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使用近红外光谱和化学计量学快速测量抗氧化性能。 需注意,原文“Rapid Measurement of Antioxidant Properties of Using Near-Infrared Spectroscopy and Chemometrics.”表述不太完整,“of”后面缺少具体内容。

Rapid Measurement of Antioxidant Properties of Using Near-Infrared Spectroscopy and Chemometrics.

作者信息

Cao Xiaoqing, Huang Jing, Chen Jinjing, Niu Ying, Wei Sisi, Tong Haibin, Wu Mingjiang, Yang Yue

机构信息

Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental Science, Wenzhou University, Wenzhou 325035, China.

出版信息

Foods. 2024 Jun 5;13(11):1769. doi: 10.3390/foods13111769.

Abstract

(), often used as a dual-use plant with herbal medicine and food applications, has attracted considerable attention for health-benefiting components and wide economic value. The antioxidant ability of is of great significance to ensure its health care value and safeguard consumers' interests. However, the common analytical methods for evaluating the antioxidant ability of are time-consuming, laborious, and costly. In this study, near-infrared (NIR) spectroscopy and chemometrics were employed to establish a rapid and accurate method for the determination of 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) scavenging capacity, 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging capacity, and ferric reducing antioxidant power (FRAP) in . The quantitative models were developed based on the partial least squares (PLS) algorithm. Two wavelength selection methods, namely the genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) method, were used for model optimization. The CARS-PLS models exhibited superior predictive performance compared to other PLS models. The root mean square errors of cross-validation () for ABTS, FRAP, and DPPH were 0.44%, 2.64 μmol/L, and 2.06%, respectively. The results demonstrated the potential application of NIR spectroscopy combined with the CARS-PLS model for the rapid prediction of antioxidant activity in . This method can serve as an alternative to conventional analytical methods for efficiently quantifying the antioxidant properties in .

摘要

()常作为一种具有草药和食品应用的两用植物,因其有益健康的成分和广泛的经济价值而备受关注。()的抗氧化能力对于确保其保健价值和维护消费者利益具有重要意义。然而,评估()抗氧化能力的常用分析方法耗时、费力且成本高昂。在本研究中,采用近红外(NIR)光谱和化学计量学方法建立了一种快速准确测定()中2,2'-联氮双(3-乙基苯并噻唑啉-6-磺酸)(ABTS)清除能力、2,2-二苯基-1-苦基肼(DPPH)清除能力和铁还原抗氧化能力(FRAP)的方法。基于偏最小二乘法(PLS)算法建立了定量模型。采用遗传算法(GA)和竞争性自适应重加权采样(CARS)方法这两种波长选择方法对模型进行优化。与其他PLS模型相比,CARS-PLS模型表现出卓越的预测性能。ABTS、FRAP和DPPH的交叉验证均方根误差()分别为0.44%、2.64 μmol/L和2.06%。结果表明,近红外光谱结合CARS-PLS模型在快速预测()抗氧化活性方面具有潜在应用价值。该方法可作为传统分析方法的替代方法,用于高效定量()中的抗氧化性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3274/11171845/057e0e2d80bf/foods-13-01769-g001.jpg

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