Grape Must Profiling And Cultivar Discrimination Based On Amino Acid Composition And General Discriminant Analysis With Best Subset

IF 1.1 4区 农林科学 Q4 FOOD SCIENCE & TECHNOLOGY South African Journal of Enology and Viticulture Pub Date : 2019-06-27 DOI:10.21548/40-2-3373
Gabriella Petrovic, J. Aleixandré-Tudo, A. Buica
{"title":"Grape Must Profiling And Cultivar Discrimination Based On Amino Acid Composition And General Discriminant Analysis With Best Subset","authors":"Gabriella Petrovic, J. Aleixandré-Tudo, A. Buica","doi":"10.21548/40-2-3373","DOIUrl":null,"url":null,"abstract":"The present study aimed to elucidate the amino acid profile of a number of grapevine cultivars relevant to the South African wine industry using 738 grape must samples obtained during the 2016 and 2017 harvests.  Proline and arginine were found to be the most abundant amino acids, with an average of 697.69 mg/L for proline (range 33.22-3445.43 mg/L) and 388.35 mg/L for arginine (range 13.56-1616.56 mg/L) across all vintages, regions, and cultivars. At the other extreme, ornithine (2.01 mg/L), glycine (3.28 mg/L), methionine (3.64 mg/L) and lysine (3.91 mg/L) were found to have the lowest concentrations, both in terms of the overall average, as well as per cultivar. Furthermore, the data were used to demonstrate how characteristic the amino acid profile is of a particular group (red or white) or cultivar. Cultivars were predicted based on their average amino acid concentrations using general discriminant analysis (GDA) and the best subset principle. For white musts, Chardonnay showed the highest prediction accuracy (100%), and Pinotage (75%) for red cultivars. Overall, the white cultivars included in this study were more accurately distinguished from one another (75.6%) compared to the red (60.1%). This predictive ability was subsequently compared to the accuracy of predicting cultivars based on only the arginine and proline concentrations as well as the ratio between the two. The use of only these amino acids as well as the addition of the proline/arginine ratio as a predictor variable did not offer satisfactory discriminatory power between either white or red cultivars.","PeriodicalId":21894,"journal":{"name":"South African Journal of Enology and Viticulture","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.21548/40-2-3373","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Enology and Viticulture","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.21548/40-2-3373","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 4

Abstract

The present study aimed to elucidate the amino acid profile of a number of grapevine cultivars relevant to the South African wine industry using 738 grape must samples obtained during the 2016 and 2017 harvests.  Proline and arginine were found to be the most abundant amino acids, with an average of 697.69 mg/L for proline (range 33.22-3445.43 mg/L) and 388.35 mg/L for arginine (range 13.56-1616.56 mg/L) across all vintages, regions, and cultivars. At the other extreme, ornithine (2.01 mg/L), glycine (3.28 mg/L), methionine (3.64 mg/L) and lysine (3.91 mg/L) were found to have the lowest concentrations, both in terms of the overall average, as well as per cultivar. Furthermore, the data were used to demonstrate how characteristic the amino acid profile is of a particular group (red or white) or cultivar. Cultivars were predicted based on their average amino acid concentrations using general discriminant analysis (GDA) and the best subset principle. For white musts, Chardonnay showed the highest prediction accuracy (100%), and Pinotage (75%) for red cultivars. Overall, the white cultivars included in this study were more accurately distinguished from one another (75.6%) compared to the red (60.1%). This predictive ability was subsequently compared to the accuracy of predicting cultivars based on only the arginine and proline concentrations as well as the ratio between the two. The use of only these amino acids as well as the addition of the proline/arginine ratio as a predictor variable did not offer satisfactory discriminatory power between either white or red cultivars.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于氨基酸组成和最佳子集一般判别分析的葡萄品种特征分析
本研究旨在利用2016年和2017年收获期间获得的738个葡萄样品,阐明与南非葡萄酒行业相关的一些葡萄品种的氨基酸特征。脯氨酸和精氨酸含量最高,平均含量为697.69 mg/L (33.22 ~ 3445.43 mg/L),精氨酸为388.35 mg/L (13.56 ~ 1616.56 mg/L)。在另一个极端,鸟氨酸(2.01 mg/L)、甘氨酸(3.28 mg/L)、蛋氨酸(3.64 mg/L)和赖氨酸(3.91 mg/L)的浓度最低,无论就总体平均值而言,还是就每个品种而言。此外,这些数据被用来证明一个特定群体(红色或白色)或品种的氨基酸特征。利用一般判别分析(GDA)和最佳子集原理对品种的平均氨基酸浓度进行预测。对于白葡萄品种,霞多丽的预测准确率最高(100%),而对于红葡萄品种,皮诺塔奇的预测准确率最高(75%)。总体而言,本研究中白色品种的区分准确率(75.6%)高于红色品种(60.1%)。随后将这种预测能力与仅基于精氨酸和脯氨酸浓度以及两者之间的比值预测品种的准确性进行了比较。仅使用这些氨基酸以及添加脯氨酸/精氨酸比率作为预测变量,在白色和红色品种之间都不能提供令人满意的区分力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.50
自引率
7.70%
发文量
1
审稿时长
>36 weeks
期刊介绍: The South African Journal of Enology and Viticulture (SAJEV) publishes full-length original Research Papers, Research Notes and Review Papers on all subjects related to enology and viticulture. The SAJEV does not accept articles published in, or submitted to, other journals.
期刊最新文献
Susceptibility of Grapevine Sucker and Green Shoot Wounds to Trunk Disease Pathogens Irrigation of Agricultural Crops with Municipal Wastewater - A Review Evolution of the Polyphenolic Content of Moravian White Grape Variety Wines of Different Vintages During Storage Phylogeny of Holocacista capensis (Lepidoptera: Heliozelidae) from Vineyards and Natural Forests in South Africa Inferred from Mitochondrial and Nuclear Genes Spur Pruning Leaving One Bud is an Interesting Viticultural Strategy to Control Bud Acrotony in Bolivian Vineyards
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1