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. 2020 Jan 2;7:5. doi: 10.1038/s41597-019-0321-1

The accumulation profiles of terpene metabolites in three Muscat table grape cultivars through HS-SPME-GCMS

Lei Sun 1, Baoqing Zhu 2, Xuanyin Zhang 1, Huiling Wang 1, Ailing Yan 1, Guojun Zhang 1, Xiaoyue Wang 1, Haiying Xu 3,4,
PMCID: PMC6940363  PMID: 31896793

Abstract

Aroma is an important parameter for table grapes and wines; terpenes are typical compounds in Muscat-type grape cultivars and can be easily perceived by humans because of their low olfactory threshold. Volatile terpenes contribute directly to the aroma character, while glycoside-bound terpenes are potential aromatic compounds and can be changed to their volatile forms via hydrolysis. With gas chromatography-mass spectrometry and a solid-phase microextraction method, an automatic data analysis platform was constructed; terpene compounds were identified and quantified from three table grape cultivars at three stages during berry development, and the raw data were deposited in MetaboLights. Terpene metabolite accumulation profiles are presented in this article for integrative analysis with the transcriptome data and phenotypic data to elucidate the important candidate genes and mechanism for terpene biosynthesis. Our method has applications in the identification and quantification of terpene compounds with very low or trace concentrations.

Subject terms: Plant breeding, Plant sciences


Measurement(s) Terpene Compound
Technology Type(s) gas chromatography-mass spectrometry • solid-phase micro-extraction
Factor Type(s) cultivar • developmental stage • biological replicate
Sample Characteristic - Organism Vitis vinifera

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.10327715

Background & Summary

The aroma character of Muscat grape cultivars has been thoroughly studied; monoterpenes are the main compounds in Muscat grapes, in the form of terpene alcohols, alkenes, aldehydes, and their oxides. The dominant terpenes in grapes are linalool, geraniol, nerol, terpineol and citronellol. Terpenes exist in two forms: the free form is volatile and directly contributes to flavor, while the glycoside form is non-volatile but can be transformed into the volatile form via hydrolysis16. Generally, bound terpenes are more abundant than the free form7. In grapes, terpenes mainly exist in the vacuoles of pericarp cells and in the flesh in some varieties8; their contents are affected by the genotype911, development stage12,13, environment and management1417.

Numerous methods have been used for the detection and analysis of aromatic compounds. The extraction strategies mainly include liquid-liquid extraction, steam distillation, solid-phase extraction, supercritical fluid extraction, and static headspace extraction1821. Among these, solid-phase microextraction (SPME) has been widely used for the extraction of volatile compounds since 199622. SPME has several advantages over other sample preparation techniques: no organic solvents are needed, the process is easily automated, and small sample sizes are required23. The target compounds are not compromised, and it is easy to set up the automation system and connect to downstream analytical instruments24,25. These features make SPME particularly well suited for studies of a large number of samples. However, the selection of fiber type and model is complicated in the SPME system and should be determined by the extracted compounds and preliminary experiments; additionally, SPME is not applicable when the compounds are not easily volatilized.

Data analysis is a critical step when handling large amounts of metabolic data, and efficient software for peak identification and deconvolution should be optimized to obtain as much information as possible from a sample26,27. Fragment ions from isomers are highly overlapped between different compounds, and this coelution is one of the difficulties in separating compounds, especially for complicated samples. The automated mass spectral deconvolution and identification system (AMDIS) was developed by the American National Standards Institute and is very powerful when dealing with background noise, single peak extraction and shift correction; the detection limit can reach 10−12 g/l28.

In this study, an automatic data analysis platform was constructed, and the contents of the free and bound forms of terpenes were analyzed in 27 table grape samples. Terpene compounds were identified by comparing their retention indices and mass spectra with reference standards and the NIST11 library. Quantification was carried out with standard curves. A total of 28 terpenes were identified. Regarding their structure and category, these terpenes included 5 cyclic alkenes: β-myrcene, (Z)-β-ocimene, (E)-β-ocimene, (E,Z)-allo-ocimene, and (Z)-allo-ocimene; 6 cyclic alcohols: nerol, geraniol, β-citronellol, linalool, γ-geraniol, and isogeraniol; 3 cyclic aldehydes: geranial, neral, and citronellal; 6 cyclic ethers: nerol oxide, cis-rose oxide, trans-rose oxide, cis-furan linalool oxide, trans-furan linalool oxide, and cis-pyran linalool oxide; 1 cyclic acid: geranic acid; 3 acyclic alkenes: limonene, γ-terpinene, and terpinolene; and 2 acyclic alcohols: α-terpineol and 4-terpineol.

The contents of these terpenes could be used for correlation analysis with transcriptome data. The data will be useful for elucidating the mechanism of terpene biosynthesis in table grapes and will provide information for future breeding.

Methods

Overview of the experimental design

The berries of three genotypes were collected at three developmental stages. Approximately 300 grape berries were randomly collected for each replicate, and three replicates were harvested for each stage. The experimental design and analysis pipeline are shown in Fig. 1.

Fig. 1.

Fig. 1

flowchart of the experimental design.

Materials and Methods

Sample collection

Three Vitis vinifera cultivars were used for volatile metabolite analysis: ‘Xiangfei’ was registered by our team in 2000 and has a strong Muscat flavor with a green to golden skin color, ‘Italia’ is a famous mid-late-season table grape cultivar originated in Italy and has moderate Muscat flavor, and ‘Zaomeiguixiang’ has a purple-reddish color and a strong Muscat flavor.

The vines were planted in the experimental field at the Beijing Academy of Forestry and Pomology Sciences in China (39°58′N and 116°13′E) under a plastic cover and trained into a two-wire vertical trellis system with a 2.5-m row space and a 0.75-m plant space. Berry samples from three vines in 2017 were harvested at the development stages corresponding to EL35, EL36, and EL3829. The berry begins to color and soften at EL 35, the completely colored version with intermediate Brix occurs at EL 36, and the berry reaches harvest ripeness at EL38. At each stage, three replicates were harvested; for each replicate, approximately 300 grape berries were randomly collected from ten vines. The berries were frozen in liquid nitrogen and stored at −80 °C.

Extraction of volatile compounds

The extraction of volatile compounds from the grape berries followed Wen’s published method with minor modifications30. The grape berries (approximately 100 g), after discarding seeds and pedicels, were ground and then blended with 1 g of polyvinylpolypyrrolidone (PVPP) under liquid nitrogen. The resultant mixture was macerated at 4 °C for 4 hours and then centrifuged at 8,000 rpm for 15 min at 4 °C to obtain a clear juice. Five milliliters of the liquid were mixed with 1 g of sodium chloride and 10 µL of 1.00808 g/L 4-methyl-2-pentanol in a 20 mL vial (Agilent, 5188-2753 Santa Clara, California, United States) capped with a silicone septum (Agilent, 8010-0139). Two technical replicates were performed for each sample.

Extraction of glycoside-bound compounds

Ten milliliters of methanol and 10 milliliters of water were added in advance to the Cleanert PEP-SPE resins (Bonna-agela Technologies, China). Two milliliters of the clear juice were passed through the Cleanert PEP-SPE column. Water-soluble compounds were eluted with 2 mL of water, free volatiles were washed out with 10 mL of dichloromethane, and then the bound terpenes were eluted with 20 mL of methanol and collected in a round flask. The flow rate was approximately 2 mL/min. The methanol eluate was concentrated to dryness by a rotary evaporator under a vacuum at 30 degrees and then redissolved in 10 mL of a 2 M citrate-phosphate buffer solution (pH 5.0). Subsequently, 4.9 mL of the solution was transferred to a tube, and 100 μL of AR 2000 was added for incubation at 40 degrees for 16 hours. Afterwards, the liquid (5 mL) was mixed with 1 g sodium chloride and 10 µL of 1.00808 g/L 4-methyl-2-pentanol in a 15-mL vial capped with a PTFE-silicone septum.

GC-MS conditions

The volatile compounds were absorbed using headspace solid-phase microextraction (HS-SPME) and then analyzed using an Agilent 7890B-5977A gas chromatograph-mass spectrometer (GC-MS). The autosampler (CTC-PAL RSI85, CTC Analytics, Zwingen, Switzerland) was operated in SPME mode with an SPME fiber (57348-U, Supelco, Bellefonte, PA, USA). The sample vial was initially incubated at 40 °C for 30 min under agitation at 250 rpm, and then the preconditioned SPME fiber was inserted into the headspace of the vial to extract volatiles for 30 min at 40 °C under the same agitation conditions. Then, the SPME fiber was immediately inserted into the GC injection port at 250 °C for 8 min to desorb the volatiles. A 60 m × 0.25 mm HP-INNOWAX capillary column with a 0.25 μm film thickness (J&W Scientific, Folsom, CA, USA) was used to separate the volatile compounds under a 1 mL/min flow rate of helium (carrier gas). The oven temperature program was set as follows: 50 °C for 1 min, increase to 220 °C at 3 °C/min and hold at 220 °C for 5 min. The ion source was maintained at 250 °C with an MSD transfer line temperature of 250 °C. Mass scans were performed from m/z 30-350 with an ionization voltage of 70 eV.

Identification of the compounds

The identification of volatile compounds was based on the retention index of reference standards and mass spectra matching using the standard NIST 11 library. A comparison of the retention index with those reported in the literature was used when standards were not available. Automated mass spectral deconvolution and identification system software (AMDIS, version 2.69, NIST, Washington, DC, USA) was used for peak deconvolution. The parameters for deconvolution were set as follows: component width = 20; adjacent peak subtraction = 2; resolution = high; sensitivity = low; and shape requirements = medium. A self-built library was used to search and match target compounds. Parameters for peak detection were set with default values. The identification information is listed in Table 1.

Table 1.

Identification information of the compounds.

Compounds Retention time Retention Index Molecular formula Standard for quantification Fragmentation Ion for identification Calibration Curves
β-Myrcene 13.977 1173 C10H16 β-Myrcene 41/69/93 41/93 y = 3350.8x − 1.0946
Phellandrene 13.756 1165 C10H16 Limonene 77/93/91/136 77/93 y = 306.8x + 0.9404
β-trans-Ocimene 16.662 1251 C10H16 β-Myrcene 79/93/121 79/93 y = 3350.8x − 1.0946
γ-Terpinene 17.184 1253 C10H16 Terpinolene 91/93/121/136 93/121 y = 300.19x + 1.3797
β-cis-Ocimene 17.386 1242 C10H16 β-Myrcene 79/93/121 79/93 y = 3350.8x − 1.0946
Terpinolene 18.747 1291 C10H16 Terpinolene 91/93/121/136 93/121 y = 300.19x + 1.3797
Cis Rose oxide 21.629 1338 C10H18O Rose oxide 69/139/154 139 y = 37.312x + 3.259
trans-Rose oxide 22.289 1375 C10H18O Rose oxide 69/139/154 139 y = 37.312x + 3.259
(E,Z)-Allo-Ocimene 22.518 1381 C10H16 β-Myrcene 105/121/136 105/121 y = 3350.8x − 1.0946
Allo-Ocimene 23.471 1397 C10H16 β-Myrcene 105/121/136 121/136 y = 3350.8x − 1.0946
nerol oxide 26.414 1480 C10H16O Nerol 41/67/68/83 68/83 y = 930.79x + 8.9527
Citronellal 26.776 1765 C10H18O Citronellal 41/69/95/121 41/69 y = 70680x + 43.97
Neral 34.916 1755 C10H16O citral 41/69/109 41/69 y = 52.961x + 2.6933
geranial 37.006 1680 C10H16O citral 41/69/84 41/69 y = 52.961x + 2.6933
cis-isogeraniol 39.415 1818 C10H18O Geraniol 41/81/109/121 41/81/109 y = 1476.8x + 0.392
Geranic acid 56.744 2340 C10H16O2 Geranic acid 41/69/100 41/69/100 y = 6818.4x + 7.8939
Linalool 29.627 1581 C10H18O Linalool 55/71/93/121 93 y = 396.8x + 3.2904
α-Terpineol 35.647 1710 C10H18O α-Terpineol 59/93/121/136 136 y = 958.5x + 5.9227
Nerol 39.384 1797 C10H18O Nerol 41/69/93 69 y = 930.79x + 8.9527
Geraniol 41.043 1857 C10H18O Geraniol 41/69 69 y = 1476.8x + 0.392
Citronellol 37.966 1766 C10H20O β-Citronellol 41/69/82/95 69 y = 1323.9x + 0.3414
Limonene 15.223 1205 C10H18O2 Limonene 68/93/121/136 68/93 y = 306.8x + 0.9404
cis-furan linalool oxide 25.175 1448 C10H18O2 Linalool 41/43/59/68 59/94 y = 396.8x + 3.2904
trans-furan linalool oxide 26.567 1477 C10H18O2 Linalool 41/43/59/68 59/94 y = 396.8x + 3.2904
Linalool oxide pyranoside 37.143 1691 C10H18O2 Linalool 41/43/59/68 68 y = 396.8x + 3.2904
trans-isogeraniol 39.751 1829 C10H18O Geraniol 41/81/109/121 121 y = 1476.8x + 0.392

Quantification of the compounds

The quantification procedure used in this study was based on previous work by Cai31. A synthetic matrix was prepared in distilled water containing 7 g/l tartaric acid and 200 g/l glucose. The pH was adjusted to 3.3 with a 5 M NaOH solution. The standard solutions contained thirteen terpenes and had fifteen levels, each of which was the halve concentration of the previous level. These solutions were extracted and analyzed under the same conditions as those of the grape samples. An internal standard (4-methyl-2-pentanol, 10 mL, 1.0018 g/l in water) was added to both the standard solutions and samples before aroma extraction and analysis. The calibration curves for analytes were established with regression coefficients above 98%. The concentrations of volatile compounds for which it was not possible to establish calibration curves were estimated on the basis of the equations of compounds with the same functional groups and/or similar numbers of C atoms. Data management and analysis were performed using ChemStation software (Agilent Technologies, Santa Clara, California, United States).

Data Records

A total of 108 raw metabolite data files were deposited in MetaboLights32, including the free-form and glycoside-bound data of 27 samples (two technical replicates). The relative peak areas, the concentration of all samples and the statistically analyzed results were deposited in figshare33.

Technical Validation

There were three biological replicates and two technical replicates for each sample. The final concentrations of the free and bound forms of the compounds were analyzed by statistics and are listed in Online-only Table 1 and Online-only Table 2.

Online-only Table 1.

The concentration of free-form terpenes.

terpenes X Y Z
EL35 SE EL36 SE EL38 SE EL35 SE EL36 SE EL38 SE EL35 SE EL36 SE EL38 SE
β-Myrcene 5.55c 0.52 181.88a 16.93 66.79b 8.82 3.18c 0.12 6.32c 3.57 19.67c 6.92 7.73c 1.56 20.08c 14.50 70.36b 12.11
phellandrene 1.4c 0.20 25.85a 2.12 10.73b 1.33 0.59c 0.03 1.19c 0.61 3.53c 1.02 1.26c 0.22 3.31c 1.83 10.94b 2.07
β-trans-Ocimene nd N/A 52.92a 3.02 22.37b 4.30 3.41ef 0.06 3.37ef 1.06 7.51d 1.85 3.91def 0.33 6.93de 3.29 16.73c 2.43
γ-Terpinene nd N/A 3.9a 0.62 2.93b 0.38 nd N/A 1.24e 0.14 1.69cd 0.23 1.35de 0.02 1.42de 0.17 1.97c 0.17
β-cis-Ocimene 3.55ef 0.17 105.61a 6.19 46.92b 8.81 nd N/A 4.56ef 2.31 13.54d 4.24 5.54def 0.68 11.94de 6.85 32.81c 5.10
Terpinolene 1.29c 0.02 16.65a 0.94 15.34a 7.17 1.13c 0.01 1.8c 0.96 5.97b 1.34 2.11c 0.09 4.28b 0.83 6.16b 0.68
Cis-Rose oxide 1.17d 0.03 2.45b 0.10 1.2d 0.03 nd N/A 1.01d 0.02 1.06d 0.03 1.15d 0.04 1.98c 0.39 5.48a 0.72
trans-Rose oxide nd 0.00 1.31b 0.03 nd 0.00 nd N/A nd N/A nd N/A nd 0.01 1.16c 0.11 2.17a 0.23
(E,Z)-Allo-Ocimene nd N/A 28.99a 1.97 17.03b 2.05 2.55ef 0.02 3.1de 0.73 5.9d 1.34 3.48de 0.22 5.34de 2.17 12.04c 1.56
Allo-Ocimene nd N/A 11.51a 0.60 7.58b 0.69 2.54e 0.02 2.74de 0.24 3.7d 0.44 2.83de 0.08 3.46de 0.71 5.94c 0.57
nerol oxide 23.81cde 4.04 202.76a 13.86 60.58b 7.13 8.1e 0.66 12.83e 1.21 16.56de 1.05 39.42bce 3.81 44.86bc 11.02 208.69a 25.86
Neral nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd 0.07 2.71b 0.55 7.83a 1.05
geranial 2.27ab 0.18 9.38b 0.53 2.57ab 1.59 nd N/A 1.83ab 0.11 2.03ab 0.57 3.07ab 1.20 4.22ab 6.43 49.18a 6.32
cis-isogeraniol nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A 43.33a 7.20
Geranic acid 42.73cd 3.44 67.02bcd 5.26 75.23bc 25.84 13.7d 3.01 40.9cd 1.81 32.04cd 8.94 102.6ab 30.68 40.85cd 36.64 144.59a 54.50
Linalool 8.43e 1.63 1473.24a 85.83 407.39b 50.65 3.87e 0.19 26.27e 22.51 118.76d 35.07 23.33e 1.93 118.88d 43.87 213.87c 15.84
4-Terpineol 1.32e 0.27 9.52a 0.36 7.11b 0.81 1.07e 0.09 1.05e 0.65 4.96c 0.74 1.7de 0.10 2.04de 0.32 2.92d 0.24
α-Terpineol 10.7e 0.62 181.57a 11.42 118.04b 16.39 9.05e 0.21 16.85e 13.66 99.24c 13.21 23.63e 1.16 53.25d 5.86 59.13d 6.90
Nerol 17.76b 1.78 149.16b 9.59 33.62b 15.91 2.7b 1.00 16.12b 2.82 26.58b 5.88 23.52b 10.26 43.46b 76.11 1572.38a 283.38
Geraniol 49.91d 5.06 335.44b 24.83 90.86cd 67.12 25.84d 5.20 45.67d 6.52 65.83d 19.63 137.19cd 60.46 187.85c 369.05 1035.58a 387.88
Citronellol 3.86c 0.54 13.63b 0.90 2.02c 1.27 1.8c 0.05 2.03c 0.06 1.94c 0.18 3.6c 0.87 3.94c 5.18 40.86a 6.09
Limonene 2.08e 0.22 82.01a 4.38 21.67bc 6.38 1.13e 0.06 3.69e 3.08 16.07cd 4.46 4.83e 0.40 12.54d 4.33 25.64b 3.89
α-muurolene nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A 3.09a 0.09
cis-furan linalool oxide 3.35bc 0.34 12.86a 0.60 3.71b 0.15 nd 0.00 0.5d 0.54 3.44bc 0.17 2.8c 0.13 3.43bc 0.33 4.05b 0.15
trans-furan linalool oxide 1.73c 0.31 10.02a 0.46 3b 0.24 nd 0.00 0.25d 0.25 1.74c 0.24 1.85c 0.15 1.44c 0.25 2.7b 0.18
Linalool oxide pyranoside 0.45d 0.20 8.12a 0.44 3.68b 0.28 nd N/A 0.42d 0.44 2.79c 0.28 0.27d 0.06 2.51c 0.23 3.65b 0.13
trans-isogeraniol nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A 39.26a 6.24

X, Y, and Z represent the cultivars Xiangfei, Italia and Zaomeiguixiang, respectively. Different letters represent significance levels of P < 0.05, and nd stands for nondetected. N/A stands for not available and SE stands for standard error.

Online-only Table 2.

The concentration of the bound-form terpene.

terpenes X Y Z
EL35 SE EL36 SE EL38 SE EL35 SE EL36 SE EL38 SE EL35 SE EL36 SE EL38 SE
β-Myrcene nd N/A 226.64cd 2.85 463.98c 12.03 nd N/A nd 1.62 168.21cd 6.48 nd N/A 2465.33a 79.12 1262.42b 26.56
phellandrene nd N/A 5.79c 0.01 9.51bc 0.33 nd N/A nd N/A nd N/A nd N/A 20.10a 0.50 12.42b 0.15
β-trans-Ocimene nd N/A 41.87d 1.44 115.39c 3.38 nd N/A 14.67d 0.46 29.71d 1.34 36.72d 0.95 601.16a 19.26 279.24b 6.18
γ-Terpinene nd N/A nd N/A 8.79c 0.07 nd N/A nd N/A nd N/A 7.82c 0.02 26.43a 0.69 15.75b 0.20
β-cis-Ocimene 36.92d 2.32 90.13d 2.91 227.08c 6.60 2.12d 0.26 44.46d 0.79 62.31d 2.62 75.26d 2.77 1176.79a 37.71 567.18b 11.97
Terpinolene 7.51d 0.03 8.71c 0.05 11.89c 0.14 nd N/A 7.48c 0.02 7.98c 0.04 8.34c 0.03 41.82a 1.14 20.90b 0.29
cis Rose oxide 16.64d 0.01 16.68cd 0.01 16.95c 0.02 nd N/A 16.44d 0.01 16.55d 0.01 16.68cd 0.01 22.74a 0.18 19.24b 0.04
trans-Rose oxide 16.41cd 0.00 16.43cd 0.00 16.52c 0.01 nd N/A 16.35d 0.00 16.39d 0.00 16.42cd 0.00 18.50a 0.06 17.32b 0.01
(E,Z)-Allo-Ocimene nd N/A 12.13d 0.13 39.53c 1.34 nd N/A 4.04d 0.18 8.00d 0.05 12.19d 0.21 202.00a 6.49 94.72b 1.98
Allo-Ocimene nd N/A 4.47cd 0.08 18.92c 0.73 nd N/A nd N/A 2.36d 0.02 4.54cd 0.13 125.31a 4.10 53.04b 1.17
nerol oxide 65.11d 0.51 66.88d 0.59 96.93c 1.50 48.89d 0.37 53.89d 0.90 56.89d 0.23 100.79c 1.34 469.91a 14.54 218.50b 2.58
Citronellal 292.93d 0.92 372.55d 3.09 471.13bc 6.56 236.55d 1.31 306.75d 3.15 347.35d 4.49 365.23d 5.29 1230.16a 31.75 676.88b 7.85
Neral 14.64de 0.05 14.67de 0.03 18.75c 0.16 13.70e 0.02 14.18de 0.09 14.39de 0.02 16.33d 0.11 43.87a 0.73 24.21b 0.16
geranial 14.27e 0.03 14.71de 0.03 17.55c 0.12 13.78e 0.01 14.41e 0.08 14.73de 0.04 15.71d 0.04 30.87a 0.47 19.83b 0.09
cis-isogeraniol nd N/A 8.38cd 0.13 11.89bc 0.25 nd N/A nd N/A 6.22cd 0.05 6.56cd 0.07 40.45a 1.15 18.46b 0.22
Geranic acid 579.99d 14.63 367.87d 21.20 2921.57b 109.64 185.55d 15.29 308.82d 28.46 450.35d 8.47 1775.95c 15.06 4971.88a 134.20 967.30cd 15.75
Linalool 22.12c 0.10 175.18a 5.19 179.63a 4.87 17.57c 0.06 27.94c 0.81 71.82b 1.96 28.53c 0.28 204.30a 6.24 102.95b 1.34
α-Terpineol 31.96c 0.03 34.06c 0.10 39.58b 0.31 30.85c 0.05 32.64c 0.20 33.07c 0.10 33.84c 0.15 66.02a 1.15 42.13b 0.23
Nerol 228.83c 3.79 506.78c 13.28 824.18c 21.56 86.67c 0.65 205.77c 2.90 308.27c 11.35 298.33c 7.02 4215.95a 129.51 2267.67b 37.62
Geraniol 146.64d 1.56 223.76d 4.15 442.51c 10.72 96.09d 0.61 181.65d 0.72 230.27d 6.39 257.38d 2.88 1130.06a 31.58 642.51b 8.88
Citronellol 12.48e 0.95 36.26d 0.98 64.26c 1.10 17.44de 0.48 14.32e 0.33 22.21de 0.16 32.69de 0.34 190.26a 4.70 116.94b 1.51
Limonene 7.20d 0.22 12.71cd 0.23 22.03c 0.41 8.35cd 0.11 7.62cd 0.08 9.45cd 0.04 12.55cd 0.08 112.07a 3.38 59.24b 1.08
α-muurolene nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A
cis-furan linalool oxide nd N/A 18.90b 0.03 18.24c 0.03 nd N/A nd N/A nd N/A nd N/A 21.03a 0.02 18.38c N/A
trans-furan linalool oxide nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A
Linalool oxide pyranoside nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A nd N/A 19.77a 0.01 nd N/A
trans-isogeraniol nd N/A 3.74cd 0.01 4.97bc 0.02 nd N/A nd N/A nd N/A nd N/A 17.38a 0.52 7.97b 0.10

X, Y, Z represent the cultivars Xiangfei, Italia and Zaomeiguixiang. Different letters represent significant levels of P < 0.05, and nd stands for nondetected. N/A stands for not available, SE stands for standard error.

Usage Notes

The final concentration of all the samples were presented in excel files and deposited in the figshare. Figure 2 shows the heatmap of terpene concentration for three cultivars at three stages. Figure 3 shows the PCA analysis results.

Fig. 2.

Fig. 2

Heatmap of terpene concentration in table grapes during three developmental stages.

Fig. 3.

Fig. 3

PCA analysis of terpene concentration at three stages.

The B represents the glycoside-bound form. F represents the free volatile form. The A, B, and C at the bottom of the X axis represent the berry developing stages EL35, EL36 and EL38, respectively. XF and ZMGX represent the cultivars Xiangfei and Zaomeiguixiang, respectively.

X stands for Xiangfei, Y stands for Italia, Z stands for Zaomeiguixiang, the terpene names of C1-C26 were shown in Table 1.

Supplementary information

Supplementary File 1 (13.8KB, docx)

Acknowledgements

This work was supported by the Beijing Academy of Agricultural and Forestry Sciences (KJCX20180411) and the China Agriculture Research System (CARS-29).

Online-only Tables

Author contributions

L.S. designed the experiments and wrote the manuscript, B.Q.Z. analyzed the data, X.Y.Z. collected the samples and performed the GC-MS experiment. G.J.Z., A.L.Y., H.L.W. and X.Y.W. review the manuscript, H.Y.X. designed the experiments, reviewed the manuscript and supervised the study.

Code availability

The code for the heatmap and PCA analysis is available in Supplementary file 1.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

is available for this paper at 10.1038/s41597-019-0321-1.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Sun L. 2019. The accumulation profiles of Terpene metabolites of three Muscat table grape cultivars through HS-SPME-GCMS. MetaboLights. MTBLS968 [DOI] [PMC free article] [PubMed]
  2. Sun L. 2019. The accumulation profiles of Terpene metabolites of three Muscat table grape cultivars through HS-SPME-GCMS. figshare. [DOI] [PMC free article] [PubMed]

Supplementary Materials

Supplementary File 1 (13.8KB, docx)

Data Availability Statement

The code for the heatmap and PCA analysis is available in Supplementary file 1.


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