Distribution of Aroma Volatile Compounds in Tangerine Hybrids

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Research ArticleReceived: 15 June 2010 Revised: 1 September 2010 Accepted: 1 October 2010 Published online in Wiley Online Library: 27 October 2010

(wileyonlinelibrary.com) DOI 10.1002/jsfa.4205

Distribution of aroma volatile compoundsin tangerine hybrids and proposedinheritance†‡§

Takayuki Miyazaki,a Anne Plotto,b∗ Kevin Goodnerc and Fred G Gmitter Jra

Abstract

BACKGROUND: With the desirable combination of sugars and acids, volatile compounds contribute to the essential organolepticattributes of citrus. This study evaluated the aroma volatiles of 20 tangerine hybrids of the University of Florida breedingprogram. Volatiles were sampled from hand-squeezed juice by headspace solid-phase microextraction (SPME), and analyzedby gas chromatography–mass spectrometry. Principal component analysis (PCA) and cluster analysis (CA) were used to findsimilarities among samples due to volatile composition with effect of genetic background.

RESULTS: In total, 203 volatiles were detected in all samples. Volatiles in lower amounts were widely distributed among samplesand were classified mainly as terpene hydrocarbons and oxygenated compounds, such as aldehydes, esters, alcohols andketones. PCA, based on relative peak areas (content) clearly separated the samples higher in volatile content, mainly those withsweet orange genetic contributions in their background. CA, based on volatile presence/absence, grouped samples into fiveclusters, each showing distinctive volatile profiles.

CONCLUSION: The genetic background of tangerine hybrids affected volatile composition and content of samples. In general,tangerines were characterized by fewer volatiles (in both quality and quantity) and more aldehydes, and hybrids with sweetorange in their background had more sesquiterpenes and esters, which would likely affect their aroma.Published 2010 by John Wiley & Sons, Ltd.

Keywords: Citrus reticulata; citrus breeding; aroma volatiles; fruit quality; tangerine; mandarin

INTRODUCTIONFlorida fresh tangerines (Citrus reticulata Blanco, sometimesreferred to as mandarins in the USA) as well as oranges (C.sinensis L. Osb.) and grapefruit (C. paradisi Macf.) are amongthe largest agricultural commodities in the US citrus market.While grapefruit are very sensitive to endemic citrus cankerdisease,1 tangerines can be fairly tolerant and therefore providean alternative to grapefruit production for the future fresh fruitindustry in Florida. The fresh tangerine fruit is widely consumedbecause of its desirable qualities of aroma, flavor and ease ofpeeling. In addition, the high nutritional content from vitamin Cand carotenoids in tangerines benefits human health. From 2007 to2009, the average annual US production of tangerines/mandarinswas 485 000 tons, increasing from 361 000 tons in 2006, andwith fresh fruit production accounting for 70–80%.2 In Florida,that production was five and a half million 95 lb (43 kg) boxes(∼237 000 tons) in the peak year.2

Improvement in fruit quality is one of the primary goals of freshtangerine breeding programs in Florida. Commercial tangerinefruits are currently graded by inspectors, with grading based onlyon fruit appearance factors such as color, size and damage.3

However, new quality standards based on flavor attributes couldbe created to be used in the selection of high-quality fruits.Conventional citrus breeding, based on crossing and selection,requires a large amount of space, and considerable time andlabor during the long juvenile period of citrus trees; such efforts

are rather costly to conduct. In the last decades, advancementof plant genetics and genomics has made citrus breeding moreefficient. The application of molecular markers to citrus breedingmay allow breeders to select superior recombinants improved formultiple traits by conventional breeding efforts, using marker-

∗ Correspondence to: Anne Plotto, USDA/ARS, Citrus and Subtropical ProductsLaboratory, 600 Avenue ‘S’, NW, Winter Haven, FL 33881, USA.E-mail: [email protected]

† This article is a US Government work and is in the public domain in the USA.

‡ Mention of a trademark or proprietary product is for identification only anddoes not imply a guarantee or warranty of the product by the US Departmentof Agriculture. The US Department of Agriculture prohibits discrimination in allits programs and activities on the basis of race, color, national origin, gender,religion, age, disability, political beliefs, sexual orientation, and marital orfamily status.

§ Part of this work was presented at the Florida State Horticultural Meeting, 1-2June 2009.

a Institute of Food and Agricultural Sciences, University of Florida, Citrus Researchand Education Center, Lake Alfred, FL 33850, USA

b USDA/ARS, Citrus and Subtropical Products Laboratory, Winter Haven, FL33881, USA

c Sensus, LLC, Hamilton, OH 45011, USA

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assisted selection (MAS).4 It can also effectively help in removingplants producing fruit with poor attributes from the program at anearlier stage. Molecular markers associated with citrus fruit qualitycan be a valuable tool for genetic improvement, leading to thefaster release of new superior scions.

Aroma, as well as taste, color and texture, is one of the most im-portant quality attributes of citrus fruits. The aroma volatiles of themajor processing orange and grapefruit cultivars have been wellinvestigated, and over 300 aroma volatiles have been reportedfrom gas chromatography (GC) and gas chromatography–massspectrometry (GC-MS) analyses of fresh orange juices.5 It is wellknown that citrus aroma components are a mixture of monoter-penes, sesquiterpenes, alcohols, aldehydes, acids, esters, ketones,etc. Although there have been several reports on aroma volatiles intangerine essence and peel oil,6 – 10 very little information is avail-able regarding those in fresh tangerine fruits.11 – 15 Information onvolatile quality and quantity can be useful to evaluate tangerinefruit flavor quality. In addition, peel and juice volatile compositionhave been analyzed for classification of different citrus fruits: yuzu(C. junos Sieb.) cultivars,16 lemon (C. limon Burm.) cultivars,17 grape-fruit hybrids18 and tangerine/mandarin hybrids.13,14 Differentia-tion of tangerine hybrids based on their aroma profiles may leadto better understanding of genetic control of aroma production.

The main objectives of this study were to investigate aromavolatile compounds in a population of tangerine hybrids, and toanalyze inter-varietal relationships from volatile profiles by usingmultivariate statistics, principal component analysis (PCA) andcluster analysis (CA). It was hypothesized that if similarities werepresent they would be due to common genetic background.13

The study on aroma volatiles present among tangerine hybrids ofdiverse origins would provide fundamental information on fruitquality, maturity and development of early DNA-based MAS.

EXPERIMENTALPlant materialsAll tangerine hybrids were obtained from the University ofFlorida Citrus Research and Education Center (UF-CREC) breedingprogram. The trees were grown under the same environmentalconditions of soil, irrigation and illumination at the CREC groves.Fruit were harvested from November 2007 until March 2008(Table 1). Twelve of the 56 tangerine hybrids evaluated in2006–200713 were selected for re-evaluation in the 2007–2008season: samples a, c and d (three seedlings issued from an 8–9 ×‘Murcott’ cross); samples b and g (two seedlings of a ‘Robinson’× ‘Fairchild’ cross); sample i (‘Fallglo’ × ‘Fairchild’); sample l (8–9);sample m (8–10); sample n (8–9 × ‘Orlando’); samples p and r (twoseedlings from unknown parentage); and sample y (8–9 × Val4x).Maturity of fruit from the individual hybrids was determined basedon the previous year’s results13 and confirmed by the breeder andhis assistants. Eight new hybrids and five named commercialcultivars (including one sweet orange) as references were alsoincluded for the present study. All hybrids have various geneticbackgrounds from tangerines, oranges and grapefruit (Fig. 1).19 – 27

Each sample was a juice composite from approximately 50–60fruits harvested from one tree of each hybrid accession. A total of25 samples were prepared at the USDA/ARS Citrus and SubtropicalProducts Laboratory.

Sample preparationFruit were soaked in warm water with 200 mL detergent (DECCO241 Fruit and Vegetable Kleen, Monrovia, CA, USA) in a 16 L

Table 1. List of samples and corresponding selection names orparentage, hybrid numbers, harvest dates and sample codes. Severalunique hybrids were evaluated from among the various cross-combinations listed

Selection name Hybrid number Harvest date Sample code

8-9 × ‘Murcott’ 1 16 Nov. 2007 a

8-9 × ‘Murcott’ 2 16 Nov. 2007 c

8-9 × ‘Murcott’ 3 16 Nov. 2007 d

‘Robinson’ × ‘Fairchild’ 1 16 Nov. 2007 b

‘Robinson’ × ‘Fairchild’ 2 16 Nov. 2007 e

‘Robinson’ × ‘Fairchild’ 3 14 Dec. 2007 g

‘Robinson’ × ‘Fairchild’ 4 14 Dec. 2007 h

‘Fallglo’ – 16 Nov. 2007 f

‘Fallglo’ × ‘Fairchild’ 1 14 Dec. 2007 i

‘Fallglo’ × ‘Fairchild’ 2 14 Dec. 2007 j

‘Fallglo’ × ‘Fairchild’ 3 14 Dec. 2007 k

8-9 1 14 Dec. 2007 l

8-10 1 14 Dec. 2007 m

Unknown – 11 Jan. 2008 o

Unknown – 11 Jan. 2008 p

Unknown – 11 Jan. 2008 r

8-9 × ‘Orlando’ 1 11 Jan. 2008 n

9-4 × Blood4x 1 11 Jan. 2008 q

‘Murcott’ – 14 Feb. 2008 s

‘Temple’ – 14 Feb. 2008 t

‘Sanguinelli’ – 14 Feb. 2008 u

‘Fortune’ × ‘Murcott’ 1 14 Feb. 2008 v

‘Ortanique’ – 25 Mar. 2008 w

8-8 × ‘Murcott’ 1 25 Mar. 2008 x

8-9 × VAL4x 1 25 Mar. 2008 y

Each sample is a juice composite from fruits harvested from one treeof individual hybrid or commercial cultivar.

bucket, washed for about 30 s, and rinsed. Individual fruits werecut in half and juiced manually for 3 s with an electric juicer(model 3183; Oster, Rye, NY, USA), avoiding any scraping ofthe albedo or squeezing of the flavedo to prevent potentialpeel components (peel oil) from entering the juice. Seeds wereremoved and aliquots (2.5 mL) of tangerine juice were placed in20 mL glass vials (Gerstel, Inc., Baltimore, MD, USA) along withsaturated sodium chloride solution (2.5 mL) to help drive volatilesinto the headspace and inhibit any potential enzymatic activity.3-Hexanone (1 ppm) was added as an internal standard. The vialswere capped with magnetic crimp caps containing Teflon-coatedsepta and stored at −20 ◦C until analyzed.

Headspace sampling and GC-MS analysisThe extraction of aroma volatiles was performed using SPME withan MPS-2 autosampler (Gerstel). The vials were incubated at 40 ◦Cfor 30 min in a water bath (Baxter Scientific Products, Cincinnati,OH, USA), and then a 2 cm SPME fiber (50/30 µm DVB/CAR/PDMS;Supelco, Bellefonte, PA, USA) was inserted into the headspaceof the sample vial and exposed for 60 min. The analytes werethermally desorbed in the GC injector (splitless mode) portfor 3 min at 250 ◦C. The separation of volatile compounds wasaccomplished using an Agilent 6890 GC (Agilent Technologies,Santa Clara, CA, USA) equipped with DB-5 (60 m length, 0.25 mmi.d., 1.00 µm film thickness; J&W Scientific, Folsom, CA, USA) andDB-Wax (60 m length, 0.25 mm i.d., 0.50 µm film thickness; Agilent

wileyonlinelibrary.com/jsfa Published 2010 by John Wiley & Sons, Ltd. J Sci Food Agric 2011; 91: 449–460

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Evaluation of tangerine aroma volatiles www.soci.org

Figure 1. Pedigree of tangerine hybrids (from references 19–27).

Technologies) columns, coupled with a 5973N MS detector (AgilentTechnologies). The column oven was programmed to increaseat 4 ◦C min−1 from the initial 40 ◦C to 230 ◦C, then ramped at100 ◦C min−1 to 260 ◦C and held for 11.70 min for a total runtime of 60 min. Helium was used as carrier gas at flow rate of1.5 mL min−1. Inlet, ionizing source and transfer line were keptat 250, 230, and 280 ◦C, respectively. Mass units were monitoredfrom 40 to 250 m/z and ionized at 70 eV. Data were collected usingthe ChemStation G1701 AA data system (Hewlett-Packard, PaloAlto, CA, USA). Samples were run in triplicate on a DB-5 column,with a blank run between each hybrid to ensure fiber cleannessbetween samples. A mixture of C-5 to C-15 n-alkanes was run atthe end of each day to calculate retention indices (RIs).28 Sampleswere also analyzed (one run per sample) on a DB-Wax column toidentify potential co-eluting compounds on the DB-5 column.

Volatile compound identificationVolatile compounds were identified by comparison of their massspectra with library entries (NIST/EPA/NIH Mass Spectral Library,version 2.0d; National Institute of Standards and Technology,Gaithersburg, MA, USA), as well as comparing RIs with publishedRIs on both columns. Published RIs were from the NIST/EPA/NIHMass Spectral Library, Kondoyan and Berdague29 and Adams.30

Chemical authentic standards, when available, were run on bothcolumns and their RIs and spectra confirmed compound identities.

Statistical analysesVolatile compounds were semi-quantified by calculating eachpeak area relative to the peak area of the internal standard

(relative peak area). These variables were used to perform a PCAbased on Pearson’s correlations to account for large variationin peak scaling31 to differentiate individual samples based ontheir volatile composition using XLSTAT software (Addinsoft, Paris,France). With the data transformed into presence/absence (1/0)of volatiles, a cluster analysis was performed to find correlationsbetween volatile composition and sample origin.13 Clusters wereformed using the unweighted pair-group average method witharithmetic mean (UPGMA) and the Kulczynski coefficient, tomeasure similarities between samples (XLSTAT, Addinsoft).

RESULTS AND DISCUSSIONA total of 146 compounds were identified by GC-MS inthe 25 samples, with an additional 57 unknown compounds(Tables 2 and 3). Spectra of tentatively identified compounds, i.e.,compounds for which identification with a chemical standardwas not confirmed, are shown in Table 4. The average number ofvolatiles per sample was 77, ranging from 52 to 118, and morethan 77 compounds were detected in 12 samples. The volatileswere widely distributed among samples; however, only a smallnumber of volatiles (5–26 volatiles) contributed to more than 90%of the total content. Many volatile compounds in Tables 2 and 3have already been reported in tangerine essence, peel oil andjuice.6,7,11 – 15,32 – 37 All samples contained 15 volatiles in common:ethanol, hexanal, α-pinene, β-myrcene, octanal, α-terpinene,p-cymene, d-limonene, terpinolene, dehydro-p-cymene, linalool,nonanal, decanal,α-terpineol and d-carvone (Table 2). d-Limonenewas the most abundant compound, representing 40.6–82.5%

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Table 2. List of most abundant aroma volatiles detected by GC-MS among samples and identified by linear retention index (LRI) on DB-5, DB-Waxcolumn and confirmed with chemical standards. Volatiles are listed according to their frequency of appearance, 48–100%, in samples

48–71%a 72–95%b 96–100%c

LRI LRI LRI

DB-5 DB-Wax DB-5 DB-Wax DB-5 DB-Wax

(E)-2-Pentenald 755 1167 Acetaldehyde 469 659 Ethanold 489 929

Benzaldehyded 985 1604 (E)-2-Decenal 1262 1868 Hexanald 805 1123

Allo-ocimene 1132 1384 α-Phellandrened 1025 1195 α-Pinened 956 1061

α-Selinene 1545 2228 γ -Terpinened 1073 1253 β-Myrcened 999 1189

α-Cubebened 1363 1496 Perillaldehyded 1293 2447 Octanald 1013 1283

α-Caryophyllened 1499 2013 Cadinene 1557 2309 α-Terpinened 1035 1239

γ -Selinene 1530 Propanald 511 747 p-Cymened 1042 1272

(−)-α-Panasinsen 1577 2393 Terpinene-4-old 1196 1765 d-Limonened 1049 1223

β-Cyclocitrald 1234 1854 p-Menth-1-en-9-al 1231 1839 Terpinolened 1100 1282

2-Undecenald 1366 2255 Copaened 1401 1551 Dehydro-p-cymened 1105 1446

(Z)-p-Mentha-2,8-dien-1-ol 1150 1933 Caryophyllened 1458 1801 Linaloold 1105 1600

β-Terpineold 1162 1796 1-Octen-3-one 988 Nonanald 1109 1384

Octyl acetated 1202 1491 6-Methyl-5-hepten-2-one 994 1316 Decanald 1205 1538

β-Elemene 1409 1754 p-Menth-1-en-9-al isomer 1234 α-Terpineold 1208 2026

Calamenened 1566 2631 1-Penten-3-oned 676 1057 d-Carvoned 1257 2225

α-Calacorened 1593 3117 (E)-2-Nonenald 1163 1615 Acetone 509 775

1 Unknown monoterpenee Geranyl acetoned 1454 2680 Ethyl acetated 599 870

2 Unknown sesquiterpenesf Valencened 1539 2191 Pentanald 690 1005

4 Unknownsg β-Iononed 1506 3187 (E)-2-Hexenald 864 1233

2 Unknown monoterpenese Heptanald 913 1208

2 Unknownsg (E)-2-Heptenald 970 1315

β-Phellandrened 1052 1229

(E)-2-Octenald 1067 1433

1,3,8-p-Menthatriene 1127 1392

(±)-4-Acetyl-1-methylcyclohexene 1144 1670

Dihydrocarvoned 1212 1819

a Volatiles detected in 12–17 out of 25 samples.b Volatiles detected in 18–23 out of 25 samples.c Volatiles detected in 24–25 samples.d Volatiles confirmed with chemical standards.e Unknown monoterpenes unidentified by GC-MS.f Unknown sesquiterpenes unidentified by GC-MS.g Unknown volatiles unidentified by GC-MS except monoterpenes and sesquiterpenes.

of the total aroma volatiles. Among 22 identified monoterpenehydrocarbons, four monoterpenes were also present in relativelyhigh amount in most samples: β-myrcene (0.5–4.9% of relativepeak area), p-cymene (0.3–7.0%), β-phellandrene (0–3.5%) anddehydro-p-cymene (0.5–9.5%). The other major compoundspresent in large amount in samples were valencene (0–24.9%),hexanal (0.1–14.1%) and linalool (0.5–9.5%). Conversely, 55volatiles were present in only one or two samples (Table 3) andtherefore might be more cultivar specific.

Most volatiles were classified into six chemical classes: monoter-penes, sesquiterpenes, aldehydes, esters, alcohols and ketones(Table 5). The number of volatiles in these classes alone accountedfor 76.8% of the total (203 volatiles). In addition, terpene-derivedaroma volatiles were grouped into several classes: e.g., neral andgeranial in aldehydes, linalyl acetate and citronellyl acetate inesters, linalool and citronellol in alcohols and α- and β-iononesin ketones. Most volatiles are originated from enzymatic synthe-sis in terpenoids and fatty acid metabolisms, these biosyntheticpathways playing an important role in aroma production in these

samples. Only a few volatiles were detected in other chemicalclasses: phenols, ethers, acids and epoxides (Table 5).

Principal component analysisIn this study, PCA was used as an exploratory technique to identifygroups among samples based on volatile composition and relativecontent. A first PCA was done using volatile quality (relative peakarea) and based on Pearson’s correlations to standardize the data.All 203 volatiles were used in this PCA as variables; the PCAreduced the number of variables to 24 principal components(data not shown). The first and second principal components(F1 and F2) represented 39.80% of the total variance (Fig. 2(A)).The third component explained an additional 11.69% of thevariance (Fig. 2(B)). Such a small percent variance in the firstthree components is due to the fact that the variance is spreadamong all 24 components. The plot of scores in the PCA analysisillustrates that samples q (9-4 × Blood4x), t (‘Temple’) and u(‘Sanguinelli’ orange) were clearly different from the others due totheir volatile profile. These samples were much richer in volatiles


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Table 3. List of less abundant aroma volatiles detected by GC-MS among samples and identified by linear retention index (LRI) on DB-5, DB-Waxcolumn and confirmed with chemical standards. Volatiles are listed according to their frequency of appearance, 1–47%, in samples

1–11%a 12–23%b 24–47%c

LRI LRI LRI

DB-5 DB-wax DB-5 DB-wax DB-5 DB-wax

2-Methyl-2-propanol 530 Ethyl propanoated 699 974 Butanald 583 861

2-Butanone 583 894 Ethyl butanoated 798 1075 Nerald 1241 2004

(E)-2-Butenal 639 1084 Methyl hexanoated 929 1208 Geraniald 1268 2005

(Z)-3-Hexenald 799 Ethyl hexanoated 1001 1240 Methyl acetate 531 784

1-Octen-3-ol 987 1436 Ethyl 3-hydroxyhexanoated 1128 1967 3-Pentanone 685 1002

p-Mentha-3,8-diene 1084 1271 Ethyl octanoated 1188 1427 4-Heptanone 878 1162

Octanoic acid 1152 α-Muurolene 1534 2160 4-Methyl-hexanal 889

Camphord 1171 2076 Caryophyllene oxided 1658 3584 Styrened 911 1262

Bornyl acetate 1294 Nootkatoned 1881 7433 α-Thujened 942 1063

(E,E)-2,4-Decadienald 1320 Dimethyl sulfide 529 1,8-Cineoled 1054 1228

(Z)-Carvyl acetated 1332 Methyl butanoated 712 1004 Dodecanal 1411 2076

δ-Elemened 1351 Ethyl 2-methylbutanoated 856 1054 β-Ionone epoxide 1511 3500

(S)-Perillyl acetate 1442 Sabinened 991 1191 Undecanald 1305 1782

α-Guaiened 1459 2212 Hexyl acetate 1018 1266 Citronellyl acetated 1341 1913

α-Farnesene 1518 2200 3-Carened 1031 1187 β-Pinened 1003 1149

(E,E)-2,4-Hexadienald 923 1397 (E)-Ocimene 1056 1241 Thymold 1289 4594

Ethyl tiglate 944 1245 β-Cubebene 1463 1788 Neryl acetated 1350 2126

1-Methylbutyl butanoate 1025 1-Penten-3-old 671 1150 Geranyl acetated 1370 2261

Methyl octanoated 1120 1373 2-Pentanone 674 1005 Selina-3,7(11)-diene 1600 2137

Hexyl butanoated 1188 2,3-Pentanedioned 683 Juniper camphor 1741 5244

(Z)-Carveold 1229 2536 3-Methyl-butanold 729 1164 2 Unknown sesquiterpenesf

Citronellold 1236 2186 Ethyl 2-butenoate 848 1194 7 Unknownsg

(E)-Carveold 1243 2664 (2E)-2-Methyl-2-hexenal 884

Nonanoic acid 1248 Hexanoic acidd 965

Nonyl acetated 1300 1689 2,3-Octanedione 991

Methyl geranate 1315 (E,Z)-2,4-Heptadienal 1007 1517

exo-2-Hydroxycineole acetate 1343 (E,E)-2,4-Heptadienald 1022 1532

α-Terpinyl acetated 1350 2063 Thymol methyl ether 1231 1766

Ylangene 1396 Linalyl acetated 1242 1638

Decyl acetated 1403 1973 α-Iononed 1439 2735

β-Farnesene 1460 1918 γ -Elemene 1455 1890

1 Unknown monoterpenee 2,6-Bis(1,1-dimethylethyl)-phenol 1523 5439

11 Unknown sesquitepenesf Nerolidold 1585 3646

12 Unknownsg Dihydroactinidiolide 1592

3 Unknown sesquitepenesf

10 Unknownsg

a Volatiles detected in 1–2 out of 25 samples.b Volatiles detected in 3–5 out of 25 samples.c Volatiles detected in 6–11 out of 25 samples.d Volatiles confirmed with chemical standards.e Unknown monoterpene unidentified by GC-MS.f Unknown sesquiterpenes unidentified by GC-MS.g Unknown volatiles unidentified by GC-MS except monoterpene and sesquiterpenes.

than the average sample (77 volatiles), since they contained 118,109 and 111 volatiles, respectively. According to the first two-component biplot data of this PCA analysis (Fig. 2(A)), many vectorsrepresenting sesquiterpenes were in the direction of the firstquadrant (upper right), along with some on the fourth quadrant(lower right), and most vectors representing esters were locatedon the fourth quadrant (lower right) (data not shown). Therefore,sample q (9-4 × Blood4x) may be distinguished by its high numberand amount of sesquiterpenes, and samples t (‘Temple’) and u

(‘Sanguinelli’) by their abundance in sesquiterpenes and esters, ascan be seen in Table 6.

Another type of PCA was performed using relative peak areasof total volatiles in each of the 11 chemical classes from Table 6(Fig. 3). In this PCA, the first two components explained 58.41%of the total variance. Ketones and alcohols were highly correlatedwith each other, as well as with aldehydes. Samples u (‘Sanguinelli’)and t (‘Temple’) had high scores on F1 (esters, other, ketones andalcohols), sample y (8–9 × Val4x) had a high score on F2, and


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Table 4. Mass spectra (percent occurrence) data for compounds not confirmed with chemical standards in Tables 2 and 3

Compound m/z (%)

Acetaldehyde 44(100), 43(21), 42(7), 41(3), 45(2)

Acetone 43(100), 58(38), 42(8), 41(2), 57(1)

2-Methyl-2-propanol 59 (100), 41(15), 43(12), 57(10), 42(7), 73(5), 60 (3), 55(2), 44(2), 58(2)

Dimethyl sulfide 62(100), 47(79), 45(43), 61(32), 46(29), 49(6), 57(5), 59(4), 44(4), 63(4)

Methyl acetate 43(100), 74(28), 42(13), 59 (12), 44(8), 73(5), 41(3), 45(2), 75(2)

2-Butanone 43(100), 72(38), 44(21), 57(12), 41(10), 42(10), 45(7), 70(5), 55(3), 69(2)

(E)-2-Butenal 70(100), 41(66), 69(47), 42(14), 71(7), 50(3), 53(3), 52(2), 68(2), 43(2)

2-Pentanone 43(100), 86(29), 71(13), 41(11), 58(10), 55(10), 42(5), 44(4), 77(3), 84(2)

3-Pentanone 57(100), 86(28), 56(5), 42(3), 58(3), 77(2), 87(2), 53(2), 44(2), 41(2)

Ethyl 2-butenoate 69(100), 99(41), 41(20), 68(7), 86(7), 70(6), 71(5), 43(5), 45(4), 42(3)

4-Heptanone 71(100), 43(77), 114(26), 41(18), 58(7), 42(6), 72(4), 55(4), 99(3), 44(3)

(2E)-2-Methyl-2-hexenal 112(100), 55(61), 41(53), 97(42), 83(41), 43(30), 69(30), 79(18), 40(17), 53(15)

4-Methylhexanal 70(100), 41(60), 57 (47),55(47), 71(29), 43(21), 58(18), 67(16), 42(16), 85(12)

Ethyl tiglate 83(100), 55(86), 113(43), 100(39), 128(22), 43(18), 82(18), 85(17), 44(13), 53(13)

1-Octen-3-one 70(100), 55(94), 97(26), 43(19), 41(13), 83(13), 71(12), 42(7), 56(5), 99(4)

1-Octen-3-ol 57(100), 72(19), 43(14), 68(14), 41(13), 67(13), 81(10), 85(8), 121(8), 79(7)

2,3-Octanedione 43(100), 99(52), 71(34), 41(19), 55(9), 42(7), 44(6), 142(4), 69)3), 87(3)

6-Methyl-5-hepten-2-one 43(100), 108(62), 41(52), 69(49), 55(46), 111(27), 67(24), 58(21), 71(21), 93(20)

(E,Z)-2,4-Heptadienal 81(100), 41(28), 110(23), 53(21), 67(18), 79(17), 57(16), 43(16), 55(15), 68(12)

Hexyl acetate 43(100), 56(58), 55(39), 41(37), 84(36), 69(31), 61(26), 42(22), 57(22), 44(17)

1-Methylbutyl butanoate 71(100), 43(44), 70(24), 41(18), 89(15), 93(14), 55(13), 115(12), 88(10), 42(9)

p-Mentha-3,8-diene 79(100), 107(48), 93(39), 91(34), 136(33), 121(29), 67(27), 77(26), 108(19), 105(17)

1,3,8-p-Menthatriene 119(100), 134(94), 91(85), 105(31), 77(25), 92(20), 117(18), 79(16), 41(16), 57(13)

Allo-ocimene 121(100), 105(42), 136(40), 91(33), 79(31), 77(18), 93(16), 106(9), 122(9), 40(8)

(±)-4-Acetyl-1-methylcyclohexene 95(100), 138(99), 43(72), 67(69), 123(57), 79(42), 93(41), 77(29), 55(28), 68(27)

(Z)-p-Mentha-2,8-dien-1-ol 134(100), 109(65), 91(61), 119(43), 137(41), 79(39), 95(28), 93(27), 105(24), 69(24)

Octanoic acid 60(100), 73(83), 43(68), 41(65), 91(59), 55(58), 71(53), 117(53), 93(49), 68(45)

Thymol methyl ether 149(100), 164(27), 91(16), 119(11), 150(11), 117(8), 115(7), 134(7), 77(6), 105(5)

p-Menth-1-en-9-al 94(100), 79(58), 67(17), 95(14), 55(11), 77(10), 68(9), 93(9), 91(9), 81(8)

p-Menth-1-en-9-al isomer 94(100), 79(57), 95(13), 93(11), 77(9), 41(8), 55(7), 53(6), 67(5), 145(5)

Nonanoic acid 60(100), 73(98), 57(58), 55(43), 41(43), 115(37), 43(37), 129(29), 69(26), 98(19)

(E)-2-decenal 70(100), 55(85), 41(73), 43(72), 83(70), 57(57), 69(45), 81(34), 56(34), 98(30)

Bornyl acetate 95(100), 121(55), 136(34), 43(30), 93(18), 81(18), 108(17), 83(15), 96(14), 154(13)

Methyl geranate 69(100), 41(45), 114(35), 123(30), 83(17), 82(15), 68(13), 70(10), 122(9), 151(9)

exo-2-Hydroxycineole acetate 43(100), 108(97), 126(53), 109(38), 82(35), 71(35), 93(32), 111(32), 69(31), 83(26)

Ylangene 105(100), 119(98), 93(80), 120(73), 161(72), 91(53), 44(39), 92(37), 41(36), 121(35)

β-Elemene 93(100), 81(91), 107(65), 67(61), 68(60), 79(55), 147(50), 121(48), 91(44), 105(44)

Dodecanal 57(100), 82(77), 43(77), 41(74), 55(74), 68(59), 67(51), 69(50), 96(46), 81(43)

(S)-Perillyl acetate 91(100), 119(70), 43(63), 92(60), 68(50), 134(48), 93(46), 67(39), 79(39), 105(36)

γ -Elemene 121(100), 93(70), 43(62), 107(55), 41(43), 69(43), 105(42), 161(41), 91(40), 119(33)

β-Farnesene 69(100), 43(69), 93(61), 41(57), 67(32), 91(32), 44(32), 133(30), 79(29), 55(25)

β-Cubebene 161(100), 105(37), 91(34), 119(24), 93(21), 120(20), 79(19), 41(19), 81(19), 162(18)

β-Ionone epoxide 123(100), 43(33), 44(25), 177(15), 135(13), 41(13), 207(12), 55(10), 95(9), 124(9)

α-Farnesene 93(100), 44(65), 41(58), 69(52), 107(45), 79(42), 119(40), 55(40), 91(40), 43(40)

2,6-Bis(1,1-dimethylethyl)-phenol 191(100), 206(15), 192(14), 57(14), 44(10), 207(8), 41(7), 163(5), 73(5), 74(5)

γ -Selinene 189(100), 133(61), 105(51), 91(44), 204(41), 107(30), 93(29), 147(29), 161(26), 79(24)

α-Muurolene 105(100), 161(59), 93(46), 91(44), 44(35), 119(34), 94(33), 204(32), 107(26), 81(22)

α-Selinene 189(100), 93(64), 107(62), 133(58), 204(56), 91(54), 105(50), 161(45), 81(44), 79(42)

Cadinene 161(100), 119(56), 204(54), 134(53), 105(48), 91(32), 162(21), 81(19), 189(19), 93(17)

(−)-α-Panasinsen 161(100), 122(79), 107(51), 105(24), 91(23), 93(20), 204(19), 81(18), 79(17), 119(14)

Dihydroactinidiolide 111(100), 44(80), 43(50), 109(46), 157(45), 137(43), 67(35), 41(28), 180(25), 142(23)

Selina-3,7(11)-diene 161(100), 122(55), 107(54), 204(54), 105(41), 91(40), 93(38), 44(28), 121(28), 119(27)

Juniper camphor 204(100), 189(99), 81(84), 161(79), 43(78), 71(60), 95(57), 109(56), 93(55), 67(54)


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Table 5. Tangerine aroma volatiles among 11 chemical classes

Monoterpenes Sesquiterpenes Aldehydes Esters Alcohols

α-Thujene δ-Elemene Acetaldehyde Methyl acetate Ethanol

α-Pinene α-Cubebene Propanal Ethyl acetate 2-Methyl-2-propanol

Sabinene Ylangene Butanal Ethyl propanoate 1-Penten-3-ol

β-Myrcene Copaene (E)-2-Butenal Methyl butanoate 3-Methylbutanol

β-Pinene β-Elemene Pentanal Ethyl butanoate 1-Octen-3-ol

α-Phellandrene γ -Elemene (E)-2-Pentenal Ethyl 2-butenoate Linalool

3-Carene Caryophyllene (Z)-3-Hexenal Ethyl 2-methylbutanoate cis-p-Mentha-2,8-dien-1-ol

α-Terpinene β-Farnesene Hexanal Methyl hexanoate β-Terpineol

p-Cymene α-Guaiene (E)-2-Hexenal Ethyl tiglate Terpinene-4-ol

d-Limonene β-Cubebene 2-Methyl-2-hexenal Ethyl hexanoate α-Terpineol

β-Phellandrene α-Caryophyllene 4-Methyl-hexanal Hexyl ethanoate (Z)-Carveol

(E)-Ocimene α-Farnesene Heptanal 1-Methyl butyl butanoate Citronellol

γ -Terpinene γ -Selinene (E,E)-2,4-Hexadienal Methyl octanoate (E)-Carveol

p-Mentha-3,8-diene α-Muurolene (E)-2-Heptenal Ethyl 3-hydroxyhexanoate Nerolidol

Terpinolene Valencene Benzaldehyde Hexyl butanoate Juniper camphor

Dehydro-p-cymene α-Selinene (E,Z)-2,4-Heptadienal Ethyl octanoate

1,3,8-p-Menthatriene Cadinene Octanal Octyl acetate

Allo-ocimene Calamenene (E,E)-(2,4)-Heptadienal Linalyl acetate

4 Unknown monoterpenes (−)-α-Panasinsen (E)-2-Octenal Bornyl acetate

α-Calacorene Nonanal Nonyl acetate

Selina-3,7(11)-diene (E)-2-Nonenal Methyl geranate

18 Unknown sesquiterpenes Decanal (Z)-Carvyl acetate

p-Menth-1-en-9-al Citronellyl acetate

p-Menth-1-en-9-al Isomer exo-2-Hydroxycineole acetate

β-Cyclocitral Neryl acetate

Neral α-Terpinyl acetate

(E)-2-Decenal Geranyl acetate

Geranial Decyl acetate

Perillaldehyde (S)-Perillyl acetate

Undecanal

(E,E)-2,4-Decadienal

2-Undecenal

Dodecanal

Ketones Phenols Ethers Acids Epoxides Others

Acetone Thymol 1,8-Cineole Hexanoic acid β-Ionone epoxide Dimethyl sulfide

2-Butanone 2,6-Bis(1,1-dimethylethyl)-phenol

Thymol methyl ether Octanoic acid Caryophyllene oxide Styrene

1-Penten-3-one Nonanoic acid (±)-4-Acetyl-1-methylcyclohexene

2-Pentanone 35 Unknowns

2,3-Pentanedione

3-Pentanone

4-Heptanone

1-Octen-3-one

2,3-Octanedione

6-Methyl-5-hepten-2-one

Camphor

Dihydrocarvone

d-Carvone

α-Ionone

Geranyl acetone

β-Ionone

Dihydroactinidiolide

Nootkatone


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Figure 2. PCA using volatile relative peak areas (peak area/peak area of IS) among all 25 samples. The percent variance explained by each of three factorsis shown in parentheses: (A) Factors 1 and 2; (B) Factors 1 and 3. Letters refer to sample codes (Table 1).

samples s (‘Murcott’) and v (‘Fortune’ × ‘Murcott’) had relativelyhigh negative scores on F2. In general, this graph shows thatthe samples on the right side, q (9-4 × Blood4x), s (‘Murcott’), t(‘Temple’), u (‘Sanguinelli’), v (‘Fortune’× ‘Murcott’), w (‘Ortanique’)and y (8–9 × Val4x) showed high total content of volatiles exceptfor ethers and phenols. Indeed, sample t (‘Temple’) produced 3.1,6.9 and 5.3 times more sesquiterpenes, esters and ketones thanthe averages of all samples, respectively (Table 6). Sample u alsocontained high amounts of sesquiterpenes, esters and alcohols. Onthe left side of Fig. 3, the samples with more mandarin/tangerinegenetic components had fewer volatiles overall.

Cluster analysis based on qualitative volatile compositionThe main goal of CA is to assign individual samples into groupsbased on their volatile quality or quantity. In the present study,CA is performed using volatile presence/absence; a dendrogramprovides information on volatile qualitative differences amongsamples as well as relationships of their volatile compositionbased on genetic background (Fig. 4).

Cluster 1 (C1)C1 grouped samples a (8–9 × ‘Murcott’) and b (‘Robinson’ ×‘Fairchild’) of which each contained fewer volatiles than the

average of all samples. These samples were characterized bygenerally having fewer aldehydes (except sample b), esters andketones (Table 7). The aliphatic aldehydes, pentanal, (E)-2-hexenal,heptanal and (E)-2-heptenal were not detected in sample a (8–9× ‘Murcott’), but were in all other samples. Sample b (‘Robinson’ ×‘Fairchild’) was the only sample without any esters; esters usuallyimpart a fruity note to orange juice.38 On the other hand, thesesamples were the richest in monoterpenes among the five clustersboth in quality (Table 7) and, for sample a, quantity (Table 6).Above all, the highest amounts of β-myrcene, d-limonene andγ -terpinene contribute to the distinctive volatile profile of samplea (8–9 × ‘Murcott’) (data not shown). Since samples a (8–9 ×‘Murcott’) and b (‘Robinson’ × ‘Fairchild’) are grouped in the samecluster as determined by their volatile profile, it is hypothesizedthat one or more of their common ancestors, ‘Clementine’,‘Duncan’ grapefruit and ‘Dancy’ tangerine, determines higherproduction of monoterpenes to the detriment of other classes ofvolatiles.

Cluster 2 (C2)C2 grouped samples c (8–9 × ‘Murcott’) and l (8–9), and hadfewer volatiles than the average of the samples, especiallyfewer sesquiterpenes and aldehydes, like cluster 1 (Table 7). In


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Table 6. Amount (sum of relative peak areas (peak area/IS peak area) in each chemical group) of aroma volatiles arranged by 11 chemical classes in25 samples

Sample name Sample code Monoterpenes Sesquiterpenes Aldehydes Esters Alcohols Ketones Phenols Ethers Acids Epoxides Others Total

8-9 × M a 27.58 0.09 0.61 0.01 0.8 0.02 0.002 0 0 0 0.01 29.13

R × FC b 16.05 0.18 0.42 0 0.87 0.2 0 0 0 0 0.03 17.76

8-9 × M c 9.04 0.08 0.41 0.01 0.48 0.12 0.015 0.198 0 0 0.02 10.39

8-9 × M d 13.74 0.05 0.5 0.03 0.37 0.18 0 0.13 0 0 0.09 15.09

R × FC e 10.36 0.03 0.83 0.06 0.36 0.25 0 0.114 0 0 0.11 12.12

FG f 3.69 0.46 0.78 0.03 0.27 0.13 0 0 0 0.005 0.06 5.43

R × FC g 6.22 0.66 0.8 0.03 0.47 0.16 0 0.08 0 0.004 0.06 8.49

R × FC h 10.61 0.05 0.96 0.05 0.74 0.36 0 0.17 0 0.003 0.13 13.08

FG × FC i 17.01 1.73 0.46 0.24 0.73 0.19 0 0 0 0 0.11 20.46

FG × FC j 7.76 0.04 0.59 0 0.66 0.19 0 0 0 0.005 0.05 9.3

FG × FC k 4.88 0.67 0.71 0.01 0.46 0.14 0 0.105 0 0.006 0.05 7.03

8-9 l 10.03 0.11 0.32 0.05 0.63 0.04 0.064 0.003 0 0 0.15 11.4

8-10 m 5.88 2.45 0.72 0.02 0.76 0.07 0.043 0.024 0 0 0.1 10.05

8-9 × O n 8.55 0.32 0.43 0.23 0.42 0.09 0 0.157 0 0 0.03 10.22

Unknown o 5.64 0.13 0.98 0.01 0.31 0.22 0 0.068 0.004 0 0.06 7.43

Unknown p 1.75 0 0.93 0.03 0.1 0.14 0 0 0 0.003 0.03 2.98

9-4 × Blood4x q 7.62 3.99 1.14 0.02 0.49 0.35 0 0 0.003 0 0.34 13.94

Unknown r 1.8 0 1.11 0.03 0.11 0.18 0 0 0 0.005 0.04 3.27

M s 11.78 0.03 1.57 0.07 0.65 0.48 0 0 0 0.003 0.12 14.69

T t 19.44 3.3 2.03 1.32 3.43 0.48 0 0 0 0 0.71 30.7

SANG u 19.05 5.56 0.99 1.11 1.35 0.63 0 0 0 0 0.35 29.03

F × M v 17.63 0.03 1.07 0.35 0.72 0.35 0 0 0.003 0 0.11 20.26

ORT w 8.35 2.13 0.65 0.44 0.27 0.37 0 0 0 0 0.15 12.36

8-8 × M x 4.95 0.03 0.73 0.04 0.18 0.1 0.03 0 0.003 0.002 0.05 6.1

8-9 × Val4x y 6.12 4.31 0.58 0.59 0.47 0.24 0.022 0.044 0.051 0 0.33 12.76

M, ‘Murcott’; R, ‘Robinson’; FC, ‘Fairchild’; FG, ‘Fallglo’; F, ‘Fortune’; O, ‘Orlando’; T, ‘Temple’; SANG, ‘Sanguinelli’; ORT, ‘Ortanique’.

looking at the relationship between volatile composition andparentage, sample c (8–9 × ‘Murcott’) as well as sample a(8–9 × ‘Murcott’) in C1 was more similar to sample l (8–9)than s (‘Murcott’) in terms of qualitative volatile composition,indicating that the seed parent might be a dominant parentfor its aroma volatile production. However, it is not a rule sincesample d (8–9 × ‘Murcott’) is in the same cluster (C3) as its parent‘Murcott (sample s). It has been observed that some volatiles inparents are not synthesized in progenies and, conversely, somenew volatiles are synthesized in progenies.13,14 In the currentstudy, 1-octen-3-one was found in both parents (sample l, 8–9;sample s, ‘Murcott’), whereas it was absent in the progenies,samples c, a and d (all are 8–9 × ‘Murcott’) (data not shown).This volatile is the most intense odor-active aliphatic ketone,with a mushroom-like odor, that was reported in orange juice.5

The content of 1-octen-3-one in sample s (‘Murcott’) was thehighest and more than twice the average of all samples. Thusits production was likely suppressed in the progenies. Moreover,carotenoid-derived volatiles were not found in sample a, c or d(all are 8–9 × ‘Murcott’). Both parents (sample l, 8–9) contained6-methyl-5-hepten-2-one and geranyl acetone, originating fromlycopene and ξ -carotene, respectively.39 β-Cyclocitral, β-iononeand dihydroactinidiolide – oxidative degradation products fromβ-carotene39 – were only present in the pollen parent (sample s,‘Murcott’), as well as neral and geranial (data not shown). β-Iononeis well known as an aroma active compound, and its odor isusually described as ‘floral’ in orange juice.40,41 This suggests thatthe carotenoid degradation to aroma volatiles is affected in thisspecific cross.

Some sesquiterpenes (α-cubebene, α-caryophyllene, α-muuro-lene, calamenene) were detected in the progenies but not intheir parents (sample l, 8–9; sample s, ‘Murcott’). The capacity toproduce these compounds might be inherited from the parents inan additive genetic fashion.

Cluster 3 (C3)C3 grouped 12 samples equally divided into ones that containmore or fewer volatiles than the average of all samples. Thecommon characteristics of the samples in this cluster are that theycontain many aldehydes and few sesquiterpenes and esters incomparison with the other clusters that either have samples withmany or few compounds in all three chemical groups (Table 7).Most samples share a common genetic background in this cluster,mostly by having ‘Murcott’ or ‘Fairchild’ as a pollen parent. Theywere samples d (8–9 × ‘Murcott’), v (‘Fortune’ × ‘Murcott’) andx (8-8 × ‘Murcott’), together with their pollen parent ‘Murcott’(sample s). Samples j and k are siblings of the same parents:‘Fallglo’ and ‘Fairchild’. Samples e, g and h are siblings originatedfrom the same cross between ‘Robinson’ and ‘Fairchild’.

Cluster 4 (C4)C4 contained samples with a higher than average number ofvolatiles, except sample n (8–9 × ‘Orlando’). Samples in thiscluster contain a distinctly higher number of volatiles in thesesquiterpene and ester categories (Table 7). Samples t (Temple’)and u (‘Sanguinelli’), the outliers in the PCA analysis, are groupedin this cluster owing to their distinctive volatile composition,


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Figure 3. PCA using the sum of relative peak areas of compounds classified into chemical categories among all 25 samples. Letters refer to sample codes(Table 1). Lines represent vectors for each of the variables (sum of compound relative peak areas).

Figure 4. CA using volatile presence and absence among samples. Letters indicate sample codes (Table 1).

as previously mentioned. Sample n (8–9 × ‘Orlando’) is alsocharacterized by its richness in esters, and samples i (‘Fallglo’ ×‘Fairchild’), w (‘Ortanique’) and y (8–9 × Val4x) are characterizedby their high content of sesquiterpenes and esters. With regardto samples u (‘Sanguinelli’), w (‘Ortanique’) and y (8–9 × Val4x),the sesquiterpene valencene was the second most abundantvolatile, although not important for aroma, accounting for 12.5%,24.8% and 11.9% of relative peak area, respectively (data notshown). Nootkatone, a putative derivative from valencene, wasalso detected in the three samples and in sample t (‘Temple’). Thiscompound is a major aroma impact compound that contributesto characteristic aroma and flavor of grapefruit and pummelo.42,43

These samples are grouped in the same cluster, probably becausethey have some orange genetic background that results inthe production of esters. Kerbiriou et al.13 had found a similarclustering in 2006–2007. ‘Temple’ and ‘Ortanique’ are believedto be tangors (presumed tangerine-sweet orange hybrids) thatoriginated in Jamaica.19 ‘Sanguinelli’ is a blood orange and Val4x isa tetraploid Valencia orange. Sample i (‘Fallglo’ × ‘Fairchild’) does

not have a direct orange parent; however, it does have orange inits background with ‘Temple’ as a grandparent.

Cluster 5 (C5)C5 grouped samples that are outliers based on their volatilecomposition. Samples p and r are themselves in a sub-cluster(Fig. 4). The parentage of samples p and r is unknown, thoughthey may have originated from the same parents owing to theirvery similar volatile composition. The marked characteristics ofthese samples are significantly lower amounts of total volatilesand an absence of sesquiterpenes. In addition, aldehydes arenumerous and in large amount in samples p and r, accounting for31.0% and 33.9% of relative peak area, respectively (Tables 6and 7). 2-Methyl-2-hexenal, (E,Z)-2,4-heptadienal and (E,E)-2,4-heptadienal were detected only in the three samples in thiscluster (data not shown). Most aldehydes present in these sampleshave already been found in many citrus fruits,5,13,17,43 – 45 and theyare well known to impart ‘green’ and ‘fatty’ notes. Therefore, the


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Table 7. Samples in five clusters formed by cluster analysis based on presence and absence of volatiles, and their number of volatiles in 11 chemicalclasses

Cluster no. Sample code Sample name Monoterpene Sesquiterpene Aldehyde Ester Alcohol Ketone Phenol Ether Acid Epoxide Other Total

C1 a 8-9 × M 18 10 9 2 5 4 1 0 0 0 3 52

b R × FC 19 11 17 0 9 5 0 0 0 0 5 66

C2 c 8-9 × M 17 7 14 2 6 6 2 2 0 0 6 62

l 8-9 16 8 14 2 6 8 2 1 0 0 8 65

C3 f FG 13 8 16 2 3 8 0 0 0 1 7 58

m 8-10 18 17 21 3 6 7 1 1 0 0 15 89

d 8-9 × M 13 8 16 2 4 4 0 1 0 0 10 58

e R × FC 14 5 17 2 5 8 0 1 0 0 9 61

k FG × FC 14 11 21 1 5 8 0 1 0 2 9 72

g R × FC 14 14 23 5 6 9 0 1 0 1 12 85

o Unknown 14 12 24 2 5 9 0 1 1 0 12 80

h R × FC 15 8 26 3 6 8 0 1 0 1 14 82

j FG × FC 16 8 22 1 5 9 0 0 0 1 8 70

x 8-8 × M 14 6 20 2 5 11 2 0 1 1 6 68

s M 15 4 26 5 7 12 0 0 0 1 12 82

v F × M 15 5 24 9 7 10 0 0 1 0 9 80

C4 n 8-9 × O 14 13 16 10 4 6 0 1 0 0 5 69

i FG × FC 16 20 19 11 5 8 0 0 0 0 11 90

y 8-9 × Val4x 13 19 20 9 6 11 1 1 2 1 10 93

t T 14 19 24 17 7 12 0 0 0 1 15 109

u SANG 17 23 18 20 8 11 0 0 0 1 13 111

w ORT 14 20 19 10 6 12 0 0 0 1 13 95

C5 q 9-4 × Blood4x 14 33 28 4 7 9 0 0 1 0 22 118

p Unknown 10 0 26 2 5 9 0 0 0 1 8 61

r Unknown 8 0 25 2 4 9 0 0 0 1 7 56

M, ‘Murcott’; R, ‘Robinson’; FC, ‘Fairchild’; FG, ‘Fallglo’; F, ‘Fortune’; O, ‘Orlando’; T, ‘Temple’; SANG, ‘Sanguinelli’; ORT, ‘Ortanique’.

high level of aldehyde content might negatively influence theoverall aroma of samples p and r, as well as q (9-4 × Blood4x).

As shown in Fig. 2 as well as Tables 6 and 7, sample q (9-4 ×Blood4x) is clearly characterized by a high number and quantityof sesquiterpenes. This sample contained 33 compounds of the39 different sesquiterpenes detected in the 25 samples. Sampleq (9-4 × Blood4x) and sample y (8–9 × Val4x) in C4 have two-thirds chromosome complement from Blood4x (tetraploid ‘Ruby’blood orange) or Val4x, respectively. While C4 grouped samplesthat have some orange in their background and thus abundantesters, this sample is differentiated from them due to its loweramount of esters. Interestingly, although sample q (9-4 × Blood4x)contained the highest number of volatiles (118 volatiles) (Table 7),their amount was only slightly higher than the average of the25 samples and similar to those of the siblings of 9-4, 8–9 and8–10 (all are hybrids from the cross ‘Clementine’ × ‘Minneola’)(Table 6). Sample y (8–9 × Val4x) in C4 contained a higher numberof volatiles (93) than its parent l (8–9) (65) (Table 7), whereas thetotal content is similar to that of the parent (Table 6).

From these results, it may be deduced that samples q (9-4 ×Blood4x) and y (8–9 × Val4x) can synthesize aroma volatiles fromthe pollen parents, though the total volatile content is regulatedby the seed parents. So far, inheritance of genes involved in volatilesynthesis and their expression in sexual citrus progenies are stillunknown. Gancel et al.46 showed that leaf volatile composition ofa somatic hybrid (2n = 4x = 36) between Willow leaf mandarin(C. deliciosa Ten.) with sweet orange was similar to that of the

mandarin parent. Since the parents 9-4 and 8–9 have backgroundfrom mandarin, their genetic components might play an importantrole in the control of aroma production.

CONCLUSIONThe qualitative and quantitative differences of volatile compositionwere observed in a population of tangerine hybrids: among 203aroma volatiles detected by GC-MS, 92 were identified andconfirmed with chemical standards, and 54 were tentativelyidentified using mass spectra and RIs on two columns. Mosthybrids with mandarin/tangerine genetic contribution weredistinguished from the other samples by their lower numberand/or quantity of volatile compounds. Different siblings ofthe same parentage (8–9 × ‘Murcott’, ‘Robinson’ × ‘Fairchild’,‘Fallglo’ × ‘Fairchild’, or 8–9 and 8–10) showed different volatilecomposition, implying complex genetic controls for aroma volatileproduction. Nevertheless, hybrids with sweet orange in theirbackground appeared to produce more sesquiterpenes and esters,except 9-4 × Blood4x, which produced fewer esters, similar to theother tangerines. These volatile differences among hybrids providefundamental information for improved genetic understanding andfuture improvement in tangerine aroma and flavor.

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Documents

Distribution of Aroma Volatile Compounds in Tangerine Hybrids