采用新型 LC-QTOF-MS/MS 方法分析希腊 Vradiano、Limnio 和 Kotsifali 栽培品种红葡萄皮的花青素和原花青素概况。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Phytochemical Analysis Pub Date : 2024-12-01 Epub Date: 2024-06-11 DOI:10.1002/pca.3400
Christina Karadimou, Elissavet Petsa, Niki-Athina Ouroumi, Emmanouil-Nikolaos Papadakis, Nikolaos Kontoudakis, Serafeim Theocharis, Ioannis Mourtzinos, Urania Menkissoglu-Spiroudi, Natasa P Kalogiouri, Stefanos Koundouras
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引用次数: 0

摘要

简介:酿酒葡萄品种 Kotsifali、Limnio 和 Vradiano 目标:本研究旨在开发一种液相色谱四极杆飞行时间串联质谱(LC-QTOF-MS/MS)方法,采用目标筛选和可疑筛选策略来检测希腊葡萄品种的花青素和原花青素含量:开发并验证了一种新型的 LC-QTOF-MS/MS 方法,用于评估 Kotsifali、Limnio 和 Vradiano 葡萄品种的花青素含量。从希腊各品种的主要种植区采集了 16 份葡萄样品。采用化学计量学方法研究了葡萄品种对希腊三种酿酒葡萄的花青素和原花青素组成的影响:所有目标分析物的线性关系都很好(R2 > 0.99),回收率在 90.1%和 119.1%之间。计算得出的定量限(LOQ)和检出限(LOD)分别为 0.020-0.40 mg/g 和 0.010-0.13 mg/g。日内和日间研究的 RSD%分别低于 9.1%和 7.3%,表明真实度和精密度令人满意。目标筛选和疑似筛选分别鉴定出 5 种和 26 种花青素:结论:与 Vradiano 和 Limnio 相比,Kotsifali 品种的花青素含量更高。结论:与 Vradiano 和 Limnio 相比,Kotsifali 品种表现出更高的花青素浓度,不同品种的平均聚合度(mDp)水平更高,原蝶呤含量(%P)也不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploration of the anthocyanin and proanthocyanidin profile of Greek red grape skins belonging to Vradiano, Limnio, and Kotsifali cultivars, analyzed by a novel LC-QTOF-MS/MS method.

Introduction: Winegrape varieties Kotsifali, Limnio, and Vradiano OBJECTIVE: The aim of this study was to develop a liquid chromatographic quadrupole time-of-flight tandem mass spectrometric (LC-QTOF-MS/MS) method for the investigation of the anthocyanin and proanthocyanidin content of Greek grape varieties employing target and suspect screening strategies.

Methodology: A novel LC-QTOF-MS/MS method was developed and validated to assess the anthocyanin content of Kotsifali, Limnio, and Vradiano grape varieties. Sixteen grape samples were collected from the main growing areas of each variety in Greece. The influence of the grape variety on the anthocyanin and proanthocyanidin composition of three Greek winegrapes was investigated using chemometrics.

Results: Excellent linearity (R2 > 0.99) was achieved for all the target analytes, and recoveries ranged between 90.1% and 119.1%. The limits of quantification (LOQs) and limits of detection (LODs) were calculated over the range of 0.020-0.40 mg/g and 0.010-0.13 mg/g, respectively. The RSD% was lower than 9.1% and 7.3% for intra-day and inter-day studies, respectively, indicating satisfactory trueness and precision. Target and suspect screening resulted in the identification of 5 and 26 anthocyanins, respectively.

Conclusions: Kotsifali variety exhibited a higher concentration of anthocyanins compared with Vradiano and Limnio. Higher levels of mean degree of polymerization (mDp) and different percentage levels of prodelphinidins (%P) were established among the varieties.

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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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