Postharvest Biology and Technology 110 (2015) 173–182

Biochemical contents of apple peel and flesh affect level of partialresistance to blue mold

Masoud Ahmadi-Afzadia,b,*, Hilde Nyboma, Anders Ekholma, Ibrahim Tahirc,Kimmo Rumpunena

aDepartment of Plant Breeding–Balsgård, Swedish University of Agricultural Sciences, Kristianstad, SwedenbDepartment of Biotechnology, Institute of Science, High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, IrancDepartment of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden

A R T I C L E I N F O

Article history:Received 11 May 2015Received in revised form 10 August 2015Accepted 13 August 2015Available online 2 September 2015

Keywords:Disease resistanceFlavonolsMalic acidMalus domesticaPhenolic compoundsProcyanidin B2

A B S T R A C T

Apple fruit contains a wide range of chemical compounds that may contribute to resistance against bluemold caused by Penicillium expansum. In the present study, contents of total titratable acidity, malic acid,total phenols and 10 individual phenolic compounds were quantified in peel and flesh fractions of bothcontrol and blue mold-inoculated fruits of 24 apple cultivars. In addition to the significant variationamong cultivars in terms of all quantified compounds, correlation analysis revealed a significant impactof total phenols and individual phenols like flavonols and procyanidins B2 in the peel fraction, on bluemold resistance in the inoculated fruits. Multivariate analyses on data for chemical compounds in peeltissue of inoculated fruits, could also separate resistant and susceptible cultivars. These findings can beuseful in breeding programs since higher levels of phenolic compounds may indicate better resistance inapple cultivars.

ã 2015 Elsevier B.V. All rights reserved.

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1. Introduction

Apple fruits contain several constituents with health-relatedbenefits such as organic acids, sugar alcohols and phenoliccompounds (Boyer and Liu, 2004). In order to provide the marketwith healthy and attractive fruits, harvesting and storageconditions must be carefully optimized to avoid damage due topostharvest fungal diseases. Some of these are difficult to avoid,like blue mold caused by Penicillium expansum. Infection by thispathogen is mainly wound-mediated and can occur both in theorchard and during harvesting and storage. In general, thesymptoms do however not appear until the fruit has been keptin cold storage for some weeks, thus causing serious economic lossfor the growers. Blue mold is easily identified by the rounded andpale straw-colored lesions with white to bluish–green spores.Symptoms increase fast and the entire fruit is soon destroyed byinternal rotting. In addition to lowering the commercial value ofthe apple harvest, this fungus also produces the powerfulmycotoxin patulin (Konstantinou et al., 2011).

* Corresponding author at: Department of Plant Breeding–Balsgård, SwedishUniversity of Agricultural Sciences, Kristianstad, Sweden. Fax: +46 44 265830.

E-mail address: masoud.ahmadi.afzadi@slu.se (M. Ahmadi-Afzadi).

http://dx.doi.org/10.1016/j.postharvbio.2015.08.0080925-5214/ã 2015 Elsevier B.V. All rights reserved.

Traditionally, serious economic loss due to blue mold and otherstorage diseases has been avoided by postharvest application offungicides. This procedure is, however, not allowed in organicapple production, and is prohibited also in conventional appleproduction in an increasing number of countries like Scandinaviaand Great Britain (Tahir and Nybom, 2013). Moreover, the storagedisease problems are likely to increase even further due to globalwarming (Weber, 2009). In this context, the identification of highlyresistant apple cultivars becomes very desirable. Considerableinter-cultivar variability in the amount of damage caused bypostharvest decay has been reported, both when evaluated afternatural infection (Janisiewicz and Peterson, 2004) and afterinoculation of harvested fruit with P. expansum (Jurick et al.,2011; Ahmadi-Afzadi et al., 2013; Tahir et al., 2015). No sources ofhighly efficient, genetically determined resistance have yet beenidentified but factors like level of fruit maturity (Prusky et al.,2004; Vilanova et al., 2012; Vilanova et al., 2014b; Vilanova et al.,2014c), initial firmness and rate of softening during storage(Nybom et al., 2008a; Johnston et al., 2009; Ahmadi-Afzadi et al.,2013) show strong associations with the amount of contracteddamage.

In addition to the above-mentioned fruit texture-related traits,chemical constituents of the fruit flesh and peel can also beexpected to play a role in resistance to storage diseases. Manyplants can respond to pathogens either by accumulation of pre-

174 M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182

formed compounds (phytoanticipins, i.e., chemicals that arealready present in different concentrations and forms) or byproduction of new compounds (phytoalexins) due to induction ofgenes involved in the defense system. Phytoanticipins andphytoalexins frequently consist of phenolic compounds. Thesecompounds belong to a large group of chemicals, many of whichare involved in the natural defense reactions of plants, and can betoxic to invading organisms (Grayer and Kokubun, 2001;Lattanzio et al., 2006). Polyphenols are usually divided intodifferent classes, e.g., flavanols (catechin, epicatechin andprocyanidins), flavonols (quercetin glycosides), dihydrochalcones(phloridzin), and hydroxycinnamic acids (chlorogenic acid).Accumulation of phenolic compounds as a response to infectionby apple scab caused by Venturia inaequalis has been reported(Mikulic-Petkovsek et al., 2009, 2011) while another study showedthat total phenols and phenylalanine-ammonia lyase increasedduring the first week after inoculation of apple fruit by P.expansum, followed by a period of decreasing contents (Schovan-kova and Opatova, 2011).

Table 1Average of TTA, MA and TPH measurements in flesh and peel of control and inoculated

Year Cultivars TTA (%) MA (m

Flesh Peel Flesh

C a I a C I C

2012 Apelsinoe 33 27 0.13 0.17 6.94

Aroma 40 28 0.09 0.10 7.94

Bersis 33 17 0.07 0.08 7.22

Björka 29 24 0.07 0.11 5.68

Discovery 33 30 0.13 0.11 6.73

Elise 51 31 0.10 0.10 11.3

Gloster 30 29 0.06 0.13 6.52

Göteborgs Flickäpple 46 27 0.11 0.13 9.16

Gravensteiner 35 29 0.10 0.12 7.32

Ingrid Marie 34 32 0.10 0.10 7.21

Katja 39 29 0.14 0.13 6.60

Konsta 28 31 0.11 0.12 5.27

Luke 53 38 0.13 0.14 10.80Olga 24 25 0.12 0.08 5.70

Raja 45 33 0.06 0.15 9.95

Santana 29 24 0.12 0.12 6.77

Sariola 22 23 0.07 0.11 4.82

Sörmlandsäpple 35 35 0.11 0.10 6.38

Tönnes 9 28 0.08 0.13 5.71

Williams' Pride 32 25 0.09 0.11 6.16

2013 Barchatnoje 35 37 0.06 0.06 7.64

Bersis 36 35 0.06 0.08 9.09

Elise 28 28 0.06 0.09 7.48

Gloster 33 41 0.05 0.11 8.17

Gravensteiner 41 43 0.06 0.05 9.79

Ingrid Marie 32 32 0.09 0.11 8.46

Juuso 49 43 0.07 0.07 12.3

Luke 49 42 0.09 0.10 12.5

Olga 25 23 0.06 0.08 6.84

Pepin Schafranovij 39 41 0.08 0.11 10.6

Raja 32 32 0.06 0.08 8.21

Sandra 11 24 0.07 0.08 2.56

Santana 25 31 0.08 0.10 5.95

Average of CVc

(%) in 20123.7 2.9 6.4 6.5 4.3 4.5

Average of CV(%) in 2013 (%)

1.9 2.2 6.1 6.7 2.8 3.3

a C, Control samples; I, Inoculated samples.b LD/W, Lesion Diameter/week.c CV, Coefficient of variation.

Identification of cultivars with a high level of pre-formedprotective chemical compounds would be especially valuable forplant breeding. Healthy fruit of different apple cultivars have thusbeen shown to vary significantly in content and composition ofpolyphenolic compounds (Bushway et al., 2002; Khanizadeh et al.,2008; Nybom et al., 2008a; Roen et al., 2009). Associationsbetween these compounds and level of genetically determinedresistance to diseases in apple have been investigated but withsomewhat contradictory results. A positive correlation of chloro-genic acid, flavanols and coumaric acid with level of resistance toapple scab was thus reported by Picinelli et al. (1995) whereasamount of pre-formed flavan-3-ols showed no association withresistance to apple scab in other studies (Sierotzki and Gessler,1993; Roen et al., 2009).

The objectives of this study were to (1) quantify the chemicalcompounds in peel and flesh of several apple cultivars in bothuninfected (control) and infected fruits, and (2) investigate apossible association between these chemical compounds and thelevel of resistance to blue mold.

fruits in different cultivars in 2012 and 2013.

g g�1) TPH (mg g�1 GAE FW) LD/Wb (mm)

Peel Flesh Peel

I C I C I C I

4.42 2.50 1.81 0.41 0.48 7.74 5.96 5.025.15 4.97 4.62 0.96 0.82 7.58 7.67 2.412.22 1.85 1.07 0.86 1.19 6.59 6.03 1.844.01 4.20 3.44 0.92 0.71 9.03 6.11 2.395.43 7.58 4.30 1.12 0.86 7.19 4.25 5.705.11 2.39 4.06 1.39 0.88 5.76 4.63 3.524.52 1.36 2.47 0.38 0.86 8.07 9.59 2.604.99 4.74 5.27 1.00 0.84 6.71 5.42 3.704.57 4.49 4.72 0.90 0.78 8.34 6.08 2.544.88 4.00 3.55 0.55 0.77 10.54 6.8 3.154.28 3.70 1.97 1.29 1.16 9.02 5.28 2.435.17 5.29 5.35 0.55 0.49 8.24 3.99 5.77

5.70 6.78 6.85 1.31 1.25 11.12 6.49 4.483.36 2.08 2.58 0.68 0.69 8.73 8.07 1.586.30 2.61 7.20 0.29 0.36 5.72 3.10 4.744.32 5.07 4.36 0.66 0.68 8.62 5.41 4.453.57 1.67 3.31 0.79 0.80 5.54 3.02 5.553.86 2.30 2.01 0.82 0.75 8.58 4.52 2.543.83 3.15 3.21 0.65 0.94 9.14 8.79 1.604.07 1.44 4.71 0.45 0.41 8.93 3.67 4.42

7.04 4.81 3.47 0.73 0.88 7.99 6.25 5.187.84 1.94 2.88 0.91 0.91 8.84 6.98 4.746.02 1.73 2.52 0.21 0.44 5.86 6.52 4.358.73 1.50 4.01 0.55 0.61 9.01 7.68 2.779.96 5.15 2.92 1.17 0.72 6.53 9.02 4.867.07 4.59 3.34 0.62 0.68 9.26 7.42 3.369.94 6.43 5.37 0.72 0.74 8.54 6.29 6.059.26 5.48 3.84 0.88 1.01 6.44 7.17 3.984.95 1.77 1.72 0.84 0.89 11.25 9.88 3.019.10 4.43 4.03 1.16 1.74 5.95 6.04 2.417.28 2.17 4.75 0.25 0.30 5.91 4.43 6.834.09 2.00 1.95 0.78 0.77 8.23 8.10 5.566.64 3.18 3.16 0.49 0.55 6.62 4.69 5.96

6.0 5.1 5.3 5.9 6.5 4.6 9.8

7.5 5.5 5.3 4.9 5.6 5.8 5.0

M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182 175

2. Materials and methods

2.1. Plant materials and inoculation

Fruits for the analyses were obtained from the applegermplasm orchards at Balsgård, SLU, in southern Sweden(N56�60, E14�90), using 20 cultivars in 2012 and 13 cultivars in2013 (Table 1). The orchards were fertilized, irrigated, prunedand sprayed as a commercial orchard, including 5–6 yearlyadministrations of standard fungicides in spring and summer,with the last one in the beginning of July. An iodine starch test(Smith et al., 1979) was applied up to 5 times for each cultivar todefine the commercial harvest date when starch break-down hasbeen initiated but the fruit is still in a pre-climacteric stage(values 4–5 on a 9-point scale). For each cultivar, 45 newlyharvested fruits were wounded with a pipette tip at two oppositesides and inoculated with 20 mL of a solution containing spores ofP. expansum (1 �105 conidia mL�1) and subsequently stored at 2–3 �C for either 6 weeks (for early-ripening cultivars) or 12 weeks(for late-ripening cultivars) as previously described by Ahmadi-Afzadi et al. (2013). Non-inoculated control fruits were storedunder the same conditions. After storage, lesion diameter wasmeasured at each inoculation point, and the average value wascalculated for each cultivar and divided by number of weeks instorage.

2.2. Chemicals

Commonly used solvents for HPLC and for analysis of titratableacidity, and the Folin–Ciocalteu reagent for analysis of totalphenols were obtained from Merck KGaA (Darmstadt, Germany).Ascorbic acid, malic acid, gallic acid, and chlorogenic acid werepurchased from Sigma-Aldrich (St. Louis, MO). Neo-chlorogenicacid, quercetin-3-O-rutinoside and quercetin-3-O-glucoside wereobtained from Extra Synthese (Genay, France). Meta-phosphoricacid (MPA) was purchased from VWR (Fontenay-Sous-Bois,France). In all analyses, purified water from an Elgastat PrimaUHQPS (Peterlee, Co., Durham, England) was used.

2.3. Preparation of extracts

For each cultivar, peel and flesh were sampled separately fromone pool of 10 inoculated fruits and from another pool of 10 controlfruits, after storage. For flesh samples, 10 g of fruit flesh wasimmediately mixed with 20 mL of extraction solution containing80% methanol and 1% 2,6-di-tert-butyl-4-methylphenol (BHT) andstored at �20 �C until analysis. For peel samples, 0.2 g of peel wascarefully cleaned from any remaining pieces of flesh and mixedwith 2 mL of the same extraction solution. Samples were finelychopped with a scalpel in Eppendorf tubes and homogenized by adisperser (IKA, ULTRA-TURRAX, Staufen, Germany) for 1 min. Allextracts were centrifuged at 4500 � g for 10 min, and thesupernatant was filtered through 0.45 mm membranes prior toinjection into the HPLC systems.

2.4. Total titratable acidity (TTA)

For the flesh samples, 6 mL of extract was diluted with ultrapurewaterto atotalvolume of10 mL, and thentitratedwith0.1 M NaOH topH 8.4 by an automated titrator and a SAC-80 sample changercontrolled by a TIM-90 titration controller (Radiometer AnalyticalInc., Copenhagen, Denmark). For peel samples, 0.6 mL of extract wasdiluted to a final volume of 10 mL and titrated with 0.01 M NaOH asdescribed above. The results were expressed as percentage (%) of0.1 M NaOH used for titration to pH 8.4. All samples were analyzed intriplicates.

2.5. Organic acid analysis

Malic acid (MAL) was quantified as the major organic acidaccording to a HPLC method by Rumpunen et al. (2002).Chromatographic separation was carried out by a Shimadzu HPLCsystem (Kyoto, Japan) equipped with SPD-10AV VP UV–VISdetector, LC-10AD pump, SIL-10A autosampler and a SCL-10AVPcontrol unit. Peak integration was done by Class-VP software(6.13 SP2). As the mobile phase, a mixture of 0.05 M NaH2PO4 and0.01 M H3PO4 at pH of 2.2 was used. Ten microliters of sample wasinjected into the system and separated using an Allure (RestekCorp., Bellefonte, PA) organic acids column (250 � 4.6 mm, 5 mmparticle size) at a flow rate of 0.5 mL min�1, operated at 30 �C by anexternal column oven (Column Chiller, Sorbent AB). The absor-bance was monitored at 210 nm for a total run time of 25 min.External standards were also injected at the beginning of the runand after each set of 12 samples, to check the stability of theanalysis. Samples were run in triplicates and the results wereexpressed as mg g�1 of fresh weight (FW).

2.6. Total phenols (TPH)

Content of total phenols was quantified according to the Folin–Ciocalteu method (Singleton et al., 1999). Briefly, 20 mL of extractwas diluted to a total volume of 100 mL with ultrapure water in acuvette and mixed with 200 mL of Folin–Ciocalteu reagentfollowed by addition of 2 mL 15% Na2CO3 and 1 mL ultrapurewater. The mixture was then incubated for 2 h at room tempera-ture. The absorbance was measured at 765 nm using a UV-2101PCspectrophotometer (Shimadzu, Kyoto, Japan) in duplicate for eachsample. Content of total phenols was expressed as mg g�1 GAE(gallic acid equivalents) of FW.

2.7. Individual phenols

Phenolic compounds were quantified using a Shimadzu (Kyoto,Japan) HPLC system equippedwith a SPD-M10Adiodearraydetector,a LC-20AB dual pump, and a Waters 717 plus autosampler linked to aShimadzu SCL-10A model system controller. Procyanidins B2 (PB2),epicatechin (EPI) and phloridzin (PHL) were detected at 280 nm,whereas quercetin-rutinoside (QRU), quercetin-galactoside (QGA),quercetin-glucoside (QGL), quercetin-xyloside (QXL), quercetin-arabinoside (QAR) and quercetin-rhamnoside (QRH) were detectedat 370 nm. Chlorogenic acid (CHL) was detected at 320 nm. Theelution solvents were mobile phase A (1% acetic acid, 5% acetonitrileand 94% dH2O) and mobile phase B (95% acetonitrile and 5%methanol). Linear gradient elution was according to the method ofGao et al. (2000) with some minor modifications (Roen et al., 2009):2% B for 2 min initially until 8 min, 15% B for 20 min, 21% B for 4 min,80% B for 5 min, 2% B for 3 min, followed by 2 min interval running towash the system (total run time was 42 min). The flow rate was keptat 1 mL min�1, and 10 mL of samples was injected into a SynergiTM

4 mm Hydro-RP 80 Å, LC Column 250 � 4.6 mm (Phenomenex,Værløse, Denmark). Peak integration and data extraction was doneusing the Class VP software (Shimadzu 5.0). Phenolic compoundswere identified through a comparison of retention time of peaks andpeak spiking by external standards. Seven external standards (EPI,CHL, PB2, QRU, QRH, QGA and PHL) were injected at the beginning ofthe run and subsequently after each set of 12 samples in order tovalidate inter- and intra-day precision (calculated based on thecoefficient of variation among the quantification of four externalcontrols in the HPLC run). Limit of detection (LOD) and limit ofquantification (LOQ) were calculated as 3 and 10 times the standarddeviation of the area of the background noise peak, respectively(Escarpa and Gonzalez, 1998). In addition, compounds werevalidated using a mass spectrometer (Sciex API 150 EX Turbo

176 M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182

Ionspray, applied biosystems, USA) using a scan range of 200–600 atomic mass unit (amu). Samples were quantified by HPLC–DADin triplicates and concentrations of compounds were calculatedfrom peak area and expressed as mg g�1 fresh weight of the sample.For three phenols (QGL, QXL, and QAR) for which a standard was notavailable, quantification was based on the equivalent of QRU.

2.8. Statistical analysis

Variation among cultivars in content of chemical compounds infruit flesh and peel was investigated using a series of one-wayanalyses of variance (ANOVA). Paired t-test analysis was used tocompare inoculated and control fruits. Reproducibility of chemicaldata was investigated by calculating an average coefficient ofvariation (CV) across cultivars for all quantified compounds. Aseries of Pearson correlation tests were used to investigateassociations between the content of different chemical compoundson the one hand, and lesion diameter (indicating the level ofsusceptibility to blue mold) on the other hand. All these statisticalanalyses were conducted with a 5% significance level, using Rversion 3.0.2 (R Core Team, 2013). To investigate the impact ofexplanatory variables (i.e., all measured chemical compounds) onvariation in the response variable (lesion diameter), a multiplelinear regression analysis was performed by Partial Least Squares(PLS) analysis. Explanatory variables were mean-centered andstandardized using 1/SD prior PLS analysis. Two multivariateexploratory analyses, Principal Components Analysis (PCA) andHierarchical Cluster Analysis (HCA), were also performed tocorrelate and classify the measured variables. A dendrogramwas constructed with average linkage as the grouping method andEuclidean distance as estimator of similarity. All multivariableanalyses were performed using Unscrambler1 X10.3 (CamoSoftware, 2006).

3. Results

3.1. Total titratable acidity

Total titratable acidity, expressed as % of 0.1 M NaOH, in the fruitflesh differed significantly among cultivars for both inoculated andcontrol fruits (P < 0.001). In 2012, the highest TTA (equal to highestacidity) in the flesh of control fruits was found in ‘Luke’ (53%) while‘Tönnes’ (9%) had the lowest acidity. In inoculated fruits, ‘Luke’(38%) again had the highest acidity while the lowest acidity wasfound in ‘Bersis’ (17%). In 2013, the highest TTA in the control fruitswas noted in ‘Juuso’ and ‘Luke’ (both 49%) while ‘Sandra’ (11%) hadthe lowest. In inoculated fruits, ‘Juuso’ and ‘Gravensteiner’ (both

Table 2Pearson correlation between level of susceptibility to blue mold and contents of differ

Compound Abbreviation 2012

Flesh Peel

Control Inoculated Contr

Total titratable acidity TTA 0.28 ns 0.17 ns 0.23 nMalic acid MAL 0.08 ns 0.50* 0.32 nTotal phenols TPH �0.13 ns �0.41 ns �0.26Hydroxycinnamic acids CHL 0.16 ns 0.04 ns 0.28 nFlavanols PB2 �0.13 ns �0.40 ns �0.09

EPI �0.11 ns 0.11 ns �0.23Flavonols QRU – – �0.20

QGA – – –0.26QGL – – –0.07QXY – – –0.38QAR – – –0.23QRH – – –0.27

Dihydrochalcones PHL �0.002 ns 0.23 ns �0.33

43%) had the highest acidity while ‘Olga’ (23%) and ‘Sandra’ (24%)had the lowest (Table 1).

For the peel samples, TTA varied significantly among cultivars inboth years (P < 0.01). In 2012, TTA ranged from 6% (‘Gloster’) to 14%(‘Katja’) in the control fruits, and from 8 % (‘Bersis’ and ‘Olga’) to17% (‘Apelsinoe’) in inoculated fruits. In 2013, TTA ranged from 5%(‘Gloster’) to 9% (‘Luke’) in the control fruits, and from 5 %(‘Gravensteiner’) to 11% (‘Gloster’, ‘Pepin Schafranovij’ and ‘IngridMarie’) in inoculated fruits (Table 1).

The TTA content was in overall higher in the flesh samples.Comparison between flesh of control and inoculated samplesrevealed that changes in TTA were somewhat contradictory indifferent cultivars. TTA increased after inoculation in the flesh ofsome cultivars while no significant change or a decline was notedfor other cultivars. By contrast, the TTA content showed moreconsistent changes when peel samples of control and inoculatedfruit were compared. The TTA content thus increased in severalcultivars after inoculation, but some exceptions were noted; TTAwas lower after inoculation in ‘Olga’, ‘Discovery’ and ‘Katja’ in 2012,while it remained unchanged in ‘Aroma’, ‘Elise’, ‘Ingrid Marie’ and‘Santana’ in 2012 and in ‘Barchatnoje’ and ‘Gravensteiner’ in 2013.Pearson correlations did not reveal any significant associationsbetween TTA in flesh or peel samples and level of susceptibility toblue mold (lesion diameter data) in either year (Table 2).

3.2. Organic acids

Among the organic acids, malic acid (MA) was the mostconsistent and abundant acid. Therefore, only the content of MAwas quantified (based on fresh weight) for investigation ofvariability across cultivars, and possible associations with thelevel of susceptibility to blue mold. The content of MA variedsignificantly among cultivars in both control and inoculated fruitsin both years (P < 0.001). In the flesh samples of control fruits, MAranged from 4.82 mg g�1 (‘Sariola’) to 11.28 mg g�1 (‘Elise’) in 2012,and from 2.56 mg g�1 (‘Sandra’) to 12.53 mg g�1 (‘Luke’) in 2013. Ininoculated fruits, MA ranged from 2.22 mg g�1 (‘Bersis’) to 6.30 mgg�1 (‘Raja’) in 2012, and from 4.09 mg g�1 (‘Sandra’) to 9.96 mg g�1

(‘Gravensteiner’) in 2013.The MA content was in overall lower in the peel samples. Values

in control fruits ranged from 1.36 mg g�1 (‘Gloster’) to 7.58 mg g�1

(‘Discovery’) in 2012, and from 1.50 mg g�1 (‘Gloster’) to 6.43 mgg�1 (‘Juuso’) in 2013. Corresponding values for the inoculated fruitswere 1.07 mg g�1 (‘Bersis’) and 7.20 mg g�1 (‘Raja’) in 2012, and1.72 mg g�1 (‘Olga’) and 5.37 mg g�1 (‘Juuso’) in 2013.

When flesh samples from the control and inoculated fruits werecompared pairwise, MA decreased significantly in most cultivars

ent chemicals in flesh and peel in 2012 and 2013.

2013

Flesh Peel

ol Inoculated Control Inoculated Control Inoculated

s 0.38 n s �0.09 ns �0.1 ns 0.05 ns 0.36 nss 0.48* �0.18 ns �0.09 ns 0.09 ns 0.24 ns ns �0.70** �0.38 ns �0.57* �0.31 ns �0.51 nss 0.02 ns �0.02* �0.50 ns 0.02 ns �0.37 ns ns �0.60** �0.46 ns �0.70** �0.34 ns -0.51 ns ns 0.03 ns �0.42 ns �0.30 ns �0.26 ns -0.21 ns ns �0.62** – – �0.31 ns �0.56*

ns �0.61** – – �0.70** �0.74** ns �0.69** – – �0.48 ns �0.61* ns �0.62** – – �0.56* �0.66** ns �0.60** – – �0.53 ns �0.61*

ns �0.55* – – �0.40 ns �0.45 ns ns �0.28 ns �0.23 ns �0.14 ns �0.13 ns �0.12 ns

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ars.

M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182 177

after being challenged with fungus. Some exceptions were noted;values remained almost unchanged for ‘Konsta’ and ‘Grave-nsteiner’ in 2012 and 2013, respectively, whereas instead anincrease was noted for ‘Sandra’, ‘Santana’ and ‘Gloster’ in 2013. Bycontrast, no consistent pattern could be found in MA changes in thepeel samples (Table 1).

Pearson correlation analysis showed no significant associationsbetween the level of susceptibility and MA content in flesh or peelsamples of the control fruits. By contrast, a significant positiveassociation between MA in inoculated fruits and lesion diameterwas found in 2012 for both flesh and peel samples (Table 2).

3.3. Total phenols

Significant variation in TPH content was revealed when samplesof control fruits and of inoculated fruits, respectively, werecompared across cultivars, for both 2012 and 2013 (P < 0.001).In fruit flesh samples from 2012, TPH ranged from 0.29 mg g�1 GAE(‘Raja’) to 1.39 (‘Elise’) for control fruits, and from 0.36 mg g�1 GAE(‘Raja’) to 1.25 mg g�1 GAE (‘Luke’) for inoculated fruits. Corre-sponding values for 2013 were 0.21 mg g�1 GAE (‘Elise’) and1.17 mg g�1 GAE (‘Gravensteiner’) for control fruits, and 0.30 mg g�1

GAE (‘Raja’) to 1.74 mg g�1 GAE (‘Pepin Schafranovij’) for inoculatedfruits.

The TPH content was in overall considerably higher in the peelsamples. In 2012, the lowest and highest TPH in peel samples fromcontrol fruits were obtained for ‘Sariola’ (5.54 mg g�1 GAE) and‘Luke’ (11.12 mg g�1 GAE) whereas ‘Sariola’ (3.02 mg g�1 GAE) and‘Gloster’ (9.59 mg g�1 GAE) had the lowest and highest TPH ininoculated fruits. In 2013, ‘Elise’ (5.86 mg g�1 GAE) and ‘Olga’(11.25 mg g�1 GAE) had the lowest and highest TPH content incontrol fruits whereas ‘Raja’ (4.43 mg g�1 GAE) and ‘Olga’ (9.88 mgg�1 GAE) had the lowest and highest values for inoculated fruits.

TPH values did not vary significantly when flesh samples of thecontrol and inoculated fruits were compared pairwise. By contrast,peel samples showed a significant difference in most cultivars,with lower TPH values in the inoculated fruits. No association wasfound between lesion size and TPH in the flesh or peel of controlfruits in either year. For flesh samples of inoculated fruits, therewas no significant association in 2012 while a significant, negativeassociation was found in 2013. For peel samples, a strong negativeassociation was found in inoculated fruits in 2012 while results for2013 were non-significant.

3.4. Individual phenols

Ten individual polyphenolic compounds including flavanols(EPI, PB2), flavonols (QRU, QGA, QGL, QXL, QAR, QRH), hydrox-ycinnamic acids (CHL) and dihydrochalcones (PHL) were quanti-fied in the fruit samples (Peaks 1–10 in Supplementary Fig. 1B) byusing calibration curve of external standards (Supplementary

Table 3Analytical characterization of the HPLC method for quantification of individualpolyphenolic compounds.

Compound Flesh Peel

CVa LODb LOQc CV LOD LOQCHL 3.46 0.03 0.09 2.42 0.11 0.37PB2 3.43 0.19 0.64 2.03 0.38 1.25EPI 4.91 0.13 0.41 2.05 0.51 1.71QRU 3.85 0.06 0.22 2.09 0.27 0.86QGA 4.07 0.03 0.11 2.42 0.13 0.42QRH 3.78 0.06 0.21 1.99 0.25 0.84PHL 3.17 0.04 0.14 3.16 0.16 0.54

a CV, Coefficient of variation.b LOD, Limit of detection.c LOQ, Limit of quantification. Ta

ble

4Con

centrationrange

(exp

ressed

asmgg�

1of

fresh

Com

pou

nds

2012

Flesh

Con

trol

Inoc

ula

Min

Max

Mea

nMin

CHL

6613

6936

36.9

PB2

2.5

117

524.2

EPI

9.7

317

128

8.4

QRU

––

–0

QGA

––

–2.6

QGL

––

–1.1

QXY

––

–2.7

QAR

––

–6.4

QRH

––

–0.4

PHL

2.7

4814

0.5

aAve

rage

ofCVs(Coe

fficien

tof

Variation

)fore

178 M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182

Fig. 1A). The results of inter- and intra-day precision, LOD and LOQvalues obtained from validation of HPLC method are summarizedin the Table 3. Comparing the standard chromatogram with fruitsample chromatograms obtained from mass spectrometry validat-ed the HPLC results and indicated that the HPLC method wassufficiently sensitive and reliable for determination of the phenoliccompounds in our experiment (Supplementary Fig. 2).

Flavonols were detected in the peel samples and in a very lowconcentration in the flesh samples from inoculated fruits. The CHLcontent was instead higher in the flesh samples than in peelsamples in all cultivars (Table 4). Analysis of variance demonstrat-ed significant variation among cultivars (P < 0.001) for allmeasured phenols in both peel and flesh samples, in both years.

To investigate possible associations between content ofindividual phenols and the level of blue mold susceptibilityestimated as lesion size, a series of correlation analyses wasperformed across all cultivars (Table 2). In 2012, no significantassociations were found between lesion size and individualphenols in the fruit flesh, neither for control nor for inoculatedfruits. In 2013, a significant association was however found forPB2 in inoculated fruits. In the peel samples, a significant negativeassociation was found between the lesion size and the content offlavonols (different quercetin compounds) in inoculated fruits inboth years, except for QRH in 2013. Similarly, the content ofPB2 was also significantly negatively correlated with lesion size in2012. In control fruits, no significant associations were found in2012, whereas a negative association was found between QGA andQXY on the one hand, and lesion size, on the other hand, in 2013(Table 2).

3.5. PLS analysis and contribution of chemical compounds to level ofresistance

A PLS analysis was performed separately for each year and typeof sample (fruit and flesh) using all chemical compounds asexplanatory variables to predict the response variable (lesion size).The weighted regression coefficients indicated the relative impactof different chemical compounds on lesion size variation (Fig. 1).

Fig. 1. Partial least square (PLS) regression analysis showing the impact of chemical com(lesion diameter data), in 2012 and 2013.

The content of MA and TTA, in overall, had a positive associationwith the level of susceptibility (lesion size) whereas TPH andseveral individual polyphenols showed a negative association withthe lesion size.

The PB2 and TPH content showed a negative association withdisease susceptibility in all samples in both years. Similar resultswere found for the quercetins in the peel samples for which a verystrong negative impact on lesion size was found in both years. Theremaining compounds showed small and/or inconsistent effects. Inaccordance with the correlation results, PLS confirmed that thecontents of above-mentioned compounds in the peel of inoculatedfruits have the largest impact on disease resistance (Fig. 1).

3.6. HCA and PCA analyses

Hierarchal clustering of genotypes based on the chemicalcontents in the peel of inoculated fruit was performed for datafrom each year separately. In 2012, the dendrogram indicated aseparation of three comparatively resistant cultivars, ‘Olga’,‘Tönnes’ and ‘Gloster’, from the remaining cultivars (Fig. 2A).The latter group was split into two subgroups, with overall higher(‘Discovery’ to ‘Apelsinoe’) and intermediate (‘Elise’ to ‘Grave-nsteiner’) levels of susceptibility. One comparatively resistantcultivar (‘Bersis’) and two intermediate cultivars (‘Aroma’ and‘Sörmlandsäpple’) were however found in the intermediate andhigh-susceptible groups, respectively. In 2013, the resistantcultivars ‘Olga’ and ‘Pepin Schafranovij’ formed one major groupwhile the second major group was split into one subgroup with thehighly susceptible ‘Raja’,‘Santana’ and ‘Sandra’, and anothersubgroup with mainly intermediate cultivars (‘Gloster’ to ‘Barch-atnoje’) (Fig. 2B).

A principal component analysis was performed using chemicaldata from peel samples of inoculated fruit as explanatory variableto investigate cultivar separation. Up to 69% of the total variation inlesion diameter values could be explained by the two firstcomponents in 2012, when highly resistant cultivars like ‘Olga’,‘Tönnes’, ‘Gloster’ and ‘Bersis’ were differentiated from highlysusceptible cultivars, i.e., ‘Discovery’, ‘Konsta’, ‘Sariola’ and ‘Raja’

pounds in flesh and peel of control and inoculated fruits on level of susceptibility

Fig. 2. Hierarchal clustering of genotypes based on chemical contents constructed by average linkage as the linkage grouping method and Euclidean distance as coefficient ofsimilarity, in 2012 (A) and 2013 (B).

M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182 179

Fig. 3. PCA score plots show the separation of very resistant and very susceptible cultivars in 2012 (A) and 2013 (C) based on the two first PCs. The loading plots show thecontribution of each chemical in explaining the variation in 2012 (B) and 2013 (D).

180 M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182

(Fig. 3A). The loading plot shows that flavonols, PB2 and TPH werethe main contributors to PC1 which explained 54% of the variation,and were thus responsible for much of the differentiation amongcultivars (Fig. 3B). In 2013, up to 72% of the total variation in lesiondiameter was explained by the first two PCs, with results of thescore plot (Fig. 3C) and the loading plot (Fig. 3D) being similar tothe results for 2012.

4. Discussion

4.1. Genetic control of blue mold susceptibility

Orchard management and postharvest procedures apparentlyhave a profound impact on the prevalence of storage diseases inapple (Tahir et al., 2008, 2009; Tahir and Nybom, 2013). A stronginfluence from, e.g., the timing of harvesting has thus beenreported; a late harvest results in substantially more fungaldamage compared to earlier harvesting of the same cultivar (Bassand Birchler, 2012). Nevertheless, substantial variation in cultivarsusceptibility to fungal storage diseases also occurs but the geneticbackground is largely unknown. Major genes providing resistanceto such diseases have not yet been identified in apple, butquantitatively inherited traits associated with chemical contents,fruit texture, structure of the fruit epidermis and ripeningbehavior, appear to have a significant impact on the ability towithstand fungal attacks (Prusky et al., 2004; Blazek et al., 2007;Nybom et al., 2008b).

In a previous study on the genetic control of blue moldresistance in 92 apple cultivars, lesion diameter was positively

affected by rate of fruit softening during cold storage andnegatively affected by maturation time (i.e. number of daysbetween harvest of the current cultivar and harvest of the earliestripening cultivar in the study) and firmness at harvest (Ahmadi-Afzadi et al., 2013). A partial least squares discriminant analysisshowed that 40% of the genetic variation could be explained bythese variables with maturation time being the most important. Inaddition to firmness and softening, factors like amount and type ofskin color, cuticular waxes and chemical contents have beenproposed to affect resistance to fungal storage diseases butexperimental results have, overall, been rather inconclusive(Spotts et al., 1999; Biggs and Miller, 2001; Blazek et al., 2007;Jurick et al., 2011; Ahmadi-Afzadi et al., 2013). Chemical changes inthe fruit like organic acids degradation and acidification (Pruskyet al., 2004; Vilanova et al., 2014a) or accumulation of polyphenolsin response to fungal attack (Mikulic-Petkovsek et al., 2009, 2011;Schovankova and Opatova, 2011) have been proposed to play animportant role in disease resistance.

4.2. Titratable acidity and malic acid

Contents of total titratable acidity and malic acid showed largevariation across cultivars in either year. Comparison of control andinoculated fruits indicated a decline in the TTA contents of fleshsamples whereas an increase was obtained for the peel samples.The MA content was lower in inoculated fruit for both flesh andpeel samples. Vilanova et al. (2014a) have reported that a generalacidification occurs in apples that have been inoculated with P.expansum. They also showed that inoculated fruits have lower

M. Ahmadi-Afzadi et al. / Postharvest Biology and Technology 110 (2015) 173–182 181

contents of malic acids than control fruits, and therefore proposedthat this acidification is not influenced by the malic acid contents.In other studies, acidification of fruits has been related to thegluconic acid production by the fungus which acts as an activatorfor fungal transcription of polygalacturonase (Prusky et al., 2004;Hadas et al., 2007; Barad et al., 2012).

Results of correlation analyses do not indicate a strongassociation between TTA or MA and blue mold susceptibility.Neither naturally occurring nor induced acids due to fungalinfection, appear to influence the resistance mechanism. Never-theless, the positive and non-significant associations foundbetween the acidity level and susceptibility to blue mold indicatethat cultivars with comparatively high MA and TTA, i.e., lower pH,most likely provide a better substrate for the fungus. This is inaccordance with an enhanced development of P. expansum onfruits with lower pH, and a reduction of decay by local treatmentwith NaHCO3 (Prusky et al., 2004).

4.3. Polyphenols

Polyphenolic compounds constitute a large family of chemicalswith many human health benefits as well as a role in the defensemechanisms of plants (Grayer and Kokubun, 2001; Lattanzio et al.,2006). The contents of both total phenols and individual phenoliccompounds were found to vary widely across cultivars. In addition,total phenol concentration was 4–32 times (depending on cultivar)higher in peel samples than in samples of fruit flesh. This finding isin accordance with previous studies (Escarpa and Gonzalez, 1998;Khanizadeh et al., 2008; Roen et al., 2009; Schovankova andOpatova, 2011).

Total phenolic contents were usually lower in inoculated fruitscompared to control fruits, both when flesh and peel samples wereanalyzed. In a previous study, Schovankova and Opatova (2011)reported that TPH started to increase shortly after inoculation,followed by a decrease seven days later. In the flesh samples of bothcontrol and inoculated fruits, PLS results revealed that TPH andPB2 had the largest positive impact on resistance to blue mold.When instead peel samples were analyzed, flavonols (differentquercetin compounds) followed by TPH and PB2 had the largestpositive impact on disease resistance. The positive association ofthese chemical compounds in the control samples (samples thatwere only wounded but not been inoculated) with the level ofresistance shows that concentration of pre-formed polyphenoliccompounds may inhibit or decrease the development of disease infruits upon fungal attack.

A contribution of polyphenolic compounds to the plant defensesystem against apple scab disease has been reported in severalstudies (Mayr et al., 1997; Mikulic-Petkovsek et al., 2008, 2011;Slatnar et al., 2012). Moreover, production of apple polyphenolsmay be initiated by activation of phenylalanine-ammonia lyase(PAL) due to fungal attack (Lattanzio et al., 2006; Mikulic-Petkovsek et al., 2011). In another study, the activity of PALenzyme was strongly correlated to the content of total phenols thatwere induced shortly after the infection by P. expansum (Scho-vankova and Opatova, 2011).

Interestingly, results of correlation analysis of individualphenols with resistance showed that the association of flavonols(different quercetins) and procyanidin B2 is stronger in inoculatedfruits than in control fruits. The stronger associations forinoculated fruits indicate that the disease development mayinduce or trigger the defense system and alter the production ofthese compounds thereby limiting or preventing the decaydevelopment. As previously reported, chemical compounds couldbe produced or accumulate in higher concentration after attack byapple scab (Picinelli et al., 1995; Lattanzio et al., 2006; Mikulic-Petkovsek et al., 2008, 2009, 2011). Schovankova and Opatova

(2011) have shown that the phenol content increased in applefruits when inoculated with P. expansum followed by a decline afterone week (Schovankova and Opatova, 2011). Additionally, appli-cation of quercetin has been shown to prevent both incidence ofblue mold decay as well as patulin production for two applecultivars, i.e. ‘Golden Delicious’ and ‘Granny Smith’ (Sanzani et al.,2009). In another study, Sanzani et al. (2010) showed thatquercetin can provide resistance to P. expansum in apples, byincreasing the transcription level of genes involved in metabolicprocesses.

Based on the present study, it can be concluded thatpolyphenolic compounds in apple fruit contribute to theirresistance against blue mold. Moreover, the level of resistanceto fungal infection appears to vary considerably among differentcultivars. The importance of the phenolic compounds like flavonolsand procyanidin B2 is especially noticeable in the peel samples,suggesting that the spread of the fungus to a large extent dependson peel chemistry. Contents of malic acids or total titratable acidity,in either flesh or peel, had much lower impact on the resistance ofapple fruits to blue mold compared to the polyphenoliccompounds. These findings could be applied in breeding programsby selecting cultivars that contain higher level of above-mentionedphenolic compounds in order to improve the level of resistance inapple cultivars. In addition, development of DNA markers linked tothese chemical compounds could assist breeders in selectingcultivars with higher level of resistance to blue mold.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.postharvbio.2015.08.008.

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