figure 5). Changes in the direction of the scores derived from the MIR spectra were linear from 5 to 15 min, while a change in this trend was observed from 30 to 60 min. Similar changes were observed in the raw and transformed spectra (data not shown). Three main peaks were selected and compared between the varieties, and the relative frequencies for each variety are shown in Figure 6, around 1060 cm−1 related to fructose and around 1160 cm−1 with the combination of glucose and fructose as reported by other authors.32−38 It has been observed that malt varieties that tend to yield high HWE present high frequencies in the wavenumber regions associated with high density sugars such as fructose (e.g., Navigator) while malt varieties that tend yield intermediate to high HWE have high frequencies in the region associated with glucose (e.g., Admiral, Flagship). Discriminant Analysis. PLS-DA was used to classify malt samples according to their corresponding variety and time course of hydrolysis. The coefficient of determination (R2) and the standard error of cross validation (SECV) obtained for the prediction of variety and time course of hydrolysis were 0.67 (SECV = 1.01) and 0.38 (SECV = 19.90), respectively. These results suggested that the time course and patterns of hydrolysis are affected by the variety and might be explained by the different composition in sugars as well as other chemical components of the grain. In this study, the combination of spectroscopy and chemometrics as an analytical tool gave the advantage of rapid monitoring of the changes occurring during malt hydrolysis without the need for quantitative data. These results also suggested that the observed patterns in malt hydrolysis (reference data and PCA scores from the MIR spectra) and the information derived from the eigenvectors indicated that the observed differences in the patterns are mainly associated with variety and not with the time course of the hydrolysis. Although other biochemical components influence the final level of extract including husk thickness, grain size, protein, starch, nonstarch polysaccharides, and enzyme production, as well as the malting process and mashing conditions (pH, temperature, mash time, grist/particle size) only the patterns related to sugars were evaluated in this study.7 Compared with traditional laboratory methods, IR provides with new and better insight into complex problems by measuring a great number of chemical compounds at once.
These methods are attractive due to their inherent features of versatility, flexibility, effectiveness, and richness of information. Further studies will be carried out in order to validate the proposed methodology with the addition of more samples derived from different harvests, localities and varieties.
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AUTHOR INFORMATION
Corresponding Author
*E-mail: [email protected]. Funding
This project (UA00126) is supported by Australia’s grain growers through their investment body, the Grain Research and Development Corporation (GRDC), with matching funds from the Australian government. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors thank technical staff of the Barley Quality Laboratory and Barley Breeding Program, University of Adelaide.
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REFERENCES
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A Novel Approach to Monitor the Hydrolysis of Barley (Hordeum vulgare L) Malt: A Chemometrics Approach D. Cozzolino,* S. Degner, and J. Eglinton School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, South Australia 5064, Australia ABSTRACT: Malting barley is a process that has been profusely studied and is known to be influenced by several physical and biochemical properties of the grain. In particular, the amount of material that can be extracted from the malt (malt extract) is an important measure of brewing performance and end quality. The objectives of this study were (a) to compare the time course of hydrolysis of different malting barley (Hordeum vulgare L) varieties and (b) to evaluate the usefulness of mid-infrared (MIR) spectroscopy as high-throughput method to monitor malt hydrolysis. Differences in the pattern of hydrolysis were observed between the malt samples analyzed where samples from the same variety that have similar hot water extract (HWE) values tend to have the same pattern of hydrolysis. Principal component score plots based on the MIR spectra showed similar results. Partial least-squares discriminate analysis (PLS-DA) was used to classify malt samples according to their corresponding variety and time course of hydrolysis. The coefficient of determination (R2) and the standard error of cross validation (SECV) obtained for the prediction of variety and time course of hydrolysis were 0.67 (1.01) and 0.38 (19.90), respectively. These differences might be the result of the different composition in sugars between the barley varieties analyzed after malting, measured as wort density and not observed when only the HWE value at the end point is reported. This method offers the possibility to measure several parameters in malt simultaneously, reducing the time of analysis as well as requiring minimal sample preparation. KEYWORDS: hydrolysis, malt, barley, sugars, principal component analysis, mid-infrared
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INTRODUCTION Malting of barley and the use of barley (Hordeum vulgare L) malt to produce fermented beverages are among the earliest biotechnological process used by humans, with records dating back to the beginnings of agriculture.1−4 Malt is defined as a barley grain that has been germinated under controlled conditions for 4 to 6 days, in which germination has been interrupted by the kilning process, and dried, hydrolyzing its starch into fermentable sugars.3,7,8 This process has been profusely studied and is known to be influenced by several physical and biochemical grain properties most of which are controlled and regulated by both the genetic makeup of the barley and the environmental conditions under which it is grown, stored, or malted.4−7 Improving malt quality is one of the key objectives in many barley breeding programs where malt extract, usually reported as hot water extract (HWE), is considered the main quality characteristic. This parameter (malt extract, fine extract, HWE) is determined by laboratories in malthouses, breweries, and breeding programs across the world and is calculated as the amount of extract a malting cultivar can yield.8,9 Malt extract is of crucial economic importance, because it determines the amount of beer that can be produced and as a consequence is one of the main parameters used in breeding programs in order to develop varieties with high malt quality characteristics and is considered one of the most important quality parameter for purchasing malt.3,7−9 It is well recognized that in good malting quality cultivars, most of the starchy endosperm is converted into water extract with low viscosity.4,8,10 However, measuring malting quality is an expensive and complex process, limiting its use in barley © XXXX American Chemical Society
cultivar development and adding to the challenges in breeding.4,5,7 The available laboratory methods estimate the content of HWE by measuring the specific gravity of the wort and relating the strengths of sucrose solutions with their specific gravities, assuming that the dissolved changes in the extract solids measured as specific gravity are to the same extent related to sucrose.3,4,11 However, the amount of sucrose equivalent or the overall final density that is routinely used to calculate the HWE might not explain the observed differences in HWE between barley varieties yielding high malt extract values (HWE > 80%).5,12,13 Over the past years, the so-called process analytical technologies have proved to be one of the most efficient and advanced tools for continuous monitoring, controlling the processes and the quality of raw ingredients and products in several fields including food processing, petrochemical, and pharmaceutical industries.14−18 Several applications can be found on the use and implementation of instrumental methods such as those based on infrared (IR) combined with chemometrics for online and at-line analysis in the beverage industries.17,18 The driving force behind this transition from traditional laboratory analysis to process analysis is the need for more rapid process control information, as well as economical, safety, and environmental issues.14−18 Therefore, fast and reliable process quality control methods and techniques will provide the industry with real time information systems in Received: August 27, 2014 Revised: November 13, 2014 Accepted: November 13, 2014
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Figure 1. Patterns of hydrolysis in different malt varieties having different hot water extract values. (Hanna, HI 96801, Hanna Instruments, Inc. Rhode Island, USA) and converted to density. The supernatant (wort) samples were scanned using a platinum diamond attenuated total reflectance (ATR) single reflection sampling module cell, mounted in a Bruker Alpha instrument (Bruker Optics GmbH, Ettlingen, Germany). Duplicates of each sample were scanned twice, and the average ATR-mid-infrared (MIR) spectrum of each sample was used for further analysis. The ATR-MIR spectra were recorded on OPUS software version 7.0 provided by Bruker Optics. The spectrum for each sample was obtained by taking the average of 24 scans (resolution of 4 cm−1, between 4000 and 375 cm−1) with a scanner speed of 7.5 kHz (background of 24 scans). Air was used as reference background spectra. The ATR diamond surface was cleaned with ethanol (95% v/v) before each sample was scanned. The absorption region between 2500 and 2000 cm−1 due to carbon dioxide and the ATR diamond cell was discarded prior the calculation.21,22 The Unscrambler X software (v. 10.1, CAMO ASA, Norway) was used for preprocessing and chemometric analysis. Principal component analysis (PCA) was performed to determine any relevant and interpretable structure in the data, to detect outlier samples, and to visualize the changes in the MIR spectra related to the time course of the hydrolysis.23,24 The ATR-MIR spectral data was preprocessed using Savitzky−Golay second derivative (40 smoothing points and second polynomial order) in order to remove and correct for baseline effects.25 The second derivative is a measure of the change in the slope of the curve ignoring the offset and is very effective in removing both baseline offset and slope from a spectrum.25 Classification models were developed separately for each variety and time course of hydrolysis. Discrimination models were developed using partial least-squares discriminant analysis (PLS-DA) (The Unscrambler X, CAMO ASA, Norway).23,24 Group membership of a new unknown sample was determined by its predicted value using PLS-DA.23,24 PCA and PLS-DA models were developed by using full cross validation (leave one out) where the number of terms
order to ensure the quality and consistency of raw materials and products, as well as allow screening of large quantities of samples.14−18 Therefore, the combination of multivariate data analysis and IR spectroscopy will be of interest in order to develop high-throughput methods to monitor different steps during malt production or rapid screening of varieties during selection or trade. The objectives of this study were (a) to compare the time course of hydrolysis of different malting barley varieties and (b) to evaluate the usefulness of mid-infrared (MIR) spectroscopy as high-throughput method to monitor malt hydrolysis.
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MATERIALS AND METHODS
Barley grain (Hordeum vulgare L) and corresponding malt samples were sourced from commercial varieties from the Barley Breeding Program (The University of Adelaide, Australia). The commercial barley malt varieties analyzed were Admiral (n = 6), Commander (n = 2), Flagship (n = 2), Gairdner (n = 2), Navigator (n = 6) and Schooner (n = 2), harvested in 2012 at one locality in South Australia (Charlick). Grain samples were malted using a Phoenix automatic micromalting system as reported previously.19 Hot water extract (HWE) was analyzed using small scale versions of the Analytica-EBC Official methods (European Brewery Convention Analytica-EBC 1998, HWE method 4.5.1).11,20 Malt samples (1 ± 0.05 g) were placed in polypropylene tubes (in duplicate), and 10 mL of hot water (65 ± 5 °C) was added to each tube. The tubes were stirred allowing the water to have total contact with the sample and then placed in a water bath (65 ± 5 °C) with continuous agitation. Tubes were taken sequentially at 5, 10, 15, 30, 40, and 60 min and placed immediately in a container with ice to stop any further biochemical reaction. Samples were centrifuged at 2500g for 20 min (Beckman, TJ6, USA). Total soluble solids (°Brix) were measured in the liquid (wort) using a digital portable refractometer B
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Figure 2. Attenuated total reflectance mid-infrared spectra of malt samples sourced from different time points during the malt hydrolysis. (eigenvectors/loadings) were defined by the prediction residual error sum of squares (PRESS) function in order to avoid overfitting of the models (The Unscrambler, CAMO AS, v. 10.1, Oslo, Norway).
same pattern of hydrolysis (Figure 1A,B). At 10 min was observed either a peak or trough in the trend of hydrolysis. These differences might be attributed to the different composition in sugars between the barley varieties analyzed. It is well-known that more than 90% of the solids present in wort are related to carbohydrates, where free sugars such as fructose, mannose, glucose, galactose, sucrose, and maltose are the most abundant. Nonstarch water-soluble sugars and cell wall components (e.g., hemicellulose) can also contribute to this.3,26 Variations in the proportion of free and water-soluble sugars in different varieties of barley grain have been reported by other authors might also explain the observed patterns.3,26 It has been reported that HWE extracts from the malt are lower than those for the corresponding polysaccharides from the same grain, indicating that cleavage of some glycosidic bonds has occurred during malting.3,26 However, all the reported studies on malt extract usually refer to the end point of HWE measured using the EBC method. The results of this study showed that the pattern or trend of starch hydrolysis might be more important than the end value. In particular, the amount of sucrose equivalent or the overall final density that is routinely used to calculate HWE might not explain the observed differences in HWE between barley varieties having high malt extract (HWE > 80%). The results from this study also suggested that the pool of sugars in the wort tend to have high density such as fructose (1.69 g/cm3) compared with glucose (1.54 g/cm3). The observed differences in density might explain the increases in HWE between the malt varieties analyzed and are in agreement with early reports by other authors.27−30 These authors reported that during kilning of the malt both glucose and sucrose increased, where the increase in sucrose is particularly well marked, indicating the important role that is played by kilning in altering the characteristics of the grain as well as the action of amylase that naturally becomes more important as malting progresses.27−30 Some other sugars or oligosaccharides tend also to increase, among these fructosans being the most important.30
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RESULTS AND DISCUSSION Patterns of Hydrolysis: Reference Method. Figure 1A− C shows the changes in density at different time points during
Figure 3. Principal component score plot (PC1 vs PC2) of all malt varieties analyzed using attenuated total reflectance mid-infrared spectroscopy.
the monitoring of the time course of starch hydrolysis in the different barley malt varieties analyzed. A nonlinear trend in the pattern of hydrolysis was observed between the different malt varieties. However, this pattern was not the same for all malt varieties analyzed. In malt varieties such as Admiral, Commander, and Flagship, an increase in density from 0 to 10 min was observed followed by a steady decrease in density after 15 min, after which time point density tends to increase until 60 min (end point). The opposite trend was observed for malting varieties such as Gairdner, Navigator, and Schooner. Moreover, malt samples from the same variety that have similar HWE (measured using the EBC method) tend to have the C
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Figure 4. Eigenvectors derived from the first three principal component analyses of all malt varieties analyzed using attenuated total reflectance midinfrared spectroscopy.
MIR spectra in the fingerprint region of the wort samples analyzed. The spectra were dominated by intense peaks around 1030, 1070, 1160, and 1630 cm−1 due to water, sugars, and nitrogen compounds. These peaks might be related to the CH−OH and alkyl frequencies for sugars mainly associated with glucose and fructose, between 1000 and 1200 cm−1.32−38 Most of the variation in the ATR-MIR spectra was observed between 1000 and 1200 cm−1 (related to stretching modes of C−C and C−O groups), and it has been mainly related to differences in the release of sugars (measured as density) as a function of the time course of the hydrolysis as reported by other authors.32−38 Figure 3 shows the principal component score plot of the time course of hydrolysis using all the malting varieties analyzed using ATR-MIR. The first three principal components explain more than 90% of the variation in the ATR-MIR spectra (PC1 = 79%, PC2 = 17%, and PC3 = 2%). Differences in the patterns of the scores between the malt varieties and within the samples from the same variety as a consequence of the time course of hydrolysis were observed. Figure 4 shows the eigenvectors derived from the score plot of the first three principal components obtained from the analysis of wort samples using ATR-MIR spectra. The analysis of the first three eigenvectors indicated that the MIR regions related to sugars explain most of the observed differences between the malt samples. The highset eigenvectors were observed at 1130 and 1025 cm−1 characteristic of sucrose and at 1032 cm−1 characteristic of glucose.32 Characteristic absorption bands of fructose are observed in the range between 1000 and 1100 cm−1, while the region between 1056 and 1116 cm−1 corresponds to the interference between
It is well-known that the major source of extract in malt wort is starch; however free sugars are also important, sucrose being one of the most abundant. Both mannose and galactose occur combined in malt, but neither is released during mashing. In wort samples, maltose, along with many other compounds, is produced during mashing by the partial hydrolysis of starch. There is some evidence that small amounts of fructans might also occur in malt.3 These can be regarded as sucrose molecules to which one or more fructose residues have been attached. However, because the levels of fructose do not increase appreciably during mashing, it is likely that the fructans, which are very soluble, are not hydrolyzed, and so they remain with the nonfermentable carbohydrates.3 Mashing constitutes the enzymatic hydrolysis of starch, resulting in the production of glucose, maltose, and glucose-based oligosaccharides.31 However, there are other starch based carbohydrates in malted barley, which also contains sucrose.31 In this context, the activity of the invertase enzyme facilitates the hydrolysis of sucrose to yield both glucose and fructose altering the density of the wort.31 Therefore, the accumulation of fructose can be similar to the hydrolysis of sucrose, while the accumulation of glucose during mashing can be up to five times greater than the theoretical yield from utilized sucrose alone.31 This large accumulation of glucose during mashing is most likely due to the combined activity of different enzymes such as invertases, glucoamylases, and α-amylase.31 Infrared Analysis: Spectra Interpretation. In order to further interpret the patterns related to the time course of hydrolysis and the fate of sugars, the ATR-MIR spectra of the wort were recorded and evaluated. Figure 2 shows the ATRD
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Figure 5. Principal component score plot (PC1 vs PC2) of Admiral, Navigator and Schooner malt samples analyzed using attenuated total reflectance mid-infrared spectroscopy labeled by the time course of hydrolysis.
Figure 6. Absorbance values at specific frequencies from different barley malt varieties analyzed using attenuated total reflectance mid-infrared spectroscopy.
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glucose and fructose as reported by other authors.32−38 Bands between 900 and 1100 cm−1 are assigned to C−O and C−C stretching modes, while those between 1300 and 1100 cm−1 are associated with the bending modes of O−C−H, C−C−H, and C−O−H. It has been reported by other authors that the spectra of aqueous solution of glucose show absorbance bands at 917 and 1034 cm−1, those of fructose at 1062 and 1151 cm−1, and those of sucrose at 926, 1005, 1048, and 1124 cm−1,32−38 while sucrose is characterized by a peak at 1005 cm−1 owing to the presence of glycosidic links.39,40 A major peak at 1034 and 1062 cm−1 was observed for glucose and fructose, respectively, while three distinct peaks were obtained for sucrose with the major peak being centered at 1048 cm−1. This shift in the frequencies of the major peaks can be explained by the difference in the chemical environment surrounding the atoms concerned with this vibrational band.41 Principal Component Analysis of the Time Course of Hydrolysis in Different Varieties. In an attempt to gain greater insight into the changes within the different malt varieties analyzed, PCA analysis was carried out for the single varieties separately (Figure 5). Changes in the direction of the scores derived from the MIR spectra were linear from 5 to 15 min, while a change in this trend was observed from 30 to 60 min. Similar changes were observed in the raw and transformed spectra (data not shown). Three main peaks were selected and compared between the varieties, and the relative frequencies for each variety are shown in Figure 6, around 1060 cm−1 related to fructose and around 1160 cm−1 with the combination of glucose and fructose as reported by other authors.32−38 It has been observed that malt varieties that tend to yield high HWE present high frequencies in the wavenumber regions associated with high density sugars such as fructose (e.g., Navigator) while malt varieties that tend yield intermediate to high HWE have high frequencies in the region associated with glucose (e.g., Admiral, Flagship). Discriminant Analysis. PLS-DA was used to classify malt samples according to their corresponding variety and time course of hydrolysis. The coefficient of determination (R2) and the standard error of cross validation (SECV) obtained for the prediction of variety and time course of hydrolysis were 0.67 (SECV = 1.01) and 0.38 (SECV = 19.90), respectively. These results suggested that the time course and patterns of hydrolysis are affected by the variety and might be explained by the different composition in sugars as well as other chemical components of the grain. In this study, the combination of spectroscopy and chemometrics as an analytical tool gave the advantage of rapid monitoring of the changes occurring during malt hydrolysis without the need for quantitative data. These results also suggested that the observed patterns in malt hydrolysis (reference data and PCA scores from the MIR spectra) and the information derived from the eigenvectors indicated that the observed differences in the patterns are mainly associated with variety and not with the time course of the hydrolysis. Although other biochemical components influence the final level of extract including husk thickness, grain size, protein, starch, nonstarch polysaccharides, and enzyme production, as well as the malting process and mashing conditions (pH, temperature, mash time, grist/particle size) only the patterns related to sugars were evaluated in this study.7 Compared with traditional laboratory methods, IR provides with new and better insight into complex problems by measuring a great number of chemical compounds at once.
These methods are attractive due to their inherent features of versatility, flexibility, effectiveness, and richness of information. Further studies will be carried out in order to validate the proposed methodology with the addition of more samples derived from different harvests, localities and varieties.
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AUTHOR INFORMATION
Corresponding Author
*E-mail: [email protected]. Funding
This project (UA00126) is supported by Australia’s grain growers through their investment body, the Grain Research and Development Corporation (GRDC), with matching funds from the Australian government. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors thank technical staff of the Barley Quality Laboratory and Barley Breeding Program, University of Adelaide.
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REFERENCES
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