{Determination of free phenolic acids from leaves within different colored maize} J. Serb. Chem. Soc. 82 (1) 63–72 (2017) UDC 633.15:635.074:547.562+543.544.5.068.7+ JSCS–4947 621.383.5 Original scientific paper Determination of free phenolic acids from leaves within different colored maize JELENA Z. MESAROVIĆ*, VESNA D. DRAGIČEVIĆ, SNEŽANA D. MLADENOVIĆ DRINIĆ, DANIJELA S. RISTIĆ and NATALIJA B. KRAVIĆ Maize Research Institute Zemun Polje, Slobodana Bajića 1, 11185 Belgrade, Serbia (Received 12 May, revised 22 November, accepted 29 November 2016) Abstract: Along with other plant parts, maize leaves are widely used for making fermented food for cattle, known as silage. Since there have only been a few reports on studies concerning the extraction and determination of phen- olic acids from maize leaves, the main goal of this investigation was to eva- luate the content of free phenolic acids in the leaves of fifteen different maize inbred lines. Reverse-phase, high performance liquid chromatography (RP- -HPLC), with a photodiode array detector (DAD), was performed. Under the optimized chromatographic conditions, referring to short time of sample pre- paration, small quantities of solvent and direct injection of the extract into HPLC, phenolic acids (i.e., gallic, protocatechuic, caffeic, p-coumaric and fer- ulic acid) were successfully separated in less than 25 min, indicating that the method could be applied for routine analysis. The efficiency and validation of the method was evaluated by measuring the rate parameters: linearity, limit of detection and quantification, accuracy and precision. The obtained results showed that the most abundant free phenolic acid was p-coumaric acid (23.57 µg g-1 dry weight), followed by ferulic and caffeic acids (21.27 and 20.78 µg g-1 dry weight, respectively). Principal Component Analysis (PCA) revealed the existence of a link. Keywords: HPLC-DAD; method validation; phenolic acids; corn. INTRODUCTION Maize (Zea mays L.) is one of the oldest cultivated grain cereals and one of the most productive species worldwide, with an average yield of about 5.5 t ha–1.1 Maize has food, feed, and industrial uses. Namely, a high proportion of the produced maize is used in livestock feed as green chop, dry forage, silage or grain.2,3 In addition, differently processed and unprocessed maize grain is used in human diet.4 The rest of the plant is mostly used for the preparation of fermented * Corresponding author. E-mail: jmesarovic@mrizp.rs doi: 10.2298/JSC160512104M 64 MESAROVIĆ et al. high-moisture preserved food used in livestock feed (silage) or is discarded wherein a potentially valuable source of phytochemicals is lost. Besides providing functional dietary micronutrients and fibers, plants are rich sources of phytochemicals, such as phenolic compounds. These are aromatic secondary plant metabolites that include a large number of naturally occurring compounds divided into several groups. Due to their antioxidant and other bio- logical properties that can promote human health, phenolic compounds in food have been constantly investigated over the past few years.5 In many studies the inhibitory effect of phenolics to oxidative damage, which could lead to athero- sclerosis and cancer, were reported.6–8 The antioxidant activity of phenolic com- pounds can be explained by several possible mechanisms, such as their ability to chelate metals, inhibit lipoxygenase, modulate peroxide concentration, scavenge free radicals and stimulate the enzyme systems of antioxidative defense.9 Due to harmful properties of synthetic antioxidants, such as butylated hydroxyanisole (BHA) and hydroxytoluene (BHT),10 demands of the food industry for antioxid- ants of natural origin, especially from industrial residues, have never been greater.11–13 Phenolic acids are one of the main classes of phenolics and, according to their chemical structure, represent derivatives of benzoic and cinnamic acids. Generally, they could be described as phenols with carboxylic acid and hydroxyl groups, the positions of which affects their antioxidative properties.14 Phenolic acids in different concentrations are distributed in seeds, leaves, roots and stems.15 Their functions in the plant are linked with photosynthesis, synthesis of proteins, enzyme activity and allelopathy.16 Various factors affect the quantity and quality of the phenolic acids present in plant foods, including plant genetics, soil composition and growing conditions, maturity state and post-harvest conditions.17,18 Many studies have reported the extraction of phenolic acids from the leaves of different plant species,19–21 but only a few from maize leaves.22 According to all the findings mentioned above, the aim of this study was to evaluate the content of free phenolic acids extracted from maize leaves. For this purpose, a new reverse phase HPLC method with diode array detection was dev- eloped for identification and quantification of five phenolic acids. The method was performed on fifteen maize inbred lines. In addition, principal component analysis (PCA) was performed to determine the relationship between compo- sitions of the free phenolic acids in the leaves and the color of the maize kernel. EXPERIMENTAL Plant material and chemicals In this study, fifteen maize inbred lines (from IL1 to IL15) from the gene bank of the Maize Research Institute “Zemun Polje”, Belgrade, Serbia, were used for the analysis. For each genotype (nine white, four orange and two red maize inbred lines), plant samples (i.e., leaf of the uppermost ear) were taken at flowering. Leaves were dried to constant weight at 60 HPLC/DAD DETERMINATION OF PHENOLIC ACIDS FROM MAIZE LEAVES 65 °C, milled (Perten 120, Sweden) into powder (particle size <500 μm) in order to obtain greater surface contact,23 and stored at –20 °C prior to analysis. Methanol and formic acid, purchased from J.T. Baker (Netherlands), were of HPLC grade. Ethanol and standards of tested phenolic acids (i.e., gallic, protocatechuic, caffeic, p-coumaric and ferulic) were HPLC grade and purchased from Sigma–Aldrich. For the analysis, ultrapure water (Thermo Fisher TKA Micro Pure water purification system, 0.055 µS cm-1) was used. Syringe filters (17 mm, PTFE membrane 0.45 µm) were purchased from Thermo Scientific (Germany). Samples preparation and extraction of free phenolic acids The method used for phenolic acids extraction was a slightly modified method proposed by Sultana et al.24 Approximately 0.3 g of the leaves powder was extracted (IKA HS 501, Germany) twice with 3 mL of 80 % methanol, for 30 min at 300 rpm, at room temperature. The collected extracts were centrifuged at 3000 rpm for 5 min, filtered through a 0.45-μm PTFE membrane filter and directly injected into the HPLC. Calibration curve and linearity Working solutions were made by diluting the initial mixture containing all analyzed phenolic acids (100 µg mL-1) to the final concentration: 0.1, 0.3, 0.5, 1, 3, 5, 10 and 20 µg mL-1. Calibration curves were obtained in MS Excel, by plotting the peak areas (detector response) versus the concentration of the standard solutions. Obtained correlation coefficients were used for determination of the linearity of the method. Limit of detection and quantification Limit of detection (LOD) and limit of quantification (LOQ) were calculated from the following equations: 3 SD LOD b = (1) 10 SD LOQ b = (2) where SD is the standard deviation of the response (standard error value for coefficient b) and b is the slope of the calibration curve obtained from the linear regression. Precision and accuracy The repeatability of the method was determined by triplicate measurement of the relative standard deviation (RSD) of both the peak area for each phenolic compound (at a concen- tration of 1.0 µg mL-1), and two randomly chosen samples, on an intra- and inter-daily basis. For the calculation, the following equation was used: / % 100 SD RSD X = (3) where SD is standard error value for the peak area and X is the average value of the peak area. The accuracy of the method was express as percentage of recovery. Two samples were spiked with the working solution of the phenolic acids mixture (at a concentration of 1 µg mL-1), in three replicates. Recovery (R / %) was determined from the equation: 0 / % 100 F R F A = + (4) 66 MESAROVIĆ et al. where F represents the concentration of phenolic acid in the spiked sample, F0 is the concen- tration of phenolic acid in the unspiked sample and A is the added amount of phenolic acid (i.e., 1.0 µg mL-1). HPLC method Chromatographic separation of five phenolic acids was performed using a Dionex UltiMate 3000 liquid chromatography system (Thermo Scientific, Germany), consisting of a quaternary pump (LPG-3400), autosampler (WPS-300SL), column compartment (TCC- -300SD) and a photodiode array detector (DAD−3000). The analytical column used was Acclaim Polar Advantage II, C18 (150 mm× 4.6 mm, 3 μm) from Thermo Fisher Scientific, operated at 25 °C. The mobile phase (flow rate 0.8 mL min-1) contained 0.1 vol. % aqueous formic acid solution (A) and pure methanol (B). The linear gradient program was as follows: 0.0−10.0 min, 15−45 % B; 10.0−20.0 min, 45−65 % B; 20.0−25.0 min, 65−15 % B. The injection volume was 5 μL. The UV detection wavelengths were set at 278, 280, 290 and 300 nm. Phenolic acids were identified according to characteristic retention time and absorption spectra, whilst calibration curves of the corresponding standards were used for quantitative calculations. Chromeleon software package (version 7.2) was used for instrument control, as well as for data acquisition and analysis. The contents of the phenolic acids are expressed as μg per g of dry weight (DW). Data are reported as the mean value of three independent injections. Statistical analysis All analyses were performed on triplicate measurements (n = 3) and the results are pre- sented as mean values. The data were subjected to one-way analysis of variance (ANOVA). The F-test was used for comparison of the means at the 0.05 probability level. Principal component analysis (PCA) was performed using the PLS Toolbox software package v.6.2.1, for MATLAB 7.12.0 (R2011a). To prevent the predominance of components existing in higher concentrations, compared to those present in lower concentrations, data were mean-centered and auto-scaled to unit variance before statistical processing. The sin- gular value decomposition (SVD) algorithm was used at the 0.95 confidence level for Hotel- ling T2 limits. RESULTS AND DISCUSSION Extraction of free phenolic acids Determination of extraction efficiency was performed using pure methanol, pure ethanol and mixtures of methanol–water and ethanol–water (both in volume ratio of 8:2, data not shown). The mixture of methanol–water exhibited the highest extraction efficiency, which is in agreement with the results of Shabir et al.,25 and was used for further analysis. Validation of the method The applied chromatographic method encompassed separation of all tested phenolic acids with good resolution, with a total separation time of 25 min. Chro- matograms of phenolic acids standards are shown in Figs. 1a and b, recorded at 278 and 300 nm, respectively. The chromatograms obtained from maize leaves, also recorded at 278 and 300 nm, are presented in Fig. 2a and b, respectively. HPLC/DAD DETERMINATION OF PHENOLIC ACIDS FROM MAIZE LEAVES 67 Fig. 1. Chromatograms of the phenolic acid standards, recorded at 278 nm (a) and 300 nm (b). Fig. 2. Chromatograms for phenolic acids from maize leaves, recorded at 278 nm (a) and 300 nm (b). According to obtained maximum absorbance, the wavelength for protocate- chuic acid (PA) and p-coumaric acid (p-CoumA) was set at 300 nm, for ferulic acid (FA) and caffeic acid (CA) at 290 nm and for gallic acid (GA) at 278 nm. These values of wavelengths are in line with those used in the study of Nour et al.,26 but different to those used by Lee et al.27 and Kovacova et al.,28 when all phenolic acids were monitored at 280 nm. Although recorded at 278 nm (Fig. 2a), the peak of gallic acid had dim- inished absorbance at 300 nm, as is shown in Fig. 2b. This was also confirmed in Fig. 1a and b, obtained from phenolic standards chromatograms. Retention time for GA, PA, CA, p-CoumA and FA were 6.78, 10.35, 14.51, 16.46 and 18.19 min, respectively. 68 MESAROVIĆ et al. The parameters of linear regression (i.e., slope, intercept, coefficient of det- ermination (r2), LOD and LOQ), were obtained for the phenolic acids standards, based on their peak area, as presented in Table I. The obtained linear correlation coefficients for all standards were not lower than 0.997, indicating good linearity of the method. The obtained LOD values ranged from 16 to 52 ng mL–1 and those of LOQ from 54 to 173 ng mL–1. The obtained values were lower to those reported in method proposed by Nour et al.,26 indicating higher sensitivity of the method used in this study. TABLE I. Parameters of linear regression, LOD and LOQ for the phenolic acid standards Phenolic acid Intercept Slope r2 LOD / ng mL-1 LOQ / ng mL-1 GA –0.1180 0.3344 0.999 27 90 PA –0.0495 0.3426 0.999 32 107 CA –0.1424 0.7078 0.997 52 173 p-CoumA –0.0133 1.0225 0.999 29 97 FA –0.1181 2.0032 1.000 16 54 The repeatability of the method was investigated using intra-day and inter- -day data obtained from the standards and two samples (Table II). For standards, the RSD of the intra-day (n = 5) and inter-day (n = 3) analysis were 0.17–1.19 and 0.81–2.42 %, respectively. For sample I, the RSD of the intra-day (n = 5) analysis was 0.21–1.41 %, being 1.13–3.05 % for the inter-day (n = 3) analysis. For sample II, the RSD of the intra-day (n = 5) analysis was 0.32–1.18 %, being 1.69–2.93 % for the inter-day (n = 3) analysis. TABLE II. The obtained RSD (%) for the phenolic acids and the tested samples Phenolic acid Standard Sample I Sample II Intra-day Inter-day Intra-day Inter-day Intra-day Inter-day GA 0.2 0.8 0.2 1.1 0.3 1.7 PA 1.2 2.4 0.7 1.9 0.6 2.1 CA 0.4 1.7 0.9 3.0 1.2 1.9 p-CoumA 0.9 2.0 1.0 2.5 0.8 2.9 FA 0.7 1.5 1.4 2.4 1.0 1.8 The standard additional method was used for recovery (R) determination, which represents the accuracy of the method. R for GA, PA, CA, p-CoumA and FA were 100.5, 97.8, 102.4, 99.7 and 98.9 %, respectively, indicating the good accuracy of the preformed method. Free phenolic acids contents in relation to the maize kernel color The content of free phenolic acids in the leaves for each of the fifteen eva- luated maize inbreds, as a well as total average values per parameter, are pre- HPLC/DAD DETERMINATION OF PHENOLIC ACIDS FROM MAIZE LEAVES 69 sented in Table III. The obtained results indicate that the most abundant evaluated free phenolic acid was p-coumaric acid, followed by ferulic and caffeic acids. TABLE III. Obtained content of phenolic acids in the tested maize leaves Sample Maize kernel color GA µg g -1 PA µg g -1 CA µg g -1 p-CoumA µg g -1 FA µg g -1 IL1 White 10.3014 7.1970 34.8993 21.8526 20.4395 IL2 White 10.2993 5.5556 24.7301 21.0614 18.1406 IL3 White 9.1026 7.0338 15.1407 18.0995 21.7998 IL4 White 9.5499 7.0916 22.5808 16.2327 23.0608 IL5 White 10.3803 11.4546 17.4689 23.5272 24.9282 IL6 White 10.4429 9.8031 25.9565 21.3246 17.0967 IL7 White 12.298 11.228 31.8369 17.2297 9.9062 IL8 White 10.8847 6.3156 22.7485 19.0469 13.1095 IL9 White 8.6345 8.5403 19.5884 15.6033 9.7336 Averagea 10.1412 8.2466 23.8833 19.3309 17.5794 IL10 Orange 15.3776 22.0641 4.7345 18.2032 12.7739 IL11 Orange 14.1058 18.2494 27.705 28.665 28.9746 IL12 Orange 13.6257 19.7144 19.1517 35.3965 28.5013 IL13 Orange 13.2097 15.0719 17.8619 15.977 16.611 Averagea 14.0797 18.775 17.3633 24.5604 21.7152 IL14 Red 9.0262 7.7717 20.9281 43.1607 29.5398 IL15 Red 9.1026 12.9652 6.4191 38.1813 44.4828 Averagea 9.0644 10.3685 13.6736 40.671 37.0113 Total average 11.0479 11.3371 20.7834 23.5708 21.2732 aAverage phenolic acids content of leaves Total average values for GA, CA and FA contents obtained from all tested fifteen genotypes (i.e. 11.05, 20.78 and 21.27 µg g–1 DW, respectively), were shown to be higher than those in study on cob leaves (10.99, 6.0 and 1.87 µg g–1 DW, respectively), reported by Pandey et al.22 Average amounts of p-CoumA, FA and CA (i.e., 23.57, 21.27 and 20.78 µg g–1 DW, respectively), obtained from all analyzed genotypes, was higher than those in commercial red wine.29 Mean values for PA and GA contents (i.e., 11.34 and 11.05 µg g–1 DW, respectively) obtained from leaves of all tested maize, was lower compared to leaf extracts of Gold Mohar (Delonix regia (Bojer ex Hook.) Raf.), having antimicrobial and antifungal properties and being widely used in folk medicine.25 On the contrary, the average contents of the other phenolic acids (i.e., p-CoumA, GA and FA) were higher.25 Different kernel color in maize generally originates from the carotenoids and anthocyanins concentration, with positive correlations found between the antiox- idant activity and the color of maize.30–32 Similar studies showed that the color of the samples is also related to the content of phenolic acids.33,34 In this context, PCA was performed in order to examine the possible relationship between the 70 MESAROVIĆ et al. content of free phenolic acids in the leaves and the color of the maize kernel. PC analysis resulted in a four-component model that explains 98.93 % of the total variance. The first two principal components explain 42.80 (for PC1) and 36.23 % (for PC2) of the overall data variance. Mutual projections of the factor scores and their loadings for these PCs are shown in Fig. 3a and b, respectively. Fig. 3. PCA score (a) and loading plots (b). Considering PC1 and PC2 score values (Fig. 3a), three well-separated groups of samples (according to kernel color) were formed. This indicates that the leaves from different colored maize possibly have unique contents of phen- olic acids. White kernel maize (IL1–IL9) formed a group in the plot center, while the group of orange kernel maize (IL10–IL13) was allocated in the upper right part of the plot. Red kernel maize (IL14 and IL15) were separated in the lower right part of plot. The loading plot (Fig. 3b) revealed that the most efficient parameters for distinguishing white kernel maize was CA, for orange maize GA and PA, while for red kernel maize FA and p-CoumA. These results are in agree- ment with the mean values for phenolic acids obtained in the leaves from differ- ent colored maize (Table III). Leaves from white kernel maize had the highest average content of CA (i.e., 23.88 µg g–1 DW) compared to the leaves from orange and red maize (i.e., 17.36 and 13.67 µg g–1 DW, respectively). Similarly, the leaves from the orange kernel maize showed the largest average content of GA and PA (i.e., 14.08 and 18.77 µg g–1 DW, respectively), compared to the leaves of white and red maize. Moreover, leaves of the red kernel maize had the highest average concentration of p-CoumA and FA (40.67 and 37.01 µg g–1 DW, respectively), compared to the leaves from other colored maize. Among the phenolic acids evaluated, the highest value for FA was found in red wheat, as was reported by Ma et al.34 HPLC/DAD DETERMINATION OF PHENOLIC ACIDS FROM MAIZE LEAVES 71 CONCLUSIONS A new RP-HPLC method with DAD was developed for the quantification of five phenolic acids in maize leaves, due to the lack of information on this subject. The observed validation parameters confirmed that the performed method is of good accuracy and precision, with relatively low values for the LOD and LOQ. This indicates that the method developed in this study could be usefully applied in further, more detailed analyses on phenolic acids content in maize leaves. The performed PCA distinguished a relationship between the concentrations of phenolic acids in the leaves and the color of the maize kernel. In leaves, the most abundant phenolic acid was CA for white maize, and GA and PA for orange maize. Moreover, the leaves from red maize showed the highest concentrations of FA and p-CoumA. Acknowledgement. This research was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Projects TR31068 and TR31028). И З В О Д ОДРЕЂИВАЊЕ СЛОБОДНИХ ФЕНОЛНИХ КИСЕЛИНА У ЛИСТУ КУКУРУЗА РАЗЛИЧИТО ОБОЈЕНОГ ЗРНА ЈЕЛЕНА З. МЕСАРОВИЋ, ВЕСНА Д. ДРАГИЧЕВИЋ, СНЕЖАНА Д. МЛАДЕНОВИЋ ДРИНИЋ, ДАНИЈЕЛА С. РИСТИЋ и НАТАЛИЈА Б. КРАВИЋ Институт за кукуруз Земун Поље, Слободана Бајића 1, 11185 Београд Лист кукуруза, заједно са другим деловима биљака, доста се користи у производњи ферментисане хране за стоку, познате као силажа. С обзиром на то да је само неколико студија објављено на тему изоловања и квантификације фенолних киселина из листова кукуруза, главни циљ овог рада је одређивање садржаја слободних фенолних киселина у листовима петнаест различитих самооплодних линија кукуруза. Коришћена је реверсно- -фазна високо ефикасна течна хроматографија са DAD детектором. Под оптимизованим хроматографским условима, као што су кратко време припреме узорака, мале количине растварача и директно инјектовање екстракта узорка, фенолне киселине (тј. гална, про- токатехинска, кафеинска, p-кумаринска и ферулинска киселина) успешно су раздвојене за мање од 25 min, што указује на могућу примену методе у рутинским анализама. Ефи- касност и валидација методе су процењенe мерењем параметара као што су: линеарност, граница детекције и квантификације, тачност и прецизност. Добијени резултати указују да је најзаступљенија слободна фенолна киселина p-кумаринска киселина (23,57 μg g-1 суве масе), праћена ферулинском и кафеинскoм киселином (21,27 и 20,78 μg g-1 суве масе, редом). Анализом главних компонената (PCA) процењен је однос садржаја слобод- них фенолних киселина у листу и боје зрна кукуруза. (Примљено 12. маја, ревидирано 22. новембра, прихваћено 29. новембра 2016) REFERENCES 1. FAOSTAT (2014), http://faostat3.fao.org/browse/Q/QC/E 2. R. A. Hallauer, Specialty Corns; CRC Press, Boca Raton, USA, 2001, p. 303 3. C. W. Smith, J. Betran, E. C. A. Runge, Corn: Origin, History, Technology and Pro- duction, Wiley, Hoboken, NJ, 2004, p. 802 4. T. E. Nuss, A. S. Tanumihardjo, Compr. Rev. Food. Sci. Food. Saf. 9 (2010) 417 72 MESAROVIĆ et al. 5. A. J. Parr, G. P. Bolwell, J. Sci. Food Agric. 80 (2000) 985 6. J. W. 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Guo, Front Plant Sci. 7 (2016) 528. << /ASCII85EncodePages false /AllowTransparency false /AutoPositionEPSFiles true /AutoRotatePages /None /Binding /Left /CalGrayProfile (Dot Gain 20%) /CalRGBProfile (sRGB IEC61966-2.1) /CalCMYKProfile (U.S. Web Coated \050SWOP\051 v2) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Error /CompatibilityLevel 1.4 /CompressObjects /Tags /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages true /CreateJobTicket false /DefaultRenderingIntent /Default /DetectBlends true /DetectCurves 0.0000 /ColorConversionStrategy /CMYK /DoThumbnails false /EmbedAllFonts true /EmbedOpenType false /ParseICCProfilesInComments true /EmbedJobOptions true /DSCReportingLevel 0 /EmitDSCWarnings false /EndPage -1 /ImageMemory 1048576 /LockDistillerParams false /MaxSubsetPct 100 /Optimize true /OPM 1 /ParseDSCComments true /ParseDSCCommentsForDocInfo true /PreserveCopyPage true /PreserveDICMYKValues true /PreserveEPSInfo true /PreserveFlatness true /PreserveHalftoneInfo false /PreserveOPIComments true /PreserveOverprintSettings true /StartPage 1 /SubsetFonts true /TransferFunctionInfo /Apply /UCRandBGInfo /Preserve /UsePrologue false /ColorSettingsFile () /AlwaysEmbed [ true ] /NeverEmbed [ true ] /AntiAliasColorImages false /CropColorImages true /ColorImageMinResolution 300 /ColorImageMinResolutionPolicy /OK /DownsampleColorImages true /ColorImageDownsampleType /Bicubic /ColorImageResolution 300 /ColorImageDepth -1 /ColorImageMinDownsampleDepth 1 /ColorImageDownsampleThreshold 1.50000 /EncodeColorImages true /ColorImageFilter /DCTEncode /AutoFilterColorImages true /ColorImageAutoFilterStrategy /JPEG /ColorACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 300 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 300 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.50000 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages true /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000GrayImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasMonoImages false /CropMonoImages true /MonoImageMinResolution 1200 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 1200 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.50000 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict << /K -1 >> /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile () /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False /CreateJDFFile false /Description << /ARA /BGR /CHS /CHT /CZE /DAN /DEU /ESP /ETI /FRA /GRE /HEB /HRV (Za stvaranje Adobe PDF dokumenata najpogodnijih za visokokvalitetni ispis prije tiskanja koristite ove postavke. 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