242个鲜食葡萄品种果实香气组分数据集

doi:10.19788/j.issn.2096-6369.100023

Abstract

Abstract:

Aroma is one of the important quality traits of grapes and a focus of research on grape quality as well as an essential aspect of molecular design breeding. Grapes have a rich germplasm resource, which also exhibits abundant genetic diversity in aroma traits. In this study, solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME-GC-MS) was used to measure the aromatic components and their contents in the fruit of 242 grape varieties. The study also conducted correlation analyses between the components and sensory evaluation, inter-component correlations, and principal component analysis among the varieties. A total of 526 volatile components were detected, and 108 potential aroma components were screened, including esters, alcohols, aldehydes, ketones, terpenes, hydrocarbons, acids, and furans, covering eight types. Esters were the most numerous, followed by terpenes, while aldehydes were the most frequent, followed by hydrocarbons and alcohols. The top ten components with the highest correlation coefficients related to aroma sensory evaluation included six esters, three terpenes, and one hydrocarbon, with ethyl hexanoate having the highest correlation coefficient, followed by ethyl 2-hexenoate and linalool. Components of the same type exhibited high correlations, especially esters, terpenes, and furans, while correlations between different types were relatively low. Principal component analysis showed that most of the varieties clustered together and diverged in three principal component directions, which highly corresponded with the results of the sensory evaluation. This study provides essential data support for researching the genetic diversity of grape aroma traits and the specificity of germplasm.

Data summary:

Items	Description
Dataset name	Dataset of Aromatic Components from the Fruits of 242 Table Grape Varieties
Specific subject area	Agronomy, biology
Research topic	Grape aroma components and content
Time range	2023-2024
Temporal resolution	year
Geographical scope	Huailai County, Zhangjiakou City, Hebei Province
Data types and technical formats	.XLS and.XLSX
Dataset structure	This dataset consists of 248 tabular data entries, primarily including GC-MS measurement results of fruit aroma from 242 grape varieties, summaries of volatile components and abundance, summaries of aroma components and abundance, sensory evaluation, correlations between aroma components and sensory evaluation, and correlations among aroma components.
Volume of dataset	39.54 MB
Data accessibility	DOI：https://doi.org/10.57760/sciencedb.agriculture.00107 CSTR： https://cstr.cn/17058.11.sciencedb.agriculture.00107
Financial support	National Key R&D Program(2023YFD1200103); National Agricultural Science and Technology Park Special Project (2021C-01); Key R&D Plan of Shandong Province (2022TZXD0010); The Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2021-RIP-02); Huailai Grape and Wine Industry Science & Technology Task Force

Key words: grape, aroma, GC-MS, genetic diversity

JI XiaoHao, WU YaJing, YU YiFei, WANG XiaoDi, LIU FengZhi, LI MingLiang, WANG He, LIU Xia, LIU Jun, WANG HaiBo. Dataset of Aromatic Components from the Fruits of 242 Table Grape Varieties[J].Journal of Agricultural Big Data, 2025, 7(1): 118-125.

Figures/Tables 6

Table 1

Table 2

Table 3

Sensory evaluation results of fruit aroma"

评价类型
Evaluation Type

品种名称
Variety Name

无香甜味
No sweet aroma

60—18—24、6—28、81—15—64、三泽系红伊豆、丛林玫瑰、东京红、丝路红、丰宝、丽红宝、井川1015（天秀）、井川101、井川1025、井川1055、京丰、亮玉、先锋（井川210）、克瑞森无核、凯旋（白香蕉）、北京红、北冰红、午夜美人、卓越公主、卓越玫瑰、卓越黑香峰、卓越黑香蜜、吉峰4号、哈尼、国绿、夏日阳光、夏至红、大宝、大青葡萄、奖尝、奥菲利亚、妮娜皇后、宇选4号、安尼斯基、山东大紫、岳红无核、峰光、峰香（井川957）、巨优（辽）、巩义无核白、巴莱莎纳（意）、布加勒斯特玫瑰B、弗雷无核、户太八号、摩尔多瓦、支那德无核、斯立潘、新星无核、新雅、无核白鸡心、早玛瑙、早玫瑰、早霞玫瑰、早黑宝、春光、昭平红、晚红宝、极高、柳子、沁香、法赫里、泽优、泽香、深红、深红无核、火焰无核、爱神玫瑰、玉波一号、玫瑰后、玫瑰露、玫香怡、玲珑指、瑞比尔、瑞都早红、瑞都红玉、瑞都红玫、瑰宝、甜峰、田野黑、白夏尼、白奥林、白瓦沙卡、白老虎眼、白马拉加、皇冠、皇家秋天、秋岭、秋黑、科瑞森、粒丽特、索索葡萄、紫王葡萄、紫香无核、累克基特、红义、红伊豆、红光无核、红地球、红大久保、红宝石、红宝石无核、红提、红玲珑、红瑞宝、红皇佳、红皇后、红艳无核、红芭拉多芽变、红高、绯红（乍娜）、美丽无核、翠玉、花泽1号、茉莉、蜜红、贝加干酒、达美娜、郑州早红、醉金香、金光、金峰、金田06082、金田0608、金田三号、金田六号、金田皇家无核、金田美指、金田蓝宝石、金田蜜、长穗无核白、阿依布拉、阿克塔尔、阿卡达依、阿古西卡龙、阿富汗、阿尔曼玫瑰、雄宝、霍里冈、音田、高妻、鲜葡3号、鲜葡4号、黄意大利、黄金蜜、黎明无核、黑三多利、黑元帅、黑×国、黑奥林、黑峰、黑拉查基、黑旋风、黑爱默无核、黑玫香、黑脆无核、龙宝（井川668）

有香甜味
With sweet aroma

11—39、228、64—1—19、79—05—6、87—1葡萄、M1803、NY14528、一品香、二号白香、井川1014、井川1288、井川666、京蜜、京超、佐藤、吉峰9号、嘟噜玫、国宝、圣诞玫瑰、地拉洼、大粒玫瑰香、大阪48202、天使玫瑰香、奥托玫瑰、尼加拉、巨优、巨峰、希姆劳德、康能无核、新郁、早巨选、早熟黑虎、早甜、晚黑宝、晨香、柔丁香、楼都蓓蕾、歌德、泽山一号、洛阳2号、浙江大叶水晶、爱欧娜、玉波二号、玫瑰怡、玫瑰香、琥珀、瑞都科美、瑞都香玉、甜玫瑰、甲州、白玫康、秋红宝、秋蜜、粉红亚都蜜、红斯威特、红茧、纽约玫瑰、绍兴1号、翠红宝、翠香宝、茉莉香、蓓蕾、蜜汁、贵州水晶、选拔巨峰、郑巨1号、郑巨2号、郑康1号、郑果21号、郑果8号、郑黑、金手指、金星无核、金田玫瑰、阪琢、阳光玫瑰、阿拉卡其、阿登纳玫瑰、霸王、香妃、香悦、高尾、黑阿尔法

Table 3

Table 4

Fig. 1

Fig. 2

References 18

[1]	穆维松, 冯建英, 田东, 等. 我国鲜食葡萄产业的国际贸易与国内需求形势. 中国果树, 2019(2):5-10.
[2]	姚於康, 于珩, 孙洪武. 江苏葡萄市场消费特征与需求偏好调查分析. 江苏农业科学, 2020, 48(21):320-328.
[3]	刘翔, 董志刚, 李晓梅, 等. 山西地区5个酿酒白葡萄果实品质及香气分析. 山西农业科学, 2022, 50(12):1647-1653.
[4]	肖慧琳, 徐维华, 郑秋玲, 等. 烟台产区三个葡萄品种原酒和蒸馏酒香气分析. 中外葡萄与葡萄酒, 2023(5):78-85.
[5]	荀志丽, 马小河, 黄丽萍, 等. 47份鲜食葡萄种质资源果实香气品质鉴定分析. 山西农业大学学报(自然科学版), 2023, 43(5):83-91.
[6]	张克坤, 王海波, 王孝娣, 等. ‘瑞都香玉’葡萄果实挥发性成分在果实发育过程中的变化. 中国农业科学, 2015, 48(19):3965-3978. doi: 10.3864/j.issn.0578-1752.2015.19.018
[7]	张文文, 吴玉森, 陈毓谨, 等. 3种巨峰系葡萄的香气特征. 上海交通大学学报(农业科学版), 2018, 36(5):51-59+66.
[8]	马宗桓, 李玉梅, 韦霞霞, 等. 河西走廊不同产地‘美乐’葡萄品质及香气物质的差异分析.园艺学报:1-16.
[9]	张海军, 张娟, 贾毅男, 等. 不同架式对‘南太湖特早’葡萄果实香气成分及品质的影响. 中国农业科技导报, 2024, 26(1):201-213.
[10]	王海霞, 蒋娅萍, 方艳, 等. 外源水溶性β-葡聚糖对‘贵人香’葡萄果实糖苷酶及香气品质的影响.园艺学报:1-17.
[11]	蒋娅萍, 方艳, 王海霞, 等. 外源油菜素内酯对霞多丽和黑比诺葡萄品质的影响. 果树学报, 2023, 40(12):2574-2590.
[12]	夏澜, 傅伟红, 应永涛, 等. 表油菜素内酯对‘阳光玫瑰’葡萄果实品质的影响. 中外葡萄与葡萄酒, 2023(4):82-88.
[13]	孙磊, 朱保庆, 孙晓荣, 等. ‘亚历山大'葡萄果实单萜生物合成相关基因转录及萜类物质积累规律. 中国农业科学, 2014, 47(7): 1379-1386. doi: 10.3864/j.issn.0578-1752.2014.07.015
[14]	冀晓昊, 刘凤之, 王宝亮, 等. 葡萄醇酰基转移酶编码基因遗传变异研究. 中国农业科学, 2022, 55(14):2797-2811.
[15]	朱捷, 何微, 高琳, 等. 顶空固相微萃取法分析葡萄蒸馏酒香气中酯类成分差异. 食品工业, 2024, 45(1):275-280.
[16]	谢林君, 王海军, 张劲, 等. 基于GC-MS和香韵法分析阳光玫瑰葡萄贮藏过程香气特征变化. 现代食品科技, 2023, 39(9):296-306.
[17]	吕茜, 孙晓涵, 汪佳琪, 等. 鲜食、酿酒、观赏类葡萄果实挥发性风味物质解析. 食品与发酵工业, 2024, 50(2):296-305. doi: 10.13995/j.cnki.11-1802/ts.034351
[18]	王文治, 陈璐, 米艳华, 等. 基于顶空固相微萃取-气相色谱-质谱法鉴别3种葡萄香气特征成分. 食品安全质量检测学报, 2022, 13(24): 8075-8082.

组分类型 Component type	种类数 Number of types	频次 Frequency		定性 Qualitative		面积 Area
组分类型 Component type	种类数 Number of types	范围 Range	均值 Mean	范围 Range	均值 Mean	范围 Range	均值 Mean
酯类Esters	34	1—190	24.7	64—95.5	80.5	1739437—313483143.4	27278297.55
醇类Alcohols	14	2—210	31.8	60—92.5	75.1	1587311.5—130636795.9	24780510.8
醛类Aldehydes	17	3—225	49.3	65—95.1	77.2	1527108.8—207780891.9	24753293.6
酮类Ketones	4	1—68	26.2	76.7—93	84.2	1683248—43867825.9	13269510.3
萜类Terpenes	26	2—42	12.7	64—93.5	81.3	2080124.7—414970911.6	27608499.8
烃类Hydrocarbons	3	19—51	33.3	82—97.6	90.4	4712060.4—9023715.2	6276010.2
酸类Acids	1	—	9.0	—	71.6	—	2619463.9
呋喃类Furans	9	3—52	22.3	71.7—92.2	81.8	2716603.2—141689093.8	28872204.2

组分名称 Component name	化合物类型 Compound type	相关系数 Correlation coefficient
己酸乙酯	酯类	0.338829609
2-己烯酸乙酯	酯类	0.31596594
芳樟醇	萜类	0.313209155
α-萜品醇	萜类	0.290269446
乙酸乙酯	酯类	0.283098762
β-香茅烯	萜类	0.279154223
2-丁烯酸乙酯	酯类	0.277982982
丁酸乙酯	酯类	0.269067746
D-柠檬烯	烃类	0.26541474
辛酸乙酯	酯类	0.253074409

Dataset of Aromatic Components from the Fruits of 242 Table Grape Varieties

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