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利用衰减全反射傅里叶变换红外光谱法测定穗状醋栗(蓝靛果忍冬)的抗氧化能力和酚类含量。

Determination of antioxidant capacity and phenolic content of haskap berries (Lonicera caerulea L.) by attenuated total reflectance-Fourier transformed-infrared spectroscopy.

机构信息

Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada.

Pi'ara Functional Foods Inc., #800, 517-10 Ave. S. W., Calgary, AB T2R 0A8, Canada.

出版信息

Food Chem. 2025 Jan 15;463(Pt 2):141283. doi: 10.1016/j.foodchem.2024.141283. Epub 2024 Sep 13.

DOI:10.1016/j.foodchem.2024.141283
PMID:39293384
Abstract

The total phenolic content (TPC) and antioxidant capacity (TAC) of haskap berries cultivated in various locations across Alberta were analyzed using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The Folin-Ciocalteu assay was used to determine TPC, while TAC was quantified by 2,2-diphenyl-1-picrylhydrazl radicals (DPPH) assay and oxygen radical absorbance capacity (ORAC) assay. Three tenfold cross-validated partial least-squares regression (PLSR) models and three fivefold cross-validated deep learning models were developed separately based on FT-IR spectra collected from 22 haskap berry samples and their corresponding reference values determined through Folin-Ciocalteu, DPPH, and ORAC assays. The deep learning models (R = 0.95, 0.93, and 0.90 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively) demonstrated better prediction capability compared to the PLSR models (R = 0.74, 0.72, and 0.66 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively). In addition, PLS loading plots indicated that phenolic contents and polysaccharides in haskap berries could contribute to their antioxidant capacity. Using ATR-FTIR to estimate the TPC and TAC of fruits offers a rapid alternative to the conventional chemical assays.

摘要

采用衰减全反射傅里叶变换红外光谱(ATR-FTIR)分析了阿尔伯塔省不同地区种植的穗状醋栗的总酚含量(TPC)和抗氧化能力(TAC)。福林-希卡尔法用于测定 TPC,而 2,2-二苯基-1-苦肼基自由基(DPPH)法和氧自由基吸收能力(ORAC)法用于定量 TAC。分别基于从 22 个穗状醋栗样本采集的 FT-IR 光谱和通过福林-希卡尔法、DPPH 和 ORAC 测定的相应参考值,开发了三个十重交叉验证偏最小二乘回归(PLSR)模型和三个五重交叉验证深度学习模型。与 PLSR 模型(福林-希卡尔法、DPPH 和 ORAC 测定的 R 值分别为 0.74、0.72 和 0.66)相比,深度学习模型(福林-希卡尔法、DPPH 和 ORAC 测定的 R 值分别为 0.95、0.93 和 0.90)表现出更好的预测能力。此外,PLS 加载图表明穗状醋栗中的酚类含量和多糖可能有助于其抗氧化能力。使用 ATR-FTIR 来估计水果的 TPC 和 TAC 提供了一种快速替代传统化学分析的方法。

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