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通过液相色谱和多变量曲线解析研究浆果中生物活性化合物的提取和定量质量。

Investigating the quality of extraction and quantification of bioactive compounds in berries through liquid chromatography and multivariate curve resolution.

机构信息

Department of Chemistry, Centre for Analysis and Synthesis, Lund University, P.O. Box 124, 22100, Lund, Sweden.

Department of Chemistry, Division of Biotechnology, Lund University, Lund, Sweden.

出版信息

Anal Bioanal Chem. 2024 Oct;416(24):5387-5400. doi: 10.1007/s00216-024-05474-8. Epub 2024 Aug 15.

Abstract

Berries are a rich source of natural antioxidant compounds, which are essential to profile, as they add to their nutritional value. However, the complexity of the matrix and the structural diversity of these compounds pose challenges in extraction and chromatographic separation. By relying on multivariate curve resolution alternating least squares (MCR-ALS) ability to extract components from complex spectral mixtures, our study evaluates the contributions of various extraction techniques to interference, extractability, and quantifying different groups of overlapping compounds using liquid chromatography diode array detection (LC-DAD) data. Additionally, the combination of these methods extends its applicability to evaluate polyphenol degradation in stored berry smoothies, where evolving factor analysis (EFA) is also used to elucidate degradation products. Results indicate that among the extraction techniques, ultrasonication-assisted extraction employing 1% formic acid in methanol demonstrated superior extractability and selectivity for the different phenolic compound groups, compared with both pressurized liquid extraction and centrifugation of the fresh berry smoothie. Employing MCR-ALS on the LC-DAD data enabled reliable estimation of total amounts of compound classes with high spectral overlaps. Degradation studies revealed significant temperature-dependent effects on anthocyanins, with at least 50% degradation after 7 months of storage at room temperature, while refrigeration and freezing maintained fair stability for at least 12 months. The EFA model estimated phenolic derivatives as the main possible degradation products. These findings enhance the reliability of quantifying polyphenolic compounds and understanding their stability during the storage of berry products.

摘要

浆果是天然抗氧化化合物的丰富来源,这些化合物对于评估其营养价值至关重要。然而,基质的复杂性和这些化合物的结构多样性给提取和色谱分离带来了挑战。本研究依靠多元曲线分辨交替最小二乘法(MCR-ALS)从复杂光谱混合物中提取成分的能力,评估了各种提取技术对干扰、提取能力的贡献,并使用液相色谱二极管阵列检测(LC-DAD)数据定量分析不同重叠化合物组。此外,这些方法的结合扩展了其在评估储存浆果冰沙中多酚降解的适用性,其中还使用演变因子分析(EFA)来阐明降解产物。结果表明,在提取技术中,与加压液体提取和新鲜浆果冰沙离心相比,甲醇中 1%甲酸辅助超声提取对不同酚类化合物组具有更好的提取能力和选择性。在 LC-DAD 数据上应用 MCR-ALS 能够可靠估计具有高光谱重叠的化合物类别的总量。降解研究表明,温度对花色苷有显著的依赖性影响,在室温下储存 7 个月后至少降解 50%,而冷藏和冷冻至少能保持 12 个月的良好稳定性。EFA 模型估计酚类衍生物是主要的可能降解产物。这些发现提高了定量分析多酚化合物及其在浆果产品储存过程中稳定性的可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4638/11416369/9af45121dcb4/216_2024_5474_Fig1_HTML.jpg

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