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Analysis of different European hazelnut (Corylus avellana L.) cultivars: authentication, phenotypic features and phenolic profiles Loredana Filomena Ciarmiello, Maria Fiorella Mazzeo, Paola Minasi, Angela Peluso, Antonio De Luca, Pasquale Piccirillo, Rosa Anna Siciliano, and Virginia Carbone J. Agric. Food Chem., Just Accepted Manuscript • Publication Date (Web): 13 Jun 2014 Downloaded from http://pubs.acs.org on June 19, 2014
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Journal of Agricultural and Food Chemistry
Analysis of different European hazelnut (Corylus avellana L.) cultivars: authentication, phenotypic features and phenolic profiles
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Loredana F. Ciarmiello#^, Maria F. Mazzeo§^, Paola Minasi§, Angela Peluso§, Antonio De Luca#, Pasquale Piccirillo#, Rosa A. Siciliano§*, Carbone Virginia§
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#
Consiglio per la Ricerca e la Sperimentazione in Agricoltura – Unità di Ricerca per la
Frutticoltura (Fruit Tree Research Unit), Via Torrino, 3- 81100 Caserta, Italy §
Centro di Spettrometria di Massa Proteomica e Biomolecolare, Istituto di Scienze
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dell’Alimentazione del Consiglio Nazionale delle Ricerche, Via Roma, 64 – 83100 Avellino,
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Italy
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^ These authors equally contributed to the present paper
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*Corrisponding author:
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Rosa Anna Siciliano
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Istituto di Scienze dell’Alimentazione del CNR
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Via Roma 64, 83100 Avellino-Italy
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Tel.: +39-0825-299363 Fax: +39-0825-781585
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e-mail:
[email protected].
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ABSTRACT
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Hazelnuts exhibit functional properties due to their content in fatty acids and phenolic
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compounds that could positively affect human health. Food industry requires precise traits for
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morphological, chemical and physical kernel features so that some cultivars could be more suitable
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for specific industrial processing. In this study, agronomical and morphological features of 29
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hazelnut cultivars were evaluated and a detailed structural characterization of kernel polyphenols
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was performed, confirming the presence of protocatechuic acid, flavan-3-ols such as catechin,
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procyanidin B2, six procyanidin oligomers, flavonols and one dihydrochalcone in all the analyzed
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cultivars.
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In addition, an innovative methodology based on the MALDI-TOF mass spectrometric analysis
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of peptide/protein components extracted from kernels was developed for the authentication of the
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most valuable cultivars. The proposed method is rapid, simple and reliable, and holds the potential
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to be applied in quality control processes. These results could be useful in hazelnut cultivar
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evaluation and choice for growers, breeders and food industry.
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KEYWORDS: European hazelnut, bio-agronomical characterization, polyphenols, MALDITOF-MS, cultivar authentication
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INTRODUCTION
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European hazelnut (Corylus avellana L.) is a diploid (2n = 2x = 22), monoecious, open
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pollinated tree. It has self-incompatibility, due to negative chemical interaction between pollen and
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style tissue, which enforces cross-pollination.1
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Hazelnut kernels are rich in fats, proteins, and vitamins, and play a relevant role in the agricultural
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market, mainly because of their use to provide flavour in dairy, bakery, confectionery, candy, and
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chocolate products. In fact, However, the aroma is considered to be among the primary
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determinants of nut quality and is improved by the roasting process. Therefore, the majority of the
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world hazelnut crop is roasted, thus developing a unique aroma that depends on the cultivar used
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and on the roasting conditions applied. The volatile profiles of fresh and roasted products were
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characterized by integrating sensory evaluation, Nuclear Magnetic Resonance (NMR), High-
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Resolution Gas Chromatography-Olfactometry (HRGC-O), High-Resolution Gas Chromatography-
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Mass Spectrometry (HRGC-MS), Two-Dimensional Gas Chromatography-Mass Spectrometry.2
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More recently a new discipline, named sensomics has been introduced that was aimed to perform a
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quantitative analysis of the entire set of aroma compounds of a given food, thus defining its
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sensometabolome. This methodology was applied to the analysis of odorant compounds in raw and
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roasted hazelnuts of different cultivars.3,4
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European hazelnut is one of the most cultivated nut crops worldwide. This species spread from
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Asia Minor and Caucasus region to Europe and North Africa. Italian hazelnut production is 85.232
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tons yearly for in-shell product.5 Particularly, Campania, Lazio, Piemonte and Sicilia account for
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98% of the national production. About 90% of the world crop is sold as kernels and processed in
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food industry (i.e. chocolates, bakery, dairy), the remaining 10% is sold as in-shell product and
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consumed fresh, blanched or roasted.6 Food industry requires uniform high-quality nuts and precise
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morphological, chemical and physical kernel characteristics, as well as absence of defects.7,8
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European hazelnut includes several cultivars, biotypes and accessions and many of these come from 3
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Europe and Turkey. These cultivars show a high level of genetic diversity for traits such as vigour,
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growth habits, suckering, nut size and shape and shell thickness.1 Cultivars more used in food
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industry are Tonda Gentile delle Langhe, also named Tonda Gentile Trilobata, Tonda Gentile
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Romana, Tonda di Giffoni, S. Giovanni, Mortarella and Riccia di Talanico, cultivated in Italy;
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Tombul, Sivri, Palaz and Fosa, cultivated in Turkey; Negret and Pauetet produced in Spain. Among
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Italian cultivars, Tonda di Giffoni and Tonda Gentile delle Langhe gained the Protected
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Geographical Indication (PGI) European marks ‘‘Nocciola di Giffoni’’ and “Nocciola Piemonte”,
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respectively. These cultivars are particularly appreciated for their agronomic traits such as
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resistance to pathogens and pests, round kernels of excellent quality, consistent yields, and for their
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processing qualities such as sweetness, low burnt aroma and cooked bread aroma.9,10 Other minor
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Italian cultivars such as Tonda bianca, Tonda rossa, Camponica and Riccia di Talanico are mainly
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destined to be sold in shelled form as snacks for direct consumption (fresh consumption).7,11 USA
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production, especially that from Oregon, is principally destined to fresh consumption and only
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recently has been directed to industrial use.12
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Hazelnut consumption may have positive influence on human health,13,14 as kernels are rich in
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unsaturated fatty acids (i.e. oleic, palmitic, stearic, linoleic and linolenic acids)15 and in α-
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tocopherol (vitamin E) and polyphenols.16,17 Furthermore, the presence of Fe, Zn and Cu, and a high
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K/Na ratio, make hazelnut interesting for human diets, and especially for electrolyte balance.17 The
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bioaccessibility of essential and toxic elements in hazelnut kernels has been also evaluated.18
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In this context, the analysis of nut and kernel phenotypic traits and polyphenolic content could
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lead to define genotype specific features, providing information useful to growers, breeders and
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food industry for cultivar evaluation and choice. The agronomical and morphological features of 29
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hazelnut cultivars originated from different geographical area were characterized in this study. In
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addition, a comprehensive study of the phenolic composition of extracts from hazelnut kernels was
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conducted. 4
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The authentication of different cultivars is also crucial in the definition of hazelnut quality.
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Traditional methods to identify hazelnut cultivars were based on phenotypic observations that may
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be affected by environmental and developmental factors, making cultivar differentiation difficult.
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Therefore, the development of innovative analytical methodologies that could suitably integrate
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well-established protocols for cultivar authentication is clearly desirable. DNA-typing methods such
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as Random Amplification of Polymorphic DNA (RAPD), Inter-Simple Sequence Repeat (ISSR),
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Restriction Fragment Length Polymorphism (RFLP), Amplification Refractory Mutation System
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(ARMS-PCR) and Simple Sequence Repeat (SSR) were known to be useful for revealing genetic
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polymorphisms among different cultivars and accurately identifying hazelnut cultivars. However,
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these methods were laborious and time consuming and were mainly applied on leaf material.19-21
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Other approaches used for hazelnut cultivars identification were based on the analysis of volatile
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constituents and metabolites using chromatographic and/or spectroscopic techniques such as gas
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chromatography coupled to mass spectrometry (GC-MS)22 and NMR10,23 as well as on the analysis
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of trace elements such as lanthanides by means of inductively coupled plasma-mass spectrometry
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(ICP-MS).24 In addition, a few papers describe the application of molecular profiling strategies
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based on Matrix-Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry
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(MALDI-TOF-MS) in food science25,26 and novel methodologies have been developed for
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authentication and detection of frauds in different food matrices.27,28 In this study, a similar
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approach has been developed, based on the MALDI-TOF-MS analysis of the peptide/protein
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fraction extracted from kernels, and, for the first time, has been applied to hazelnut cultivars
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authentication.
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MATERIALS AND METHODS
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Plant material
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Twenty-nine hazelnut cultivars originating from different geographical areas were used (Table
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1). Three plants per cultivar were maintained in the same agronomical and pedo-climatical
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conditions, in the Fruit Tree Research Unit’s collection field (CRA-FRC) located in Pignataro
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Maggiore (Caserta province, Italy). All plants were about seven year old.
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Chemicals
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High Performance Liquid Chromatography (HPLC) grade methanol, HPLC grade acetonitrile
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and formic acid were obtained from Merck (Darmstadt, Germany). HPLC grade n-hexane and
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chloroform were obtained from Carlo Erba (Milan, Italy). Gallic acid, protocatechuic acid,
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quercetin-3-O-rhamnoside (quercitrin), phloretin-2’-O-glucoside (phloridzin), myricetin, sodium
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carbonate, Folin Ciocalteau’s reagent, sinapinic acid and ribonuclease A (Rnase A) and
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trifluoroacetic acid (TFA) were purchased from Sigma Chemical Company (St. Louise, MO, USA).
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(+)-catechin, procyanidin B2, myricetin-3-O-rhamnoside (myricitrin) were purchased from
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Extrasynthese (Genay, France). HPLC grade water (18.2 mΩ) was prepared using a Millipore Milli-
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Q purification system (Millipore Corp., Bedford, MA, USA).
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Agronomical and pomological characterization
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Agronomical and pomological traits were evaluated for each cultivar for three years (2010-
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2012), according to the guidelines provided by Bioversity International in the “Descriptor for
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Hazelnut”.29 The investigated plants were taken from the Fruit Tree Research Unit’s collection field
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(Pignataro Maggiore-Caserta, Campania, South Italy). Nut samples from the selected cultivars were
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collected at the ripening time optimum for each cultivar, i.e. when nut falling, observed at maturity,
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occurred.29 Nut samples were dried at 43°C to prevent quality deterioration and rancidity, frozen
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with carbon dioxide to destroy insect pests and stored according to good handling practices in clean,
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closed vials at room temperature. Twelve standard descriptors were evaluated.29 Agronomical traits, 6
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such as growth habit, vigour and suckering, were evaluated on three plants per cultivar.
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Pomological traits, such as nut shape, nut weight, kernel weight and yield, were estimated on 50
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nuts per cultivar for each year (Table 1). These characters were monitored following previously
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reported guidelines.30,31 The percentage of pellicle removal were estimated after blanching kernels
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at 115°C for 20 min and skin was removed by mechanical brushing.32
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Sample treatment and polyphenol extraction
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Kernels (with skin) were ground with an electric blender and, for each cultivar, 5 g of these
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samples were defatted three times with 10 mL of n-hexane, with the help of an ultrasonic bath, and
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then filtered through filter paper. The defatted samples were extracted with 15 mL of methanol in
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an ultrasonic bath for 60 min. Extracts were then dried in rotary evaporator (LaboRota 4000 /HB
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Efficient, Heidolph, Schwabach, Germany) and stored at -20°C until analysis.
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HPLC-UV Analysis
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Extracts from different hazelnut cultivars were analyzed by HPLC-UV using a HP 1110 Series
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HPLC (Agilent, Palo Alto, CA, USA) equipped with a binary pump (G-1312A) and an UV detector
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(G-1314A). Compounds were separated on a XBridge BEH C18 Column (130Å, 5 µm, 4.6 mm x
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150 mm) (Waters, Milford, MA, USA) at a flow rate of 1 mL/min; solvent A was 0,1% formic acid
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and solvent B was 0,1% formic acid in acetonitrile. After a 8 min hold at 2% solvent B, elution was
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performed according to the following conditions: from 2% (B) to 35% (B) in 42 min, from 35% (B)
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to 95% (B) in 2 min, followed by 10 min of maintenance. Extracts were reconstituted in HPLC
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solvent A prior to injection into the HPLC and chromatograms were acquired at 280 nm. Standard
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curves for each polyphenol standard were prepared over a concentration range of 2,5–30 µg/mL
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with five different concentration levels and duplicate injections at each level. Peak area ratios
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between the areas of each polyphenol standard and those of myricetin, used as internal standard, 7
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were calculated and plotted against the corresponding standard concentration, using weighed linear
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regression to generate standard curves. All samples were prepared and analyzed in duplicate.
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Results were expressed as mg/Kg of fresh weight (FW).
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ESI-ITMSn analysis
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Identification of phenolic compounds present in the different HPLC separated fractions was
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carried out by electrospray ionisation multistage ion trap mass spectrometry (ESI–ITMSn) using a
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Finnigan LCQ DECA XP Max ion trap mass spectrometer (Thermo Finnigan, San Josè, CA, USA)
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equipped with Xcalibur® system manager data acquisition software (Thermo Finnigan, San Josè,
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CA, USA). Mass spectra were recorded from mass/charge (m/z) 50 to 1200 in negative ionization
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mode. The capillary voltage was set at -10 V, the spray voltage was at 3.0 kV and the tube lens
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offset was at -10 V. The capillary temperature was 275°C. Data were acquired in MS, MS/MS and
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MSn scanning mode.
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Statistical analysis
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Data were analyzed in the R environment33, using Packages FactoMineR34, ade435 and ggplot236
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(R version 3.1.0). R is a software environment for statistical computing and graphics that provides a
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wide variety of statistical (linear and nonlinear modelling, classical statistical tests, classification,
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clustering, etc.) and graphical techniques. FactoMineR is a package dedicated to multivariate data
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analysis. The main features of this package is the possibility to take into account different types of
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variables (quantitative or categorical), data structures and supplementary information34. The ade4
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package (Data Analysis functions to analyse Ecological and Environmental data in the framework
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of Euclidean Exploratory methods) is dedicated to multivariate analyses for the identification and
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the understanding of structures of ecological communities35. Finally, ggplot2 is a data visualization
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package for the statistical programming language R36. 8
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Individual and total polyphenol content as well as nut shape (length/width) and kernel weight
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were used for cultivar ordination by clustering. Other traits (kernel yield, growth habit, plant vigour,
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plant suckering and bud break) were introduced as supplementary variables. A range score was
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calculated in order to make comparable variables with different ranges and to focus on distributions.
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Range score values for n (x) are obtained as the ratio between each value (x) minus the minimum
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and the difference between maximum and minimum: [X - min (x)] / [max (x) - min (x)] for x from 1
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to n. Score distributions were summarized in quartiles for graphical presentation. Hierarchical
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clustering was performed on principal components using euclidean distances with the complete-
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linkage method.
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Extraction of the protein fraction
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0.06 g of ground kernels (with skin) were suspended in 0.8 mL of chloroform and vortexed for 5
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min. 0.8 mL of 0.1% TFA, containing 1% protease inhibitor cocktail (Sigma, St. Louise, MO,
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USA), was added and protein extraction was carried out for 5 min. The mixture was then
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centrifuged for 10 min at 13000 rpm and the aqueous fraction was recovered. Protein concentration
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was determined using the Bradford method.37
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MALDI-TOF-MS analyses and mass spectra processing
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Two separated aliquots (0.2 µg) of the protein extract were concentrated and desalted by solid
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phase extraction using µZipTipC18 tips (Millipore, Billerica, MA, USA). Tips were washed and
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equilibrated with 0.1% TFA and eluted in 1 µL of sinapinic acid (10 mg/mL in 0.1%
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TFA/acetonitrile (1:1 v:v), containing 1 pmol/µL of Rnase A) used as matrix for MALDI-TOF-MS
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analyses. Three spectra were acquired from each well, so that six mass spectra were generated for
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each sample.
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MALDI-TOF-MS analyses were carried out on a Voyager DE PRO mass spectrometer (AB
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SCIEX, Foster City, CA, USA) operating in linear positive-ion mode. Mass spectra, acquired in the
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m/z range 3500-15000, were calibrated using the average peaks (doubly charged ion at m/z 6841
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and singly charged ion at m/z 13682) originated from the internal standard Rnase A. Mass spectra
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were processed and transformed in a list containing the m/z values of all the signals and the
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corresponding intensity, using the DataExplorer 5.1 software (AB SCIEX).
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Peak intensities were normalized by considering 100 the intensity of the most intense signal in
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the mass spectrum and signals having intensity < 2% were excluded from the peak list. For each
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cultivar, peak lists obtained from the six mass spectra were aligned along the m/z axis using the
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NEAPOLIS software developed in-house (www.bioinformatics.org/bioinfo-af-cnr/NEAPOLIS).38
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The threshold value to align signals was fixed to 1000 ppm, so that, among the aligned signals, the
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minimum and maximum m/z values differed for < 1000 ppm. Signals present in at least four of the
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six replicate mass spectra were included in the mean peak list. This processing allowed calculating
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the mean m/z value and the corresponding mean intensity for each signal, leading to the mean peak
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list of each cultivar. Mean peak lists from all the hazelnut cultivars were further aligned by
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NEAPOLIS to obtain the total dataset. Data processed by NEAPOLIS were subjected to a visual
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inspection to resolve any mass spectral ambiguities.
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RESULTS AND DISCUSSION
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Plants used in the present study (twenty nine cultivars) were grown in the CRA-FRC collection
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field and some of them were phenotypically and genetically characterized in previous studies.1,39 In
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addition, as plants were grown in the same field, the effects of agronomical and pedo-climatical
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conditions on fruit characteristics were minimized and it could be assumed that the reported results
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are mainly related to differences in genetic traits of the cultivars.
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Bio-agronomical and pomological analysis
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According to the guidelines provided by Bioversity, twelve agronomical and pomological traits
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were selected to describe the 29 hazelnut cultivars.29-31 The selected traits represent well defined
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characteristics of economic interest and, consequently, could act as target traits for selection by
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growers, breeders and food-processing industry. Agronomical and pomological traits are depicted in
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Table 1.
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Significant differences among cultivars were observed for all the examined nut and kernel traits.
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Pellicle removal, one of the most important practice for nut quality preservation, was evaluated after
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roasting.40 Percentage of pellicle removal ranged from 19.6% for Grifoll to 87.5% for Tonda di
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Giffoni. Other cultivars that showed good score for pellicle removal (value higher than 55%) were
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Avellana sp, Barcelona, Fructo Rubro, Montebello, Napoletana II, Riccia di Talanico, S. Maria del
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Gesù, Segorbe, Sivri, Tonda Romana and Willamette. The most common shapes were short sub-
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cylindrical (24.14%) and sub-spherical (31.03%). The kernel yield ranged from 37.5% for Locale di
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Piazza Armerina to 50% for Tonda di Giffoni. Apolda, Barcelona, Fructo Rubro, Ghirara,
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Nocchione, Royal, Tonda di Giffoni and Tonda Gentile Romana were characterized by higher nut
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weights, associated with kernel yield higher than 40% and lower than 50%, and Tonda di Giffoni
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showed the highest kernel yield (50%) (Table 1). In particular, Barcelona, Tonda di Giffoni and
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Tonda Gentile Romana showed high kernel yield and sub-spheroidal nut shape that are the most
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important traits required by the food-processing industry, as also reported by Cristofori et al.41
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Identification and quantification of polyphenols and their correlation with agronomical and pomological traits
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The polyphenol fraction of each cultivar was analyzed by HPLC. The characterization of
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phenolic compounds was carried out by ESI–ITMSn. Identification was achieved on the basis of
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pseudomolecular [M-H]- ions, together with the interpretation of their collision induced dissociation 11
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(CID) fragments. When authentic standards were available, identification was conducted by
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comparing retention times and MSn fragmentation spectra with those of standards. Twelve
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compounds were characterized and the classes of polyphenols detected were in agreement with
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those already reported in previous studies on phenolic composition of hazelnut.42,43 As an example,
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the HPLC chromatogram of hazelnut extract (Grossal cultivar) recorded at 280 nm is shown in
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Figure 1 and the list of compounds identified in the polyphenol hazelnut extract of Grossal cultivar
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is reported in Table 2.
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Total and individual polyphenol content of each cultivar is summarized in Figure 2 and in
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Supplementary Table 1. The total polyphenol content varied among the different cultivars and
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ranged from 84.80 ± 3.10 mg/Kg of FW in Fructo Rubro to 32.29 ± 0.11 mg/Kg of FW in Cosford.
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ESI-ITMSn identification of individual phenolics in the different hazelnut extracts confirmed the
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presence of protocatechuic acid, flavan-3-ols such as catechin, procyanidin B2, six procyanidin
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oligomers (three other unidentified procyanidin dimers (indicated as D1, D2, D3), and three
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unidentified procyanidin trimers (indicated as T1, T2, T3)), flavonols (quercetin-3-O-rhamnoside
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and myricetin-3-O-rhamnoside) and one dihydrochalcone (phloretin-2-O-glucoside) in all the
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analyzed cultivars. Among the detected flavonols, quercetin-3-O-rhamnoside was present in highest
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content in whole kernels, ranging from 1.89 ± 0.04 mg/Kg of FW in Cosford to 6.62 ± 0.42 mg/Kg
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of FW in Jeans (Supplementary Table 1).
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Based on kernel polyphenolic content, cultivars were divided in six clusters and this division
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reflected the clustering obtained by correlating the total polyphenolic content with the agronomical
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and pomological features (Fig. 2 and 3).
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Some agronomical and pomological features, such as kernel weight and yield, nut shape (as
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length/width ratio), plant vigour, suckering, bud break and growth habit were summarized and
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correlated to total polyphenol content in kernels (Fig. 3). A negative correlation between nut shape
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and kernel weight and yield was observed, as well as plant vigour and suckering were negatively 12
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correlated with kernel weight and yield. Tonda di Giffoni and Riccia di Talanico showed the higher
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kernel yield, while the higher total polyphenol content was registered in Riccia di Talanico, Tonda
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Gentile Romana, Fructo Rubro and Ghirara (Fig. 3, Supplementary Table 1). Based on these
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features, cultivars can be divided in six clusters:
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- cluster 1 containing cultivars with small, elongated nuts and low polyphenol levels (Table 1, Fig. 3). In this cluster Willamette was the most typical and Cosford was the most specific;
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- cluster 2 containing 9 of the 29 cultivars with high vigour, erect branches, low kernel yield,
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low levels of procyanidin trimer (T3), phlorizin, procyanidin dimer (D3) and quercetin (Table 1,
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Fig. 2 and 3, Supplementary Table 1). In this cluster, Napoletana II was the most typical and Royal
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was the most specific;
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- cluster 3 including cultivars with round nuts and high kernel weight (Table 1, Fig. 3). In this
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cluster Barcelona was the most typical and Apolda was the most specific, Tonda di Giffoni showed
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the better combination of features of this cluster (Fig. 3);
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- cluster 4 including cultivars whose nuts showed high levels of quercetin, catechin and
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procyanidin trimer (T3) (Fig. 2, Supplementary Table 1). In this cluster, S. Maria del Gesù was the
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most typical and Jeans was the most specific;
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- cluster 5 containing two cultivars, Tonda Romana and Riccia di Talanico, that showed high
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kernel yield and high levels of phlorizin, procyanidin B2, procyanidin dimer (D2) and trimer (T2)
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(Fig. 2 and 3, Supplementary Table 1);
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- cluster 6 including two cultivars, Ghirara and Fructo Rubro, whose nuts showed the higher
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total polyphenols content and high levels of myricitrin, catechin, protocatehuic acid, procyanidin B2
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and procyanidin dimers (D2) and (D3) (Fig. 2, Supplementary Table 1).
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In order to better observe the relationship among traits of the hazelnut cultivars, a dendrogram
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based on Euclidean distances was constructed (Fig. 4). Clustering cannot be related to geographical
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origin of cultivars. This is likely due to plant species domestication that resulted in a narrowing of 13
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the gene pool.44 Two major clusters were recognized; about 67% of cultivars included in cluster 1
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originated from Italy, while the others had different geographic origin (see Table 1). Cluster 2 was
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composed by European cultivars, excepted for Fructo Rubro, a cultivar originated from Turkey
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(Fig. 4). The two clusters reflected cultivar features such as kernel weight and yield, nut shape and
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polyphenols content. Cultivars included in cluster 2 showed higher polyphenols content than those
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included in cluster 1, but lower kernel yield, except for Tonda Gentile Romana and Riccia di
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Talanico (Table 1, Fig. 2, 3 and 4).
330 331
MALDI-TOF-MS analyses and mass spectra processing
332
The present study was also aimed to develop an innovative strategy based on the MALDI-TOF-
333
MS suitable for discriminating different hazelnut cultivars. The applicability of the method was
334
ascertained by analyzing the 29 selected cultivars. Protein extracts from kernels were analyzed by
335
MALDI-TOF-MS and mass spectra were acquired in the m/z range 3500-15000 in linear positive-
336
ion mode, as no significant peaks were detected outside the selected m/z range (data not shown).
337
The mass spectrum obtained from the analysis of Tonda di Giffoni is shown in Figure5.
338
The 29 mean peak lists were aligned by the NEAPOLIS software and a dataset that included
339
about 270 m/z values and their corresponding mean intensity was thus generated. This dataset
340
highlighted a high variability in the molecular profile of different samples. To increase data
341
reliability, m/z values having mean intensity less than 10% in all the cultivars were excluded from
342
this dataset. Unfortunately, only a few signals had intensity higher than 10% in the mean peak lists
343
of Grossal and Willarmette. Therefore, these cultivars were not further included in this analysis.
344
Four intense signals in the m/z range 6000-7000 (m/z 6825.3, 6547.9, 6209.0, 6080.5) were
345
present in the acquired molecular profiles, regardless of the cultivar (Supplementary Table 2, Fig.
346
5). Interestingly, these signals were absent in the mass spectra of protein extracts from walnuts,
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peanuts and almonds (data not shown). Therefore, it could be suggested to consider this cluster as a
348
specific signature of hazelnut presence in nut mixtures or in nut containing products.
349
Furthermore, a signal at m/z 9468.3 was present in the mean peak lists of twenty cultivars and it
350
could be originated from the nonspecific-lipid transfer protein (ns-LTP), also called Cor a 8
351
(theoretical molecular weight 9468.0 Da), described as one of the predominant hazelnut allergens
352
(Fig. 5). Due to the presence of four disulphide bridges, the protein structure of ns-LTPs is
353
particularly stable and resistant to proteolysis, harsh pH changes, or thermal treatments.45 As these
354
proteins are usually not affected by technological processes, they have been also proposed as
355
biomarkers for in vitro diagnosis of potentially severe hazelnut allergy.46
356
The main goal of the molecular profiling analyses was to discriminate the analyzed cultivars.
357
Specific signals among the ones having the highest mean intensity for at least one cultivar (>10%)
358
were selected as putative biomarkers, thus leading to the dataset of 35 signals reported in
359
Supplementary Table 2. Due to the high specificity of the acquired molecular profiles, the 27
360
different hazelnut cultivars could be unambiguously discriminated on the basis of specific
361
biomarker patterns (presence and/or absence of m/z values). The obtained data could be also used
362
for the identification of unknown samples.
363
In this context, in order to automate the authentication method, a four-step process that used the
364
NEAPOLIS software was set up, as reported in the flow chart (Fig. 6). As first, the mean peak list
365
of a putative unknown sample should be aligned with a list containing the selected biomarkers of
366
each cultivar of Group I using 500 ppm as threshold for aligning values (Sheet Group I in
367
Supplementary File 1) and 2 as the minimum number of aligned signals. This step would allow us
368
to rapidly identify the unknown sample (if it is one of these twelve cultivars) on the basis of a
369
biomarker pattern including from two to five signals, as indicated in Supplementary File 1. In case
370
the identification would not been achieved, as following steps, this process should be reiterated
371
using the lists of Group II (that is defined based on the presence of the m/z value 3661, Sheet Group 15
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II in Supplementary File 1), Group III (whose peculiar features were the absence of the m/z value
373
3661 and the presence of the m/z value 14345, Sheet Group III in Supplementary File 1), Group
374
IIIA (that included Nociara and Locale Piazza Armerina, Sheet Group IIIA in Supplementary File
375
1) and Group IV (whose peculiar feature was the absence of the m/z values 3661 and 14345, Sheet
376
Group IV in Supplementary File 1). It is worth stressing that the biomarker dataset could be easily
377
updated as more mass spectrometric data on other cultivars will be gathered and bioinformatic tools
378
could be further developed to simplify and speed the identification process.
379
In conclusion, although the analysis of a larger number of cultivars of different geographic
380
origins could further validate the method, these results clearly highlight that the developed
381
molecular profiling strategy, is able to discriminate hazelnut cultivars and strongly suggest the
382
applicability of the method to the analysis of other foods of plant origin. Furthermore, as the method
383
is rapid, simple and reliable, it holds the potential to be routinely applied in quality control
384
processes.
385 386
ABBREVIATIONS
387
ESI–ITMSn, electrospray ionisation multistage ion trap mass spectrometry; FW, fresh weight;
388
HPLC, high performance liquid chromatography; MALDI-TOF-MS, matrix-assisted laser
389
desorption-ionization time-of-flight mass spectrometry; m/z, mass/charge; Rnase A, ribonuclease
390
A; TFA, trifluoroacetic acid
391 392
ACKNOWLEDGEMENTS
393
The authors are grateful to dr. Filippo Piro (C.R.A.-Research Institute of Horticolture,
394
Pontecagnano, Italy) for improving the manuscript.
395 396
SUPPORTING INFORMATION 16
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Supplementary Table 1: Concentration of individual and total polyphenolics determined by
398
HPLC (mg/Kg of FW) extracted from different hazelnut cultivars. Results were expressed as
399
average (mean) concentration ± SD of duplicate (HPLC method).
400
Supplementary Table 2: Dataset obtained from the MALDI-TOF-MS molecular profiles of the
401
protein fraction extracted from the 27 cultivars. Specific signals among the ones having the highest
402
mean intensity for at least one cultivar (>10%) were included in the dataset. The mean intensity
403
values of signals selected as biomarkers are indicated in red.
404
Supplementary File 1: Lists containing the selected biomarkers of cultivars included in the
405
defined Groups. The lists, as reported can be directly uploaded in the NEAPOLIS software, together
406
with the list of an unknown sample to achieve cultivar identification. The absence of signals at m/z
407
3661 and 14345 is crucial for discriminating the different groups.
408
This material is available free of charge via the Internet at http://pubs.acs.org
409
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411
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42. Jakopic, J.; Petkovsek, M.M.; Likozar, A.; Solar, A.; Stampar, F.; Veberic, R. HPLC-MS
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Recombinant lipid transfer protein Cor a 8 from hazelnut: a new tool for in vitro
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diagnosis of potentially severe hazelnut allergy. J. Allergy Clin. Immunol. 2004, 113,
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141-147.
548 549
FUNDING SOURCES
550
This work was supported by a dedicated grant from the Italian Ministry of Economy and
551
Finance to CNR and ENEA for the Project “Innovazione e Sviluppo del Mezzogiorno e Conoscenze
552
Integrate per Sostenibilità ed Innovazione del Made in Italy Agroalimentare (CISIA)” Legge
553
n.191/2009. This work has been also supported by Regione Campania in the framework of the
554
“Rete di Spettrometria di Massa della Campania” (RESMAC).
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FIGURE CAPTIONS
558
Figure 1. HPLC chromatogram of hazelnut extract (Grossal cultivar) recorded at 280nm. Peaks
559
are labelled according to Table 2.
560
Figure 2. Medium score for total and individual polyphenolic content in kernels. Parameters are
561
sub-divided in four quartiles, depicted with different colours: white (lower quartile), light grey
562
(second quartile), dark grey (third quartile) and black (upper quartile).
563
Figure 3. Medium score for morphological and pomological traits combined with total
564
polyphenolic content in kernels. Parameters are sub-divided in four quartiles, depicted with
565
different colours: white (lower quartile), light grey (second quartile), dark grey (third quartile) and
566
black (upper quartile).
567
Figure 4. Dendrogram depicting the relationship among different C. avellana cultivars based on
568
quantitative and qualitative features. Dendrogram was inferred using euclidean distances with
569
complete-linkage method.
570
Figure 5. MALDI-TOF mass spectrum obtained from the analysis of the protein fraction
571
extracted from kernels of the Tonda di Giffoni cultivar. The four signals present in the molecular
572
profiles of all the cultivars are indicated by dots. The signal originated from the allergen Cor a 8
573
(nonspecific-lipid transfer protein) is indicated by an asterisk.
574 575
Figure 6. Flow chart of the four-step process developed in order to automate the authentication method based on the MALDI-TOF-MS molecular profiles of the different cultivars.
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Table 1. Geographic origin and values of representative agronomic and carpological traitsa for 29 cultivars of hazelnut “Corylus avellana L.”. Phenological and carpological traits were calculated from three-yearly data. The investigated plants were from the Fruit Tree Research Unit’s collection field.
Cultivar name
Locally origin
Growth habit
Vigour
Suckering
Bud break b
Nut shape
Shell colour
Shell thickness
Nut weight (g)
Kernel weight (g)
Kernel yield (%)
Pellicle removal (%)
Kernel fibre texture
auburn light brown striated light brown brown dark brown light brown striated dark brown light brown striated
relatively thin
1.85
0.86
46.3
39.9
medium corky
medium
3.30
1.40
42.4
19.8
light corky
medium medium high high thin thin
2.12 2.28 3.30 2.16 1.36 1.55
0.91 0.88 1.50 0.89 0.57 0.69
43.1 38.6 45.5 41.5 41.9 45
65.3 40 61.1 43.5 51.3 42.3
strongly corky light corky medium corky light corky medium corky strongly corky
Amandi
Spain
intermediate
Medium-high
strong
late
sub-cylindrical short
Apolda
Italy
spreading
intermediate
strong
intermediate
sub-oval
Italy Turkey USA-Oregon France/Spain Greece England
semi-erect semi-erect intermediate spreading spreading intermediate
intermediate low intermediate medium-low intermediate medium-high
strong medium weak strong medium weak
intermediate intermediate intermediate intermediate intermediate late
Avellana sp Badem Barcelona Bearn Comen Cosford
USA
intermediate
high
weak
medium-late
Fructo Rubro
Turkey
spreading
intermediate
strong
intermediate
Ghirara Gironell Grifoll Grossal Jeans Locale di Piazza Armerina Minnolara Montebello Napoletana II Nocchione Nociara Riccia di Talanico
Italy Spain Spain Spain Italy
spreading erect spreading upright spreading
medium-high high medium-high high intermediate
strong medium strong weak strong
early early intermediate late intermediate
sub-spheroidal sub-cylindrical long sub-spherical ovate sub-cylindrical short sub-cylindrical short sub-cylindrical elongated sub-cylindrical elongated sub-elliptic sub-cylindrical short sub-cylindrical short sub-spheroidal ovate
Italy
intermediate
medium-high
strong
medium-early
Italy Italy Italy Italy Italy
intermediate spreading semi-erect intermediate intermediate
intermediate intermediate high high high
medium weak strong medium strong
intermediate late intermediate intermediate intermediate
Italy
intermediate
medium high
medium
Endrix
Royal S. Maria del Gesù Segorbe Sivri Tonda di Giffoni Tonda Gentile Romana Willamette
a
brown
medium
1.67
0.66
39.3
28
strongly corky
light brown striated
medium
2.95
1.31
44.3
60.9
strongly corky
light brown brown dark brown light brown striated brown
medium medium medium high high
2.84 1.82 1.95 2.08 2.28
1.34 0.73 0.82 0.84 0.88
47.2 41.2 42 40.3 38.6
38.4 26.3 19.6 32.3 51
medium corky medium corky medium corky medium corky light corky
elliptic
brown
high
2.22
0.83
37.5
30.6
strongly corky
elliptic ovate sub-spheroidal sub-elliptic sub-spheroidal
light brown striated light brown striated brown light brown striated light brown striated
high high high high high
2.51 2.46 2.36 2.70 2.67
1.02 1.00 0.98 1.10 1.01
40.6 40.6 41.3 40.7 38
37 61.9 61.6 31.5 48.7
medium corky medium corky medium corky strongly corky medium corky
intermediate
sub-spheroidal
auburn
thin
2.10
1.10
52.4
72.5
medium corky
USA-Oregon
erect
high
strong
intermediate
sub-cylindrical short
light brown striated
medium
3.40
1.41
41.3
51.2
stronglycorky
Italy
intermediate
medium-high
medium
intermediate
sub-elliptic
light brown
medium
2.42
0.99
41.1
56.8
medium corky
France Turkey
erect semi-spreading
very high low
medium strong
intermediate early
sub-spheroidal ovate
light brown striated brown fawn striated
relatively high relatively thin
2.00 1.41
0.76 0.67
37.9 47.8
59.5 76.3
medium corky medium corky
Italy
semi-erect
intermediate
strong
early
sub-spheroidal
brown striated
relatively thin
3.00
1.50
50
87.8
light corky
Italy
semi-erect
low
medium
early
sub-spheroidal
light brown striated
thin
2.70
1.30
48
55.3
light corky
USA-Oregon
intermediate
medium-high
strong
intermediate
sub-cylindrical short
light brown striated
medium
2.22
0.98
44.5
56.1
strongly corky
According to the “Descriptors for hazelnut (Corylus avellanaL.)”, Bioversity, FAO and CIHEAM. 2008.
b
early: < 02/28; medium-early: 03/01-03/10; intermediate: 03/11-03/20; medium-late: 03/21-03/30; late: > 03/30
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Table 2. List of compounds identified in hazelnut extract (Grossal cultivar) including corresponding HPLC retention times, quasi-molecular ions and fragment ions.
Peak
Rt (min)
[M-H]m/z
MS/MS ions m/z
1 2 3 4 5 6 7 8 9 10 11 12
11.93 19.23 20.11 20.81 21.57 22.73 25.14 25.62 25.93 30.12 33.75 37.34
153 577 577 865 289 865 577 577 865 463 447 435
109 451, 407, 289 451, 407, 289 577 245 577 451, 407, 289 451, 407, 289 577 317 301 273
Identification Protocatechuic acid Procyanidin dimer (D1) Procyanidin dimer (D2) Procyanidin trimer (T1) (+)-catechin Procyanidin trimer (T2) Procyanidin dimer (D3) Procyanidin B2 Procyanidin trimer (T3) Myricetin 3-O-rhamnoside (Myricitrin) Quercetin-3-O-rhamnoside (Quercitrin) Phloretin-2’-O-glucoside (Phloridzin)
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Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
Voyager Spec #1 MC=>BC=>SM7[BP = 6079.5, 7903]
6080.1
100 90
6208.4 80
% Intensity
70 60 50 40
6547.4 30
8205.3
20 10 0 3500
6825.0 6192.4 7273.5 8175.1 5604.2
5252.2 4005.4
5800
Internal standard 13682.6
*9467.3
13891.4
8100
10400
12700
Mass (m/z)
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Figure 6
MALDI-TOF MS analysis of unkonwn sample and MS data processing
Alignment of peak list obtained from the analysis of unknown sample with a list of specific biomarkers of GROUP I using NEAPOLIS
GROUP I AMANDI AVELLANA BADEN BEARN COSFORD FRUCTO RUBRO GHIRARA GRIFFOL MINNOLARA NAPOLETANA SEGORBE SIVRI
I D E N T I F I C A T I O N
NO IDENTIFICATION Alignment of unknown peak list with GROUP II biomarker list
GROUP II Presence of m/z 3661.2
MONTEBELLO RICCIA di TALANICO S.MARIA del GESU'
I D E N T I F I C A T I O N
NO IDENTIFICATION Alignment of unknown peak list with GROUP III biomarker list
GROUP III Presence of m/z 14345.7 BARCELONA GIRONELL NOCCHIONE TONDA GENTILE ROMANA TONDA di GIFFONI
NO IDENTIFICATION
I D E N T I F I C A T I O N
NO IDENTIFICATION Alignment of unknown peak list with GROUP IV biomarker list
Alignment of unknown peak list with GROUP III A biomarker list IDENTIFICATION
I D E N T I F I C A T I O N
GROUP III A NOCIARA LOCALE PIAZZA ARMERINA
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GROUP IV APOLDA COMEN ENDRIX JEANS ROYAL
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GRAPHIC FOR TABLE OF CONTENTS
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