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利用近红外光谱法快速测定梅花中总黄酮含量、黄嘌呤氧化酶抑制活性和抗氧化活性。

Rapid determination of total flavonoid content, xanthine oxidase inhibitory activities, and antioxidant activity in Prunus mume by near-infrared spectroscopy.

机构信息

College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu'an City 237012, China; Anhui Province Key Laboratory for Quality Evaluation and Improvement of Traditional Chinese Medicine, Lu'an City 237012, China; Anhui Engineering Technology Center for Conservation and Utilization of Traditional Chinese Medicine Resource, Lu'an City 237012, China; Lu'an City Laboratory for Quality Evaluation and Improvement of Traditional Chinese Medicine, Lu'an City 237012, China.

College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu'an City 237012, China; Anhui Province Key Laboratory for Quality Evaluation and Improvement of Traditional Chinese Medicine, Lu'an City 237012, China; Anhui Engineering Technology Center for Conservation and Utilization of Traditional Chinese Medicine Resource, Lu'an City 237012, China; College of Pharmacy, Anhui University of Chinese Medicine, No 1. Qianjiang Road, Hefei City, Anhui Province 230012, PR China; Lu'an City Laboratory for Quality Evaluation and Improvement of Traditional Chinese Medicine, Lu'an City 237012, China.

出版信息

J Pharm Biomed Anal. 2024 Aug 15;246:116164. doi: 10.1016/j.jpba.2024.116164. Epub 2024 May 5.

Abstract

Evaluating the quality of herbal medicine based on the content and activity of its main components is highly beneficial. Developing an eco-friendly determination method has significant application potential. In this study, we propose a new method to simultaneously predict the total flavonoid content (TFC), xanthine oxidase inhibitory (XO) activity, and antioxidant activity (AA) of Prunus mume using near-infrared spectroscopy (NIR). Using the sodium nitrite-aluminum nitrate-sodium hydroxide colorimetric method, uric acid colorimetric method, and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) free radical scavenging activity as reference methods, we analyzed TFC, XO, and AA in 90 P. mume samples collected from different locations in China. The solid samples were subjected to NIR. By employing spectral preprocessing and optimizing spectral bands, we established a rapid prediction model for TFC, XO, and AA using partial least squares regression (PLS). To improve the model's performance and eliminate irrelevant variables, competitive adaptive reweighted sampling (CARS) was used to calculate the pretreated full spectrum. Evaluation model indicators included the root mean square error of cross-validation (RMSECV) and determination coefficient (R) values. The TFC, XO, and AA model, combining optimal spectral preprocessing and spectral bands, had RMSECV values of 0.139, 0.117, and 0.121, with R values exceeding 0.92. The root mean square error of prediction (RMSEP) for the TFC, XO, and AA model on the prediction set was 0.301, 0.213, and 0.149, with determination coefficient (R) values of 0.915, 0.933, and 0.926. The results showed a strong correlation between NIR with TFC, XO, and AA in P. mume. Therefore, the established model was effective, suitable for the rapid quantification of TFC, XO, and AA. The prediction method is simple and rapid, and can be extended to the study of medicinal plant content and activity.

摘要

基于主要成分的含量和活性评价草药质量具有重要意义。开发一种环保的测定方法具有重要的应用潜力。在本研究中,我们提出了一种新的方法,即使用近红外光谱(NIR)同时预测梅花中总黄酮含量(TFC)、黄嘌呤氧化酶抑制(XO)活性和抗氧化活性(AA)。使用亚硝酸钠-硝酸铝-氢氧化钠比色法、尿酸比色法和 2,2-二苯基-1-苦基肼自由基(DPPH)清除自由基活性作为参考方法,我们分析了来自中国不同地区的 90 个梅花样本中的 TFC、XO 和 AA。将固体样品进行 NIR 分析。通过采用光谱预处理和优化光谱波段,我们使用偏最小二乘回归(PLS)建立了 TFC、XO 和 AA 的快速预测模型。为了提高模型性能并消除无关变量,采用竞争自适应重加权采样(CARS)计算预处理全光谱。评价模型指标包括交叉验证均方根误差(RMSECV)和决定系数(R)值。将最佳光谱预处理和光谱波段相结合的 TFC、XO 和 AA 模型的 RMSECV 值分别为 0.139、0.117 和 0.121,R 值均超过 0.92。TFC、XO 和 AA 模型在预测集上的预测均方根误差(RMSEP)分别为 0.301、0.213 和 0.149,决定系数(R)值分别为 0.915、0.933 和 0.926。结果表明,NIR 与梅花中的 TFC、XO 和 AA 之间具有很强的相关性。因此,所建立的模型是有效的,适合于 TFC、XO 和 AA 的快速定量。该预测方法简单快速,可扩展到药用植物含量和活性的研究。

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