- Email: [email protected]
Uncertainty of antioxidant profiling in complex mixtures using liquid chromatography involving post-column derivatisation
Journal of Food Composition and Analysis 33 (2014) 216–219
Contents lists available at ScienceDirect
Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Commentary
Uncertainty of antioxidant profiling in complex mixtures using liquid chromatography involving post-column derivatisation§ Bronisław K. Gło´d a,d, Marian Kamin´ski b,d, Paweł K. Zarzycki c,d,* a
Department of Analytical Chemistry, Institute of Chemistry, Faculty of Science, Siedlce University of Natural Sciences and Humanities, 3 Maja 54, 08-110 Siedlce, Poland b Department of Chemical and Process Engineering, Chemical Faculty, Gdan´sk University of Technology, 11/12 Narutowicza St, 80-233 Gdan´sk, Poland c Section of Toxicology and Bioanalytics, Department of Civil and Environmental Engineering, Koszalin University of Technology, S´niadeckich 2, 75-453 Koszalin, Poland d Polish Society of the Separation Science, Poland
A R T I C L E I N F O
A B S T R A C T
Article history: Received 3 November 2012 Received in revised form 19 January 2013 Accepted 3 February 2013
The main goal of this paper is to discuss the problems associated with antioxidant profiling in complex samples using a high-throughput HPLC system coupled with post-column derivatisation reactor. Based on the experimental data reported in the literature, we demonstrated that improper optimisation of temperature and/or pH assay conditions performed using an on-line derivatisation reactor may substantially change the antioxidant peaks ratio of targeted phytochemical compounds. It has been found that despite the relatively high stability of flavonoids at high temperature and under binary mobile phase HPLC conditions, the reaction of target compounds with common ABTS, FCR and DPPH radicals at elevated regions (particularly above 100 8C) dramatically changes their antioxidant activity values expressed, for example, as TEAC (Trolox equivalent antioxidant capacity) parameters. In principle, separation and detection processes of antioxidant profiling assay must not significantly affect the antioxidant activity of target compounds. In the case of foods eaten by humans or animals, critical experimental parameters such as pH and temperature concerning interaction of target analytes with derivatisation reagent should be as close as possible to the real physiological values. ß 2013 Elsevier Inc. All rights reserved.
Keywords: Total antioxidant activity Antioxidant fingerprints Trolox equivalent antioxidant capacity Post-column derivatisation HPLC Temperature Food analysis Food composition Analytical method uncertainty
1. Problem overview and discussion A wide range of low-molecular mass compounds may act as direct radical scavengers or as agents capable of enhancing the resistance to oxidation of biologically active substances in medicinal, pharmaceutical, food, cosmetic and environmental materials. The chemical non-homogeneity of antioxidants, and their relatively low concentration in high organic load samples presents unique challenges for sample handling and analysis. Moreover, many antioxidants can interact with each other, in particular via redox reactions, increasing or decreasing synergetic
§ Editorial note: Journal of Food Composition and Analysis welcomes discussion from other researchers on this Commentary, and will be happy to publish pertinent comments in the area of analytical uncertainty in this particular field of food composition. * Corresponding author at: Section of Toxicology and Bioanalytics, Department of Civil and Environmental Engineering, Koszalin University of Technology, S´niadeckich 2, 75-453 Koszalin, Poland. Tel.: +48 94 3478671. E-mail addresses: [email protected], [email protected] (P.K. Zarzycki).
0889-1575/$ – see front matter ß 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jfca.2013.02.012
effects within a given matrix. Therefore, the choice of method for antioxidant profiling depends strongly on the required outcome. For example: total antioxidant potential (TAP) can be relatively easily determined using bulk spectrophotometric tests, without isolation of individual components from a particular sample. However, for the accurate measurement of antioxidant properties of individual compounds of interest in complex samples, a number of liquid-chromatography-based methods have been extensively studied and developed (Ding et al., 2009; Gło´d et al., 2012a,b). Recently, Kusznierewicz and co-authors reported a chromatographic protocol for the determination of antioxidants in complex samples involving coupled post-column derivatisation of target substances (Kusznierewicz et al., 2011a,b). In the method described by the authors, it is their intention that optimised separation and detection protocols appear to represent ‘‘a ready-to-use toolbox for the food and pharmaceutical industries, enabling the monitoring of bioactive substances along the production line and during storage, and the characterisation of plant material by creating chromatographic profiles supplemented with antioxidant fingerprints’’ (Kusznierewicz et al., 2011b). Unfortunately, in our opinion the optimisation
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
principles of the detection process for antioxidant profiling in complex samples using chromatographic method has not been clearly demonstrated. The main problem concerns the principles of optimisation of the detection process involving two key parameters: reaction temperature and mobile phase pH. Because such factors may strongly affect the quantitative results of antioxidant measurement during proposed post-column detection mode, it is important not to ignore them. In the application paper (Kusznierewicz et al., 2011a) the authors described the temperature resistance test, which was performed in the presence of mobile phase; however, this was carried out without derivatisation reagent. They conclude that brief exposure of the investigated analytes to high temperature in the reactor coil (130 8C) has almost no impact on the analytical signal recorded, in comparison to 30 8C conditions. It should be noted that this observation can be true only for analysis of thermally stable substances passing through the detection system working without a derivatisation reagent. Obviously, such temperature stability test cannot be convincing for the analytes passing through post-column detection system working with
given detection reagent and elevated temperature conditions. In particular, for the phytochemicals that were analysed by the authors, neither temperature and/nor pH parameters can be arbitrarily changed. In principle, food, medicine, tissue extracts or blood and plasma samples should be measured at temperatures and pH close to the real physiological conditions of the target organ, system or compartment (36 8C or at least room temperature; pH for e.g. plasma, skin or stomach gastric acid: = 7.2, 5.5 and 1.5–3.5, respectively). This allows comparison of the results with the values reported in the literature. In case of the above-mentioned samples, optimisation of both parameters just for the analytical signal improvement (especially by raising the derivatisation temperature above 100 8C) makes no sense for the interpretation of antioxidant properties of substances recorded as the chromatographic peaks. As can be seen from the data presented in Kusznierewicz’s papers, both pH and temperature strongly affect the peak areas of the substances chromatographed. Moreover, manipulation of temperature at elevated regions substantially changes the antioxidant peaks ratio. The consequence of this is that signal detection optimisation processes
b Peak Area at Temperature = 130oC [Arbitrary units]
Peak Area at Temperature = 130oC [Arbitrary units]
a 20000 16000
12000 8000 y = 1.1847x + 5999.4
4000
2
R = 0.2802
2000
1600 1200
800 y = 2.3589x + 337.28
400
2
R = 0.5216
0
0 0
4000
8000
0
12000
Peak Area at Temperature = 30oC [Arbitrary units]
100
200
300
400
Peak Area at Temperature = 30oC [Arbitrary units]
c
d Peak Area at Temperature = 130oC [Arbitrary units]
Peak Area at Temperature = 130oC [Arbitrary units]
217
8000
6000
4000
2000
y = 0.8809x - 629.34 2
R = 0.8789
0
30000
24000
18000
12000
y = 1.3313x + 3072.2 2
R = 0.8295
6000
0 0
2000
4000
6000
Peak Area at Temperature = 30oC [Arbitrary units]
8000
0
4000
8000
12000
16000
20000
Peak Area at Temperature = 30oC [Arbitrary units]
Fig. 1. (A–D) Comparison of antioxidant peak areas recorded under post-column derivatisation conditions carried out with ABTS (A) and FC (B) reagents as well as DPPH derivatisation using acidified (C) and non-acidified (D) mobile phases at 30 and 130 8C for selected phenolic compounds reported by Kusznierewicz et al. (the peak area values are based on the bars presented in Fig. 1, p. 394, Kusznierewicz et al., 2011b).
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
20000 13
Peak area [arbitrary units]
dramatically change the antioxidant activity values expressed as e.g. TEAC (Trolox equivalent antioxidant capacity) parameter. In other words, optimisation of antioxidant detection via pH and temperature can be interesting from theoretical point of view, but it is completely not relevant for antioxidant profiling in complex food, pharmaceutical or biological mixtures, in which pH and temperature must be set close to the living conditions of the target organism. This problem can be simply illustrated using data provided by the authors in the detection optimisation paper in Fig. 1, p. 394 (Kusznierewicz et al., 2011b). According to the graph presented in Fig. 1A, there is no correlation between peak areas of the investigated phenolic compounds that were analysed at different reaction temperatures 30 and 130 8C (post column derivatisation carried out with ABTS reagent). This can be explained, for example, by the limited stability of the ABTS reagent at high temperature conditions. On the other hand, such results may strongly suggest different reaction mechanisms at room and elevated temperature conditions. A similar correlation problem can be observed if we compare both temperatures for the remaining reagents including FCR (Fig. 1B) and DPPH assays for different pH conditions (Fig. 1C and D). Moreover, in case of Folin-Ciocalteu reaction (FCR), rational interpretation of the results may be really problematic due to the fact that the proposed detection protocol is based on a very short reaction time (just 1 min). In reality, the reaction between phenolic compounds and FC reagent is slow and stabilises around 0.5–2 h at room temperature. Obviously, the reaction time proposed by the authors is too short to achieve the stabilisation plateau (asymptote), and under such analytical setup the reaction time must be extremely precisely controlled. Additionally, a short reaction time may significantly affect (reduce) the final detection sensitivity. This may both increase the measurement uncertainty and strongly affect the method robustness. It should be noted that phenolic compounds react with FCR only under basic conditions (adjusted by a Na2CO3 solution to pH 10). The dissociation of a phenolic proton leads to a phenolate anion, which is capable of reducing FCR. Considering that the chromatographic separation of the phenolic compounds in Kusznierewicz et al. (2011a,b) was performed using a mobile phase containing formic acid (4.8% aq. formic acid, solvent A), the reaction between phenolic compounds and FRC happened under very different conditions from those where the phenolic compounds have the greater capacity to donate electrons. In particular, the optimised temperature is very high, which totally changes the capacity of phenolic compounds to reduce the FCR. It is noteworthy to say that relatively high correlations observed for data presented in graphs in Fig. 1C and D are due mainly to the non-symmetric distribution of the experimental data points across the X-axis. In both cases the values of determination coefficients drop dramatically, if the extreme points are eliminated from the initial data sets. This problem is well illustrated in the plots that are inserted within Fig. 1C and D graphs. Remarkably, the R2 value decreased from 0.83 to 0.27 for the data set involving DPPH reagent using non-acidified mobile phase. Such observation strongly supports our doubts that the proposed optimisation strategy is not appropriate for detection of target antioxidants, even based on different types of derivatisation reagents. Moreover, it is also a good example how highly correlated data set may turn into totally uncorrelated group by elimination of just one experimental data point. To illustrate that the reported method may generate misleading results, we compared the peak area values after post-column derivatisation at a temperature of 130 8C obtained for known standards by Kusznierewicz, derived from Fig. 1, p. 394 (Kusznierewicz et al., 2011b) and the TEAC values for these
(bKusznierewicz et al., 2011)
218
y = 2.4277x - 1.5374 2
R = 0.474
16000
12 10
12000 14
9 2
8000
7 3
8
1
4000
6
11
4 5
0 1
2
3 4 TEAC [mM] (Rice-Evans et al., 1996)
5
Fig. 2. Relationship between Trolox equivalent antioxidant activity values (X-axis) and peak areas after post-column derivatisation at temperature of 130 8C (Y-axis) for selected phenolic compounds reported by Rice-Evans et al. (1996, Table 3, p. 938) and Kusznierewicz et al. (2011b, Fig. 1, p. 394). Compared data sets reflect the ability of studied antioxidants to scavenge the ABTS radical. Antioxidant labels: (1) protocatechuic acid, (2) caffeic acid, (3) kaempferol, (4) apigenin, (5) naringenin, (6) ferulic acid, (7) luteolin, (8) rutin hydrate, (9) catechin hydrate, (10) epicatechin, (11) morin, (12) gallic acid, (13) myricetin, (14) cyanidin chloride.
compounds reported previously by Rice-Evans et al. (according to data listed in Table 3, p. 938, Rice-Evans et al., 1996). In both cases, these parameters reflect the ability of target molecules to scavenge the ABTS radical. As can be seen from the graph presented in Fig. 2, there is very weak correlation between data obtained using both methods. Additionally, within each data set the individual flavonoids are ordered in different ways according to their antioxidant activity. For example, based on data reported by Kusznierewicz, someone may conclude that epicatechin, gallic acid and myricetin are stronger antioxidants than cyanidin. It should be noted that, because of the relatively simple chemical structure of flavonoids, their free radical scavenging activity is usually predictive. In particular, it is well recognised that glycosylation of flavonoids reduces their activity compared to the corresponding aglycones (Rice-Evans et al., 1996). Therefore, the authors should justify and discuss the very unusual results that were generated under optimised detection conditions, in particular, the results reported for glycosidic form of cyanidine or flavonoids having catechol group in the B ring as well as carbonyl or hydroxyl groups in the C ring. 2. Conclusions The methodological problems that were discussed in this research communication may indicate that the proposed optimisation method described by Kusznierewicz and co-workers cannot be recommended as the rule of thumb for routine antioxidant profiling and fingerprinting in complex mixtures originating from plant or food samples. In principle, the separation and detection processes of antioxidant profiling assay must not significantly affect the antioxidant activity of target compounds. In case of foods eaten by humans or animals, the critical experimental parameters like pH and temperature concerning interaction of target analytes with derivatisation reagent should be as close as possible to the real physiological values. It is hoped that our comments will initiate fruitful discussion regarding new analytical protocols designed for fast and efficient quantification and fingerprinting of antioxidants from complex food, biological and environmental samples using high-throughput separation and detection systems.
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
Acknowledgements We would like to express many thanks to the anonymous referees for their questions and interesting comments, which significantly extended the manuscript text body as well as initiated critical and productive discussion within our group during preparation of the final version of this paper.
References Ding, X.P., Qi, J., Chang, Y.X., Mu, L.L., Zhu, D.N., Yu, B.Y., 2009. Quality control of flavonoids in Ginkgo biloba leaves by high-performance liquid chromatography with diode array detection and on-line radical scavenging activity detection. Journal of Chromatography A 1216, 2204–2210.
219
Gło´d, B.K., Piszcz, P., Beta, A., Zarzycki, P.K., 2012. Improved RP-HPLC, with fluorescence detection, assay for the determination of Total Antioxidant Potential (TAP). Journal of Liquid Chromatography & Related Technologies 35, 1194–1201. Gło´d, B.K., Piszcz, P., Czajka, J., Zarzycki, P.K., 2012. Evaluation of total antioxidant potential of selected biogenic polyamines, non-alcoholic drinks and alcoholic beverages using improved RP-HPLC assay involving fluorescence detection. Food Chemistry 131, 1029–1036. Kusznierewicz, B., Piasek, A., Bartoszek, A., Namies´nik, J., 2011. Application of a commercially available derivatization instrument and commonly used reagents to HPLC on-line determination of antioxidants. Journal of Food Composition and Analysis 24, 1073–1080. Kusznierewicz, B., Piasek, A., Bartoszek, A., Namiesnik, J., 2011. The optimisation of analytical parameters for routine profiling of antioxidants in complex mixtures by HPLC coupled post-column derivatisation. Phytochemical Analysis 22, 392–402. Rice-Evans, C.A., Miller, N.J., Paganga, G., 1996. Structure–antioxidant activity relationships of flavonoids and phenolic acids. Free Radical Biology & Medicine 20, 933–956.
Contents lists available at ScienceDirect
Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Commentary
Uncertainty of antioxidant profiling in complex mixtures using liquid chromatography involving post-column derivatisation§ Bronisław K. Gło´d a,d, Marian Kamin´ski b,d, Paweł K. Zarzycki c,d,* a
Department of Analytical Chemistry, Institute of Chemistry, Faculty of Science, Siedlce University of Natural Sciences and Humanities, 3 Maja 54, 08-110 Siedlce, Poland b Department of Chemical and Process Engineering, Chemical Faculty, Gdan´sk University of Technology, 11/12 Narutowicza St, 80-233 Gdan´sk, Poland c Section of Toxicology and Bioanalytics, Department of Civil and Environmental Engineering, Koszalin University of Technology, S´niadeckich 2, 75-453 Koszalin, Poland d Polish Society of the Separation Science, Poland
A R T I C L E I N F O
A B S T R A C T
Article history: Received 3 November 2012 Received in revised form 19 January 2013 Accepted 3 February 2013
The main goal of this paper is to discuss the problems associated with antioxidant profiling in complex samples using a high-throughput HPLC system coupled with post-column derivatisation reactor. Based on the experimental data reported in the literature, we demonstrated that improper optimisation of temperature and/or pH assay conditions performed using an on-line derivatisation reactor may substantially change the antioxidant peaks ratio of targeted phytochemical compounds. It has been found that despite the relatively high stability of flavonoids at high temperature and under binary mobile phase HPLC conditions, the reaction of target compounds with common ABTS, FCR and DPPH radicals at elevated regions (particularly above 100 8C) dramatically changes their antioxidant activity values expressed, for example, as TEAC (Trolox equivalent antioxidant capacity) parameters. In principle, separation and detection processes of antioxidant profiling assay must not significantly affect the antioxidant activity of target compounds. In the case of foods eaten by humans or animals, critical experimental parameters such as pH and temperature concerning interaction of target analytes with derivatisation reagent should be as close as possible to the real physiological values. ß 2013 Elsevier Inc. All rights reserved.
Keywords: Total antioxidant activity Antioxidant fingerprints Trolox equivalent antioxidant capacity Post-column derivatisation HPLC Temperature Food analysis Food composition Analytical method uncertainty
1. Problem overview and discussion A wide range of low-molecular mass compounds may act as direct radical scavengers or as agents capable of enhancing the resistance to oxidation of biologically active substances in medicinal, pharmaceutical, food, cosmetic and environmental materials. The chemical non-homogeneity of antioxidants, and their relatively low concentration in high organic load samples presents unique challenges for sample handling and analysis. Moreover, many antioxidants can interact with each other, in particular via redox reactions, increasing or decreasing synergetic
§ Editorial note: Journal of Food Composition and Analysis welcomes discussion from other researchers on this Commentary, and will be happy to publish pertinent comments in the area of analytical uncertainty in this particular field of food composition. * Corresponding author at: Section of Toxicology and Bioanalytics, Department of Civil and Environmental Engineering, Koszalin University of Technology, S´niadeckich 2, 75-453 Koszalin, Poland. Tel.: +48 94 3478671. E-mail addresses: [email protected], [email protected] (P.K. Zarzycki).
0889-1575/$ – see front matter ß 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jfca.2013.02.012
effects within a given matrix. Therefore, the choice of method for antioxidant profiling depends strongly on the required outcome. For example: total antioxidant potential (TAP) can be relatively easily determined using bulk spectrophotometric tests, without isolation of individual components from a particular sample. However, for the accurate measurement of antioxidant properties of individual compounds of interest in complex samples, a number of liquid-chromatography-based methods have been extensively studied and developed (Ding et al., 2009; Gło´d et al., 2012a,b). Recently, Kusznierewicz and co-authors reported a chromatographic protocol for the determination of antioxidants in complex samples involving coupled post-column derivatisation of target substances (Kusznierewicz et al., 2011a,b). In the method described by the authors, it is their intention that optimised separation and detection protocols appear to represent ‘‘a ready-to-use toolbox for the food and pharmaceutical industries, enabling the monitoring of bioactive substances along the production line and during storage, and the characterisation of plant material by creating chromatographic profiles supplemented with antioxidant fingerprints’’ (Kusznierewicz et al., 2011b). Unfortunately, in our opinion the optimisation
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
principles of the detection process for antioxidant profiling in complex samples using chromatographic method has not been clearly demonstrated. The main problem concerns the principles of optimisation of the detection process involving two key parameters: reaction temperature and mobile phase pH. Because such factors may strongly affect the quantitative results of antioxidant measurement during proposed post-column detection mode, it is important not to ignore them. In the application paper (Kusznierewicz et al., 2011a) the authors described the temperature resistance test, which was performed in the presence of mobile phase; however, this was carried out without derivatisation reagent. They conclude that brief exposure of the investigated analytes to high temperature in the reactor coil (130 8C) has almost no impact on the analytical signal recorded, in comparison to 30 8C conditions. It should be noted that this observation can be true only for analysis of thermally stable substances passing through the detection system working without a derivatisation reagent. Obviously, such temperature stability test cannot be convincing for the analytes passing through post-column detection system working with
given detection reagent and elevated temperature conditions. In particular, for the phytochemicals that were analysed by the authors, neither temperature and/nor pH parameters can be arbitrarily changed. In principle, food, medicine, tissue extracts or blood and plasma samples should be measured at temperatures and pH close to the real physiological conditions of the target organ, system or compartment (36 8C or at least room temperature; pH for e.g. plasma, skin or stomach gastric acid: = 7.2, 5.5 and 1.5–3.5, respectively). This allows comparison of the results with the values reported in the literature. In case of the above-mentioned samples, optimisation of both parameters just for the analytical signal improvement (especially by raising the derivatisation temperature above 100 8C) makes no sense for the interpretation of antioxidant properties of substances recorded as the chromatographic peaks. As can be seen from the data presented in Kusznierewicz’s papers, both pH and temperature strongly affect the peak areas of the substances chromatographed. Moreover, manipulation of temperature at elevated regions substantially changes the antioxidant peaks ratio. The consequence of this is that signal detection optimisation processes
b Peak Area at Temperature = 130oC [Arbitrary units]
Peak Area at Temperature = 130oC [Arbitrary units]
a 20000 16000
12000 8000 y = 1.1847x + 5999.4
4000
2
R = 0.2802
2000
1600 1200
800 y = 2.3589x + 337.28
400
2
R = 0.5216
0
0 0
4000
8000
0
12000
Peak Area at Temperature = 30oC [Arbitrary units]
100
200
300
400
Peak Area at Temperature = 30oC [Arbitrary units]
c
d Peak Area at Temperature = 130oC [Arbitrary units]
Peak Area at Temperature = 130oC [Arbitrary units]
217
8000
6000
4000
2000
y = 0.8809x - 629.34 2
R = 0.8789
0
30000
24000
18000
12000
y = 1.3313x + 3072.2 2
R = 0.8295
6000
0 0
2000
4000
6000
Peak Area at Temperature = 30oC [Arbitrary units]
8000
0
4000
8000
12000
16000
20000
Peak Area at Temperature = 30oC [Arbitrary units]
Fig. 1. (A–D) Comparison of antioxidant peak areas recorded under post-column derivatisation conditions carried out with ABTS (A) and FC (B) reagents as well as DPPH derivatisation using acidified (C) and non-acidified (D) mobile phases at 30 and 130 8C for selected phenolic compounds reported by Kusznierewicz et al. (the peak area values are based on the bars presented in Fig. 1, p. 394, Kusznierewicz et al., 2011b).
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
20000 13
Peak area [arbitrary units]
dramatically change the antioxidant activity values expressed as e.g. TEAC (Trolox equivalent antioxidant capacity) parameter. In other words, optimisation of antioxidant detection via pH and temperature can be interesting from theoretical point of view, but it is completely not relevant for antioxidant profiling in complex food, pharmaceutical or biological mixtures, in which pH and temperature must be set close to the living conditions of the target organism. This problem can be simply illustrated using data provided by the authors in the detection optimisation paper in Fig. 1, p. 394 (Kusznierewicz et al., 2011b). According to the graph presented in Fig. 1A, there is no correlation between peak areas of the investigated phenolic compounds that were analysed at different reaction temperatures 30 and 130 8C (post column derivatisation carried out with ABTS reagent). This can be explained, for example, by the limited stability of the ABTS reagent at high temperature conditions. On the other hand, such results may strongly suggest different reaction mechanisms at room and elevated temperature conditions. A similar correlation problem can be observed if we compare both temperatures for the remaining reagents including FCR (Fig. 1B) and DPPH assays for different pH conditions (Fig. 1C and D). Moreover, in case of Folin-Ciocalteu reaction (FCR), rational interpretation of the results may be really problematic due to the fact that the proposed detection protocol is based on a very short reaction time (just 1 min). In reality, the reaction between phenolic compounds and FC reagent is slow and stabilises around 0.5–2 h at room temperature. Obviously, the reaction time proposed by the authors is too short to achieve the stabilisation plateau (asymptote), and under such analytical setup the reaction time must be extremely precisely controlled. Additionally, a short reaction time may significantly affect (reduce) the final detection sensitivity. This may both increase the measurement uncertainty and strongly affect the method robustness. It should be noted that phenolic compounds react with FCR only under basic conditions (adjusted by a Na2CO3 solution to pH 10). The dissociation of a phenolic proton leads to a phenolate anion, which is capable of reducing FCR. Considering that the chromatographic separation of the phenolic compounds in Kusznierewicz et al. (2011a,b) was performed using a mobile phase containing formic acid (4.8% aq. formic acid, solvent A), the reaction between phenolic compounds and FRC happened under very different conditions from those where the phenolic compounds have the greater capacity to donate electrons. In particular, the optimised temperature is very high, which totally changes the capacity of phenolic compounds to reduce the FCR. It is noteworthy to say that relatively high correlations observed for data presented in graphs in Fig. 1C and D are due mainly to the non-symmetric distribution of the experimental data points across the X-axis. In both cases the values of determination coefficients drop dramatically, if the extreme points are eliminated from the initial data sets. This problem is well illustrated in the plots that are inserted within Fig. 1C and D graphs. Remarkably, the R2 value decreased from 0.83 to 0.27 for the data set involving DPPH reagent using non-acidified mobile phase. Such observation strongly supports our doubts that the proposed optimisation strategy is not appropriate for detection of target antioxidants, even based on different types of derivatisation reagents. Moreover, it is also a good example how highly correlated data set may turn into totally uncorrelated group by elimination of just one experimental data point. To illustrate that the reported method may generate misleading results, we compared the peak area values after post-column derivatisation at a temperature of 130 8C obtained for known standards by Kusznierewicz, derived from Fig. 1, p. 394 (Kusznierewicz et al., 2011b) and the TEAC values for these
(bKusznierewicz et al., 2011)
218
y = 2.4277x - 1.5374 2
R = 0.474
16000
12 10
12000 14
9 2
8000
7 3
8
1
4000
6
11
4 5
0 1
2
3 4 TEAC [mM] (Rice-Evans et al., 1996)
5
Fig. 2. Relationship between Trolox equivalent antioxidant activity values (X-axis) and peak areas after post-column derivatisation at temperature of 130 8C (Y-axis) for selected phenolic compounds reported by Rice-Evans et al. (1996, Table 3, p. 938) and Kusznierewicz et al. (2011b, Fig. 1, p. 394). Compared data sets reflect the ability of studied antioxidants to scavenge the ABTS radical. Antioxidant labels: (1) protocatechuic acid, (2) caffeic acid, (3) kaempferol, (4) apigenin, (5) naringenin, (6) ferulic acid, (7) luteolin, (8) rutin hydrate, (9) catechin hydrate, (10) epicatechin, (11) morin, (12) gallic acid, (13) myricetin, (14) cyanidin chloride.
compounds reported previously by Rice-Evans et al. (according to data listed in Table 3, p. 938, Rice-Evans et al., 1996). In both cases, these parameters reflect the ability of target molecules to scavenge the ABTS radical. As can be seen from the graph presented in Fig. 2, there is very weak correlation between data obtained using both methods. Additionally, within each data set the individual flavonoids are ordered in different ways according to their antioxidant activity. For example, based on data reported by Kusznierewicz, someone may conclude that epicatechin, gallic acid and myricetin are stronger antioxidants than cyanidin. It should be noted that, because of the relatively simple chemical structure of flavonoids, their free radical scavenging activity is usually predictive. In particular, it is well recognised that glycosylation of flavonoids reduces their activity compared to the corresponding aglycones (Rice-Evans et al., 1996). Therefore, the authors should justify and discuss the very unusual results that were generated under optimised detection conditions, in particular, the results reported for glycosidic form of cyanidine or flavonoids having catechol group in the B ring as well as carbonyl or hydroxyl groups in the C ring. 2. Conclusions The methodological problems that were discussed in this research communication may indicate that the proposed optimisation method described by Kusznierewicz and co-workers cannot be recommended as the rule of thumb for routine antioxidant profiling and fingerprinting in complex mixtures originating from plant or food samples. In principle, the separation and detection processes of antioxidant profiling assay must not significantly affect the antioxidant activity of target compounds. In case of foods eaten by humans or animals, the critical experimental parameters like pH and temperature concerning interaction of target analytes with derivatisation reagent should be as close as possible to the real physiological values. It is hoped that our comments will initiate fruitful discussion regarding new analytical protocols designed for fast and efficient quantification and fingerprinting of antioxidants from complex food, biological and environmental samples using high-throughput separation and detection systems.
B.K. Gło´d et al. / Journal of Food Composition and Analysis 33 (2014) 216–219
Acknowledgements We would like to express many thanks to the anonymous referees for their questions and interesting comments, which significantly extended the manuscript text body as well as initiated critical and productive discussion within our group during preparation of the final version of this paper.
References Ding, X.P., Qi, J., Chang, Y.X., Mu, L.L., Zhu, D.N., Yu, B.Y., 2009. Quality control of flavonoids in Ginkgo biloba leaves by high-performance liquid chromatography with diode array detection and on-line radical scavenging activity detection. Journal of Chromatography A 1216, 2204–2210.
219
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