Osloveien 1, Aas, N-1430, Norway b Department of Plant and Environmental Sciences, Norwegian University of Life

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1 This article was downloaded by: [Nofima] On: 07 October 2011, At: 01:03 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Acta Agriculturae Scandinavica, Section B - Soil & Plant Science Publication details, including instructions for authors and subscription information: Variation in quality parameters between and within 14 Nordic tree fruit and berry species Grete Skrede a, Berit Karoline Martinsen a, Anne-Berit Wold b, Stein-Erik Birkeland c & Kjersti Aaby a a Nofima AS - The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, Aas, N-1430, Norway b Department of Plant and Environmental Sciences, Norwegian University of Life Sciences, P.O. Box 5003, N-1432, Aas, Norway c TINE SA, TINE R&D Center, P.O. Box 7, Oslo, N-0902, Kalbakken, Norway Available online: 01 Aug 2011 To cite this article: Grete Skrede, Berit Karoline Martinsen, Anne-Berit Wold, Stein-Erik Birkeland & Kjersti Aaby (2011): Variation in quality parameters between and within 14 Nordic tree fruit and berry species, Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, DOI: / To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

2 Acta Agriculturae Scandinavica Section B Soil and Plant Science 2011, 116, ifirst article Variation in quality parameters between and within 14 Nordic tree fruit and berry species GRETE SKREDE 1, BERIT KAROLINE MARTINSEN 1, ANNE-BERIT WOLD 2, STEIN-ERIK BIRKELAND 3 & KJERSTI AABY 1 1 Nofima AS - The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, N-1430 Aas, Norway, 2 Department of Plant and Environmental Sciences, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Aas, Norway, 3 TINE SA, TINE R&D Center, P.O. Box 7, Kalbakken, N-0902 Oslo, Norway Abstract A 3-year study was carried out to investigate quality parameters in 14 tree fruit and berry species grown in southern Norway. The species were blueberry, apple, aronia, sour cherry, sweet cherry, red raspberry, strawberry, blackcurrant, gooseberry, red currant and elderberry, harvested along with wild bilberry, cloudberry and lingonberry. Significant differences between species were identified for all quality parameters. The coefficient of variation between species was lowest for ph (12.5%), dry matter (18.9%) and soluble solids (25.3%), followed by titratable acids (59.3%), total phenolics (83.8%), antioxidant capacity FRAP (85.7%) and antiradical power by the DPPH-assay (97.8%), total monomeric anthocyanins (132%) and ascorbic acid (137%). Average coefficient of variation within species were lower and ranged from 4 (ph) to 62% (ascorbic acid). Only the FRAP values were significantly affected by harvesting year with lower levels in 2004 than in 2005 and There were significant interactions between species and harvesting year for dry matter, soluble solids, ph, ascorbic acid and FRAP. The results indicate generic ranges in composition within species independent upon growing location and climate, and the composition of the tree fruits and berries is not likely to deviate from these ranges. It is concluded that desirable composition of tree fruits and berries and their products should primarily be achieved by selection among species rather than searching fors broadened variation within individual species. Keywords: Anthocyanins, antioxidants, antiradical power, apple, aronia, ascorbic acid, bilberry, blackcurrant, blueberry, cloudberry, composition, dry matter, elderberry, FRAP, gooseberry, lingonberry, ph, raspberry, red currant, soluble solids, sour cherry, strawberry, sweet cherry, titratable acids, total phenolics. Abbreviations: Ascorbic acid, L-ascorbic acid; ANOVA, analysis of variance; ARP, antiradical power; 8Brix, g sucrose 100 g 1 of FW as determined in a refractometer; DPPH, 2,2-diphenyl-1-picrylhydrazyl; FRAP, ferric reducing activity power; FW, fresh weight; GAE, gallic acid equivalents; HPLC, high-performance liquid chromatography; TCEP, tris[2-carboxyethyl]phosphine; Trolox, 6-hydrox-2,5,7,8-tetramethyl-2-carboxyl acid; TE, Trolox equivalents; UV-vis, ultraviolet-visible light. Introduction The increasing consciousness on healthy foods has led to renewed attention to specific constituents of fruits and berries. In addition to satisfying traditional sensory and chemical/physical quality criteria, fruits and berries should be high in vitamins and other health-related components, like polyphenolics. The traditional quality parameters in fruits and berries include dry matter, sugars, dietary fiber, organic acids and pigments (Kuusi 1970, Skrede 1980). Soluble solids, representative of sugar levels, and titratable acids and ph representative of total acids, contribute to sweetness and acidity of fruits and berries and their products (Viljakainen et al. 2002). Quality parameters related to human health include vitamin C, analysed as l-ascorbic and dehydro ascorbic acid (Agar et al. 1997, Benvenuti et al. 2004, Davey and Keulemans 2004), anthocyanins, classified both as pigments and antioxidants (Kähkönen and Heinonen 2003, Matsumoto et al. 2004, Ngo et al. 2007), total phenolics (Moyer et al. 2002, Kroon and Williamson 2005), and total antioxidant activity as determined by various assays (Prior et al. 1998, Halvorsen et al. 2002, Aaby et al. 2004). There may be considerable variation in chemical composition among different fruit and berry species. While some species are similar in composition, others differ markedly (Häkkinen et al. 1999, Wada Correspondence: Grete Skrede, Nofima AS, Osloveien 1, N-1430 Aas, Norway. Fax: grete.skrede@nofima.no (Received 16 February 2011; revised 7 June 2011; accepted 8 June 2011) ISSN print/issn online # 2011 Taylor & Francis DOI: /

3 2 G Skrede et al. and Ou 2002, Pellegrini et al. 2003, Määttä-Riihinen et al. 2004, Wu et al. 2004). Most commercially grown species comprise a wide number of genotypes which contribute to variation in composition within the species (Haffner et al. 2002, Moyer et al. 2002, Vrhovsek et al. 2004, Capocasa et al. 2008). Further, it is well documented that location (McGhie et al. 2005, Zheng et al. 2009a), weather conditions (Poll et al. 2003, Zheng et al. 2009b) and farming practice (Haffner et al. 2002, Wold and Opstad 2007) influence levels of constituents in the plant material. Today, fruits and berries grown for industrial use, and increasingly also for the fresh market, are to a large extent becoming international commodities. It would thus be interesting to know to what extent the composition of species varies when effects of varying genotypes, and different geographical origin and growing conditions are taken into consideration. The purpose of the present study was to study differences in constituents among 11 domesticated and three wild tree fruit and berry species. The species were represented by cultivars typical for Nordic growing conditions, and samples were harvested during three years. The parameters analysed were dry matter, soluble solids, titratable acids, pigments, and the health-related ascorbic acid, total phenolics, and antioxidant activity by the DPPH and FRAP assays. Known ranges for each parameter were established by selecting upper and lower levels in published studies. The analysed material was compared with ranges obtained from literature in order to establish generic ranges in each species. Materials and methods Chemicals Gallic acid, malic acid, 2,2-diphenyl-1-picrylhydrazil (DPPH) and Folin-Ciocalteu s phenol reagent were purchased from Sigma Chemical Co. (St. Louis, MO). Metaphosphoric acid was purchased from Sigma-Aldrich Chemie GmbH (Steinham, Germany). 2,4,6-Tripyridyl-s-triazine (TPTZ) and 6-hydroxy-2,5,7,8-tetramethyl-2-carboxylic acid (Trolox) were obtained from Fluka Chemie GmbH (Buchs, Switzerland). FeCl 3 6H 2 O, FeSO 4 8 7H 2 O, L-()-ascorbic acid, citric acid, sodium acetate (CH 3 CO 2 Na 3H 2 O), sodium carbonate, sodium dihydrogen phosphate hydrate (NaH 2 PO 4 H 2 O), disodium hydrogen phosphate dihydrate (Na 2 H- PO 4 2H 2 O), NaOH (Titrisol), potassium chloride (KCl), n-dodecyltrimethylammonium chloride, and disodium EDTA (Na 2 -EDTA) were obtained from Merck KGaA (Darmstadt, Germany). HCl, acetonitrile and methanol were all of analytical or HPLCgrade (Merck KGAa), and water was of MilliQ quality (Millipore Corp., Cork, Ireland). Plant material Tree fruits and berries were grown by farmers in the Lier area (latitude 59877?N, longitude 10821?E) or in the experimental fields of the Norwegian University of Life Sciences at Aas (latitude 59863?N, 10884?E), Norway. Samples (0.5 kg fresh weight (FW)) were harvested at commercial ripeness as judged by the growers, and frozen at 20 8C within a few hours. Wild berries were obtained from the berry processing company Findus Norge AS (Lier, Norway) or picked from typical native stands in Norway. All samples were transported to Nofima where they were kept frozen up to 5 months until analysis of all or a selection of the analysis described below. Most samples were harvested during three years ( ). The material included in the study is specified in Table I. The number of cultivars within each species varied from 15 in blackcurrant to three in sweet cherry and gooseberry (Table I). The wild species (bilberry, lingonberry and cloudberry) were each represented by 23 independent samples of different origin with many genotypes potentially represented in each sample. Determination of dry matter, soluble solids, titratable acids and ph Frozen tree fruit and berry samples were thawed at room temperature and homogenized (Braun 4262, Kronberg, Germany). Dry matter was determined by vacuum drying (NMKL 2002) and given as g 100 g 1 of fresh weight (FW). Soluble solids were determined at 20 8C using a refractometer (Mettler Toledo RE40, Columbus, OH) with the results given as 8Brix (g 100 g 1 of FW). For determination of titratable acids, the homogenized material was filtered and diluted 1:10 with water followed by titration to ph 8.1 with 0.1 M NaOH using an automated Mettler DL25 titrator (Mettler Toledo) (Hagen et al. 2007). Titratable acids were calculated as g malic acid per 100 g of FW. ph was recorded at the titrator on the material prior to titration. The samples were analysed in duplicate. Determination of ascorbic acid Ascorbic acid was determined by HPLC as described previously (Aaby et al. 2007). In brief, partly thawed, homogenized (Polytron PT3100, Kinematica AG, Littau, Switzerland) material (10 g) in 20 ml 4.5% (w/v) metaphosphoric acid in water was homogenized

4 Nordic tree fruit and berry species 3 Table I. Family/crop, botanical name, cultivar/genotype and harvesting year of the 14 tree fruit and berry species included in the study. Family/Crop Botanical name Cultivar/Genotype Harvesting Year a - bilberry Vaccinium myrtillus L. 3 wild samples, different sites blueberry Vaccinium corymbosum L. Bluecrop, 1613A (syn. Hardyblue), Patriot, Putte lingonberry Vaccinium vitis-idaea L. 2 wild samples, different sites apple Malus domestica Borkh. Aroma, Fiesta, Gravenstein, Julyred, Summerred aronia/black Aronia melanocarpa (Michx.) Aron, Moskva, Park, Viking chokeberry Elliot - cherry sour Prunus cerasus L. Birgitte, Fanal, Kelleris, Nefris, Stevnsbær, Tiki cherry sweet Prunus avium L. Huldra, Kristin, Stella cloudberry Rubus chamaemorus 3 wild samples, different sites raspberry Rubus idaeus L. Algonquin, Balder, Elida, Glen Ample, Niniane, Veten - strawberry Fragaria x ananassa Duch. Bounty, Elan, Frida, Korona, Polka, Senga Sengana, Zefyr black currant Ribes nigrum L , Ben Alder, Ben Avon, Ben Dorain, Ben Gairn, Ben Hope, Ben Nare, Ben Nevis, Ben Tirran, Ben Tron, Kristin, N 18, Narve Viking, Titania, Varde Viking - gooseberry Ribes uva-crispa L. Hinnomäke Red, Invicta, Pax red/white currant Ribes rubrum L. Hvid, Hvid Jede, Nortun, Red Start, Rondom, Rosetta, Rubin, Red Dutch elderberry Sambucus nigra L. Sambu, Samdal, Samnor, Sampo, Samyl a All cultivars/genotypes were not harvested each year. for 1 min. The solution was diluted to 50 ml with 4.5% metaphosphoric acid, and filtered through a folded filter (Schleicher & Schuell GmbH, Dassel, Germany), followed by a Millex HA 0.45 mm filter (Millipore Corp., Cork, Ireland). The samples were analysed using an Agilent 1100 series HPLC system (Agilent Technologies, Waldbronn, Germany). The HPLC column was a Chromolith TM Performance RP-18e (100 mm4.6 mm i.d., Merck KGaA, Darmstadt, Germany) with a guard cartridge (5 mm4.6 mm i.d., Merck KGaA). The eluent was 2.5 mm Na 2 H 2 PO 4 2H 2 O, 2.5 mm n-dodecyltrimethylammonium chloride, 1.25 mm Na 2 -EDTA, and 2% acetonitrile, adjusted to ph 4.7 with 0.27 M citric acid. The eluent flow rate was 1 ml min 1 and the column temperature 25 8C. Sample injections were 15 ml. Ascorbic acid was detected at 264 nm, quantified by an ascorbic acid external standard, and expressed as mg ascorbic acid per 100 g of FW. The samples were analysed in duplicate. Determination of total monomeric anthocyanins, total phenolics, antiradical power (ARP) by the DPPH assay, and ferric reducing activity power (FRAP) Extracts for the total monomeric anthocyanins, total phenolics, DPPH and FRAP assays were prepared by mixing 5 g homogenized tree fruits and berries with 10 ml methanol. Samples were centrifuged (Beckman J2-21M/E, Beckman Instruments Inc., Fullerton, CA) at g and 4 8C for 10 min, and decanted. The pellets were resuspended in 10 ml 70% methanol in water (v/v) followed by centrifugation. The combined supernatants were diluted to 25 ml with 70% methanol. The extracts were frozen at 80 8C until analysis. The extracts were made in duplicate. Total monomeric anthocyanins were determined by the ph-differential method (Giusti and Wrolstad 2005). Extracts were diluted with M potassium chloride buffer, ph 1, and 0.4 M sodium acetate buffer, ph 4.5. After 20 min at room temperature, absorptions at 520 nm and 700 nm were measured (Agilent 8453 spectrophotometer, Agilent Technologies, Waldbronn, Germany). Results were calculated as mg cyanidin-3-glucoside (molecular weight g mol 1, molar absorptivity ) per 100 g of FW. Total phenolics were determined using the Folin Ciocalteu method as described previously (Waterhouse 2005, Aaby et al. 2007). To methanol extract (0.2 ml), 1.0 ml FolinCiocalteu reagent (diluted 1:10 with water) was added. The mixture was left for 3 min to react before 0.8 ml 7.5% (w/v) sodium carbonate was added. After 60 min incubation at

5 4 G Skrede et al. room temperature, absorption at 765 nm was measured (Agilent 8453 spectrophotometer, Agilent Technologies). Gallic acid was used as a standard. Total phenolics were calculated as mg gallic acid equivalents (GAE) per 100 g of FW. ARP, the scavenging effects towards the 2,2- diphenyl-1-picrylhydrazyl free radical (DPPH), was determined by the DPPH-assay reported by Brand- Williams et al. (1995), and slightly modified by Aaby et al. (2004). Briefly, three appropriate dilutions of methanol extracts (0.1 ml) were added to 2.4 ml DPPH-solution (25 mg L 1 methanol). Sample blanks were methanol and DPPH-solution. Samples and blanks were left in the dark for 2 h at room temperature, after which the absorption at 515 nm was recorded in a spectrophotometer (Agilent 8453, Agilent Technologies). The amount of material required to decrease the initial DPPH concentration by 50% (EC 50 ) was calculated by linear regression of remaining DPPH (%) vs. concentration of the sample. ARP was calculated as the reciprocal of EC 50 and reported relative to ARP of Trolox as mmol Trolox equivalents (TE) per g of FW. The FRAP assay was performed according to Benzie and Strain (1996) with some modifications as described by Volden et al. (2008). In brief, 0.2 ml FRAP reagent (3.0 mm acetate buffer, 10 mm TPTZ in 40 mm HCl, 20 mm FeCl 3 6H 2 O, ratio 10:1:1 (v/v/v)) were automatically pipetted and mixed in cuvettes using a Konelab 30i (Thermo Electron Corp., Vantaa, Finland). Appropriately diluted methanol extracts (8 ml) were added, mixed and incubated for 10 min at 37 8C prior to measurements of absorption at 595 nm. Fe 2 (FeSO 4 7H 2 O) in different concentrations were used for calibration of the FRAP assay. Results were calculated as mmol Fe per 100 g of FW. Statistical analysis Linear regression analysis for calculating ARP values were performed by Microsoft Excel (Redmond, WA). For all parameters, mean and coefficient of variation (CV) within and between species were calculated and ranges between highest and lowest levels within species identified. One-way analysis of variance (ANOVA) was used to analyse differences between all species, and between harvesting year for species harvested for three years, using Minitab Statistical Software (Release 15, Minitab Inc., State College, PA). Two-way ANOVA was performed to analyse effects of species and harvesting year and their interactions for samples harvested for three years, using the general linear model with harvesting year as random factor (SAS 9.1 for Windows, SAS Institute Inc., Cary, NC). Significant differences (p 50.05) between means were determined by Tukey s multiple-comparisons test. Results Dry matter Dry matter within the 14 tree fruit and berry species varied from 9.3 to 20.8% with a mean dry matter for all species of 14.3% (Table II). Aronia and blackcurrant, followed by sweet cherry had the highest dry matter levels. The remaining species did not differ significantly in dry matter except for strawberry with the lowest level. The lowest CV within species represented by more than two samples was seen in aronia (7.3%) and the highest in gooseberry (17.5%). Sour cherry, red currant, strawberry, apple, elderberry, and blueberry also revealed relatively high variability. The CV within species was slightly lower than between species (18.9%). Levels of dry matter for most species were within previously published ranges, but for sour and sweet cherry the literature data were rather limited. Among the analysed species only gooseberry showed maximum levels of dry matter slightly exceeding published levels, while most species had lower minimum levels. Thus, the dry matter levels in the present study appeared to be comparable but in the lower end of ranges established previously for the present species. Soluble solids The mean level of soluble solids in the 14 species was Brix (Table III). Blackcurrant, aronia and sour cherry with 17.4, 17.0, and Brix, respectively, had the highest soluble solids among the species, followed by sweet cherry and lingonberry. The lowest soluble solid levels were found in cloudberry, strawberry, elderberry, raspberry, bilberry, and red currant, all in the range of 7.3 to Brix and with no significant differences between them. The CV between species was 25.3%, and there was a 2.4-fold difference between the highest and the lowest soluble solid level, i.e. between blackcurrant and cloudberry. The variation in soluble solids within species, expressed by the CV, was around 10% for most species, however, for aronia and lingonberry the CV was only 4.4% and for gooseberry as high as 21.8%. Soluble solids was well within the published ranges in all species, except for sour cherry where the level was lower and blackcurrant and gooseberry where the level was higher than reported in literature. The minimum soluble solid levels in bilberry, apple, sour cherry, and elderberry were slightly lower than reported earlier, while no previous reports have

6 Nordic tree fruit and berry species 5 Table II. Dry matter levels (g 100 g 1 of fresh weight) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest dry matter levels for the species. Dry matter (g 100 g 1 of FW) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry c (Kuusi 1970, Mattila et al. 2006) Blueberry c (Prior et al. 1998, Giovanelli and Buratti 2009) Lingonberry c (Kuusi 1970, Mattila et al. 2006) Apple c (Wu et al. 2006) Aronia a (Wu et al. 2006, Kulling and Rawel 2008) Cherry, sour c Cherry, sweet bc (Wu et al. 2006) Cloudberry c (Kuusi 1970, Mattila et al. 2006) Raspberry c (Haffner et al. 2002, Remberg et al. 2010) Strawberry d (Skupień and Oszmiański 2004, Tulipani et al. 2008) Blackcurrant ab (Blom and Skrede 1984, Wu et al. 2006) Gooseberry c (Kuusi 1970, Mattila et al. 2006) Red currant c (Kuusi 1970, Wu et al. 2006) Elderberry b (Wu et al. 2006, Kaack et al. 2008) All species p (species) B0.001 a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. recorded higher levels in soluble solids than the present maximum levels in blackcurrant, gooseberry, red currant and cloudberry. Titratable acids Blackcurrant, with 3.75 g malic acid 100 g 1 of FW, exhibited higher titratable acids than any of the other species, followed by red currant, gooseberry, raspberry and lingonberry (Table IV). Bilberry, blueberry, apple, aronia, sweet cherry, cloudberry, strawberry and elderberry showed the lowest levels of titratable acids; all within a range from 0.55 to 1.27 g 100 g 1 of FW and with no significant differences between them. Mean titratable acid level of all species was 1.57 g 100 g -1 of FW and the CV between species was 59.3%. There was a 6.8-fold difference between the highest level of titratable acids in blackcurrant and the lowest in sweet cherry. Titratable acidity appeared to be more variable among species than did soluble sugars and dry matter. The CV for titratable acids within species varied from 8.8% in bilberry to 33.3% in blueberry, when excluding lingonberry with only two samples. Elderberry, gooseberry and sour cherry also showed relatively high CV ( %). The overall variation in titratable acid levels within species was lower than the variation among species. All species, except gooseberry and red currant with slightly higher levels than previously reported, and cloudberry with lower level, had levels of titratable acids within published ranges. The highest level in apple and blackcurrant was higher, and the lowest level in sour cherry lower than previously reported. Gooseberry and red currant showed wide ranges with both minimum and maximum titratable acid levels beyond reported ranges. Although one acid often dominates, many of the tree fruit and berry species investigated contain a mixture of various organic acids (Viljakainen et al. 2002). In the literature both malic acid and citric acid are used for calculating titratable acid content in fruits and berries. The differences in the calculations for the two acids are owing to the difference in their equivalent weights. This implies that acid levels calculated as citric acid are 95.5% of levels calculated as malic acid. The choice of acid is thus considered to have minor impact when comparing results from various published studies.

7 6 G Skrede et al. Table III. Soluble solid levels (8Brix) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest soluble solid levels for the species. Soluble solids (8Brix) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry bc (Kuusi 1970, Ochmian et al. 2009) Blueberry b (Prior et al. 1998) Lingonberry bc (Kuusi 1970, Saario 2000) Apple b (Davey and Keulemans 2004, Hagen et al. 2007) Aronia a (Plocharski and Zbroszcyzk 1992) Cherry, sour a (Petersen and Poll 1999, Poll et al. 2003) Cherry, sweet ab (Girard and Kopp 1998, Gonçalves et al. 2004) Cloudberry c (Kuusi 1970) Raspberry c (Kuusi 1970, Tosun et al. 2009) Strawberry c (Skupień and Oszmiański 2004, Capocasa et al. 2008) Blackcurrant a (Kuusi 1970, Blom and Skrede 1984) Gooseberry b (Kuusi 1970, Pantelidis et al. 2007) Red currant bc (Rotundo et al. 1998, Pantelidis et al. 2007) Elderberry c (Kaack et al. 2008) All species p (species) B a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. ph The ph of the fruit of the 14 species studied varied from 2.6 to 4.1 and there were significant differences among species (Table V). Elderberry and sweet cherry represented the highest, and lingonberry, blackcurrant, gooseberry, bilberry, red currant and raspberry the lowest ph values. The mean ph for all species was 3.24 and the CV between species was 12.5%, which is low compared with the CV for titratable acids. This may be as expected as the ph is a logarithmic function of acid concentration and less sensitive to changes within certain concentration ranges. The species with the highest ph (elderberry and sweet cherry) also had the lowest acid levels, while the species with low ph had high acid levels. The variation in ph within species was rather low, the CV differing from 1.9% in lingonberry to 6.0% in elderberry. Blueberry, sour cherry, blackcurrant and sweet cherry also had CV above 4%. The ph values in most species were in accordance with published values. The lowest ph values were slightly lower than previously reported for bilberry, lingonberry, aronia, sour cherry, raspberry, blackcurrant, gooseberry and elderberry, while maximum> values were higher in cloudberry, gooseberry and elderberry. Ascorbic acid The mean ascorbic acid level for all species was 34.8 mg 100 g 1 of FW and varied from 0.4 mg 100 g 1 of FW in sweet and sour cherry to mg 100 g 1 of FW in blackcurrant (Table VI). Cloudberry followed blackcurrant in ascorbic acid level, but was not significantly different from red currant, strawberry, gooseberry or lingonberry. Substantial differences between species in ascorbic acid levels were reflected in a high CV (137%) when all species were included. The ascorbic acid levels within species were within or close to published ranges in most species, but there was great variation, especially at the lower levels where analytical precision may be more critical than at higher levels. In species with ascorbic acid levels above 10 mg 100 g 1 of FW and more than two samples analysed, the CV varied between 27.3 and 61.9%.

8 Nordic tree fruit and berry species 7 Table IV. Titratable acid levels (g 100 g 1 of fresh weight) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest titratable acid levels for the species. Titratable acids (g 100 g 1 of FW) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry cd (Viljakainen et al. 2002, Ochmian et al. 2009) Blueberry d (Connor et al. 2002, Skupień 2006) Lingonberry bc (Viljakainen et al. 2002, Wang et al. 2005) Apple d (Aaby et al. 2002, Hagen et al. 2007) Aronia d (Plocharski and Zbroszcyzk 1992, Ochmian et al. 2009) Cherry, sour c (Petersen and Poll 1999, Poll et al. 2003) Cherry, sweet d (Girard and Kopp 1998, Vursavus et al. 2006) Cloudberry d (Kuusi 1970) Raspberry bc (Haffner et al. 2002, Viljakainen et al. 2002) Strawberry d (Kuusi 1970, Capocasa et al. 2008) Blackcurrant a (Blom and Skrede 1984, Viljakainen et al. 2002) Gooseberry bc (Kuusi 1970) Red currant b (Kuusi 1970) Elderberry d (Lee and Finn 2007, Kaack et al. 2008) All species p (species) B a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. Total monomeric anthocyanins Differences in pigmentation between species are well known as this parameter in contrast to most others can be visually judged. In the species investigated, total monomeric anthocyanin levels ranged from 0.3 to 697 mg 100 g 1 of FW (Table VII) with a CV between species of 132%. Elderberry had the highest anthocyanin levels, followed by bilberry, aronia and blackcurrant. No significant differences were obtained among the remaining species. Cloudberry and apple were only slightly pigmented by anthocyanins. The white/green cultivars of red currant and gooseberry were excluded from the calculations. Within species the CV ranged from 16.4 to 57.4% when apple and cloudberry, which contained very low levels of anthocyanins, were excluded. Among the species where comparisons could be made, pigment levels were within reported values, except for bilberry and aronia. Particularly in bilberry both level and range of total monomeric anthocyanins exceeded previously reported levels. In strawberry the maximum level of 122 mg 100 g 1 of FW was reported for one genotype in a study of six genotypes where the remaining genotypes were within the range of 3776 mg 100 g 1 of FW (Ngo et al. 2007) which is higher but more in accordance with the present results. Total phenolics Aronia exhibited a total phenolic content of 1496 mg GAE 100 g 1 of FW, which was significantly higher than in any other species, including elderberry with significantly higher total phenolics than all remaining species (Table VIII). Lingonberry, blackcurrant and bilberry showed levels of mg GAE 100 g 1 of FW, while apple, sweet cherry and gooseberry all had total phenolic content below 150 mg GAE 100 g 1 of FW. The content of total phenolics was 18- fold higher in aronia than in gooseberry with the lowest level. The CV between species was 83.8% and ranged from 5.2 to 40.1% within species. The CV within species with the highest number of samples was 19.8% for blackcurrant, 39.5% for red currant and 15.2% for strawberry. Total phenolic levels of most species were within reported ranges. The values in sour cherry and cloudberry were higher, and those in gooseberry and red currant lower than previously published data. The minimum levels of total phenolics were below reported ranges in blackcurrant,

9 8 G Skrede et al. Table V. ph in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest ph for the species. ph Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry de (Kuusi 1970) Blueberry d (Connor et al. 2002, Saftner et al. 2008) Lingonberry e (Kuusi 1970, Saario 2000) Apple c (Aaby et al. 2002, Davey and Keulemans 2004) Aronia bc (Plocharski and Zbroszcyzk 1992) Cherry, sour cd (Chaovanalikit and Wrolstad 2004) Cherry, sweet ab (Girard and Kopp 1998, Gonçalves et al. 2004) Cloudberry bc (Kuusi 1970) Raspberry de (Rotundo et al. 1998, Haffner et al. 2002) Strawberry b (Kuusi 1970, Aaby et al. 2007) Blackcurrant e (Rotundo et al. 1998, Zheng et al. 2009b) Gooseberry de (Kuusi 1970) Red currant de (Rotundo et al. 1998) Elderberry a (Lee and Finn 2007) All species p (species) B a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. gooseberry, red currant, strawberry and bilberry while the maximum levels in sour cherry and cloudberry exceeded known ranges. Antiradical power (ARP) by the DPPH assay The highest ARP value occurred in aronia, followed by elderberry, blackcurrant and bilberry (Table IX). Raspberry, red currant, blueberry, strawberry, apple, gooseberry and sweet cherry all had ARP values below 20 mmol TE g 1 of FW. There was a 27.4-fold difference between the highest ARP value of aronia and the lowest of sweet cherry. The overall variation coefficient between species was 97.8%. Within species the CV differed from 3.5% in lingonberry to 44.3% in red currant. Only a limited number of studies reporting ARP values were identified in the literature and no literature data on ARP are presented in Table IX. The only comparable values were 1922 mmol TE g 1 of FW in various blackcurrant cultivars obtained from Tabart et al. (2006) after recalculations using the present dry matter value for blackcurrant (Table II). These values were slightly lower than the present 33.5 mmol TE g 1 of FW. Ferric reducing activity power (FRAP) FRAP values ranged from 1.1 to 19.8 mmol Fe 100 g 1 of FW, corresponding to an 18-fold difference (Table X). Aronia had significantly higher FRAP value than the fruit of all the species except bilberry. Sweet cherry, apple, gooseberry, red currant, strawberry and raspberry had the lowest FRAP values. The CV between species was 85.7%. The CV within species was lower, ranging from 14.8% in strawberry to 63.2% in red currant when the species with less than three samples were excluded. FRAP values obtained for bilberry, aronia, cloudberry and elderberry exceeded previously reported values, while the remaining species were within published ranges. The maximum FRAP values in many of the species were higher than previously reported, especially in bilberry, aronia and elderberry. Effects of harvesting year on quality parameters Ten out of the total 14 tree fruit and berry species investigated were harvested for three years (Table I). With those ten species in the model, there were highly significant differences between the species for all

10 Nordic tree fruit and berry species 9 Table VI. Ascorbic acid levels (mg 100 g 1 of fresh weight) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest ascorbic acid levels for the species. Ascorbic acid (mg 100 g 1 of FW) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry c (Prior et al. 1998) Blueberry c d 9.5 (Prior et al. 1998, Olsson et al. 2004b) Lingonberry bc d (Olsson et al. 2004b) Apple c (Lee et al. 2003, Vrhovsek et al. 2004) Aronia c (Kulling and Rawel 2008) Cherry, sour c (Bonerz et al. 2007) Cherry, sweet c (Girard and Kopp 1998, Serrano et al. 2005) Cloudberry ab (Baardseth and Russwurm 1978) Raspberry c (Rotundo et al. 1998, Pantelidis et al. 2007) Strawberry bc (Skrede 1982, Tulipani et al. 2008) Blackcurrant a (Blom and Skrede 1984, Bordonaba and Terry 2008) Gooseberry bc (Häkkinen et al. 1999, Pantelidis et al. 2007) Red currant bc (Häkkinen et al. 1999, Zheng et al. 2009a) Elderberry c (Porpaczy and Laszlo 1984) All species p (species) B a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. d From Olsson et al. (2004b), recalculated into mg 100 g 1 of FW using mean dry matter levels in Table II. parameters, while no significant effects of harvesting year were seen except for the FRAP value (Table XI). The lowest mean FRAP value for all species occurred in 2004 (data not presented). For dry matter, soluble solids, ph, ascorbic acid, total monomeric anthocyanins and FRAP there were significant interactions between species and harvesting year, which means that the species responded differently to the growing conditions of the three harvesting years. The dry matter content in apple (p 0.015; ) and elderberry (p0.042; ) but in no other species, were significantly affected by harvesting year. Soluble solids in elderberry was higher in 2005 than in 2004 (p0.031). ph in strawberry (p 0.001; 2005 and ) and blackcurrant (p 0.019; ) were affected by harvesting year, while ascorbic acid content in blackcurrant (p0.007; and 2006) and sour cherry (p 0.026; ) varied between years. For FRAP, aronia (p0.030; ) was the only species with significant differences between year. For total monomeric anthocyanins which were analysed in 2004 and 2006 only, none of the species demonstrated any significant effect of harvesting year. Discussion The tree fruit and berry species included in the present study belong to various botanical families. The species display broad differences in morphology and considerable variation in taste, pigmentation and content of health-promoting components. All fruits and berries were harvested at visually judged full ripeness so that the effects of ripening which is known to greatly influence quality (Gonçalves et al. 2004, Olsson et al. 2004a, Siriwoharn et al. 2004, Castrejón et al. 2008, Wang et al. 2009), was kept at a minimum. The growing sites for the plant material were only a short distance apart and the differences in climate conditions between locations were considered to be minor. The climatic conditions may have differed more for the bilberry, lingonberry and cloudberry samples as they were sampled from wild plantings at various locations. Weather conditions are well known to affect composition of fruits and berries (Poll et al. 2003, Zheng et al. 2009a, 2009b, Remberg et al. 2010). The differences between the three harvesting years appeared to be small in the present study, as only two species (blackcurrant and elderberry) significantly responded to harvesting

11 10 G Skrede et al. Table VII. Total monomeric anthocyanin levels (mg 100 g 1 of fresh weight) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest total monomeric anthocyanin levels for the species. Total monomeric anthocyanins (mg 100 g 1 of FW) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry ab (Skrede and Wrolstad 2002) Blueberry d (Moyer et al. 2002) Lingonberry 2 72 d (Wang et al. 2005) Apple d Aronia b (Kulling and Rawel 2008) Cherry, sour d (Poll et al. 2003) Cherry, sweet 3 17 d Cloudberry Raspberry 6 43 d (Haffner et al. 2002, Wada and Ou 2002) Strawberry 8 29 d (Skrede and Wrolstad 2002, Ngo et al. 2007) Blackcurrant c (Skrede 1987) Gooseberry 2 d 19 d Red currant 8 d 26 d (Benvenuti et al. 2004, Pantelidis et al. 2007) Elderberry a (Brønnum-Hansen and Hansen 1983, Lee and Finn 2007) All species p (species) B a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. d White colored gooseberry and red currant were excluded from the calculations. year in more than one quality parameter. It is well documented that farming managements like the type of soil, planting distance, pruning, fertilizing and irrigating all influence tree fruit and berry quality (Lee and Kader 2000, Anttonen et al. 2006, Wold and Opstad 2007). As these factors were not specifically investigated in the present study, their effects should be considered as incorporated in the study, thus rendering the sampled material representative of wild and commercially grown tree fruits and berries in this geographic area. The results showed significant differences between species for all quality parameters investigated. The variability expressed by CV differed between parameters; the lowest CV being obtained for ph (12.5%), dry matter (18.9%), and soluble solids (25.3%), followed by titratable acids (59.3%), total phenolics (83.8%), FRAP (85.7%), and ARP (97.8%). Pigments as total monomeric anthocyanins, and ascorbic acid levels varied most between species with a CV of 132 and 137%, respectively. These differences illustrate that species with different composition will be more easily identified for ascorbic acid and pigments, than for ph, soluble sugars and dry matter, whereas the antioxidant parameters represent intermediate variability. Differences in quality parameters between species have been reported in numerous studies (Heinonen et al. 1998, Häkkinen et al. 1999, Wang and Lin 2000, Halvorsen et al. 2002, Moyer et al. 2002, Viljakainen et al. 2002, Wu et al. 2004, Mattila et al. 2006, Kevers et al. 2007), but only a limited number of studies present statistical evidence for the differences (Benvenuti et al. 2004, Pantelidis et al. 2007, Ochmian et al. 2009). The inclusion of several cultivars/genotypes within most species gave indications of the variations to be expected in composition of the tree fruits and berries grown within this Nordic region. Still, the material represented a limited selection of all genotypes available for the species investigated, and general conclusions must be drawn with caution. The literature data used for comparison with our findings represent samples obtained from a diversity of cultivars, agricultural practices, growing sites, and climate conditions around the world where some of the species may have been better adapted to the growing conditions than they might have been when grown in Norway. Even with these restrictions taken

12 Nordic tree fruit and berry species 11 Table VIII. Total phenolic levels (mg 100 g 1 of fresh weight) in fruits from 14 tree fruit and berry species harvested during three years, reported as mean, coefficient of variation (CV), and range between highest and lowest level within each species. Literature data, along with their references, provide previously reported ranges between highest and lowest total phenolic levels for the species. Total phenolics (mg GAE 100 g 1 of FW) Family/Crop N a Mean b CV (%) (analysed) (from literature) c Bilberry cd (Prior et al. 1998, Ochmian et al. 2009) Blueberry de (Moyer et al. 2002, Taruscio et al. 2004) Lingonberry cd (Wang et al. 2005) Apple e (Imeh and Khokhar 2002, Vrhovsek et al. 2004) Aronia a (Zheng and Wang 2003, Ochmian et al. 2009) Cherry, sour d (Chaovanalikit and Wrolstad 2004, Piccolella et al. 2008) Cherry, sweet e (Gonçalves et al. 2004, Usenik et al. 2008) Cloudberry de d (Kähkönen et al. 2001) Raspberry de (Liu et al. 2002, Kafkas et al. 2008) Strawberry e (Skupień and Oszmiański 2004, Tulipani et al. 2008) Blackcurrant c (Moyer et al. 2002, Wu et al. 2004) Gooseberry 5 83 e (Moyer et al. 2002, Wu et al. 2004) Red currant e (Benvenuti et al. 2004, Wu et al. 2004) Elderberry b (Wu et al. 2004, Lee and Finn 2007) All species p (species) B0.001 a Number of samples, i.e. sum of samples from different cultivars/genotypes, harvesting years and/or growing locations. b Values with different letters are different (p B0.05) calculated by Tukey s comparison test. c s obtained from literature by identifying highest and lowest levels reported. d From Kähkönen et al. (2001), recalculated into mg 100 g 1 of FW using mean DM levels in Table II. into consideration, the ranges obtained from literature should be representative of today s generic knowledge of tree fruit and berry composition. In the present study, mean levels of the various parameters were within already published ranges for most species. The exceptions were bilberry and aronia with higher levels in pigments and antioxidant activity as FRAP, sour cherry with higher levels in total phenolics, and cloudberry with higher levels in total phenolics and FRAP. Further, blackcurrant had higher levels of soluble solids, gooseberry higher soluble solid, titratable acid and ascorbic acid levels, red currant higher titratable acid levels, and elderberry higher FRAP levels than reported before. Lower levels than previously reported were detected only in gooseberry (dry matter, total phenolics), sour cherry (soluble solids), and red currant (total phenolics). Maximum levels in individual samples of the present study exceeded published levels for soluble solids in blackcurrant, gooseberry, and red currant, for titratable acids in apple, blackcurrant, gooseberry and red currant, and for ascorbic acid in apple, raspberry, gooseberry, red currant and elderberry. Variation in composition between cultivars/genotypes has been shown in numerous studies including species such as apple (Wojdylo et al. 2008), red raspberry (Haffner et al. 2002, Tosun et al. 2009), strawberry (Olsson et al. 2004a, Capocasa et al. 2008, Tulipani et al. 2008), elderberry (Lee and Finn 2007, Kaack et al. 2008), blueberry (Skupień 2006, Giovanelli and Buratti 2009), sweet cherry (Girard and Kopp 1998), blackcurrant (Moyer et al. 2002, Tabart et al. 2006) and red currant (Benvenuti et al. 2004). However, many cultivars/genotypes are closely genetically linked, resulting in only moderate differences in composition (Davey and Keulemans 2004). In the present study, the variation within species expressed as CV varied dependent upon species and parameter. The lowest variation within species was seen in ph with an average CV of 4%, followed by dry matter, soluble solids and titratable acids with average 1016%, total phenolics, ARP, and FRAP with average 2128%, total monomeric anthocyanins with average 37% and finally ascorbic acid with average 62%, the highest average variation in CV among the parameters tested. The variation within species was thus considerably lower than the