School of Food and Biological Engineering Jiangsu University, Xuefu Road 301, Zhenjiang 213013, China.
School of Food and Biological Engineering Jiangsu University, Xuefu Road 301, Zhenjiang 213013, China; College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China.
Food Chem. 2021 Oct 15;359:129928. doi: 10.1016/j.foodchem.2021.129928. Epub 2021 Apr 22.
Benchtop near-infrared (NIR) spectroscopy coupled with multivariate analysis was used for the classification and prediction of antioxidant properties of walnut. Total phenolic content (TPC), total flavonoid content (TFC), ABTS assay and FRAP assay were performed spectrophotometrically. The synergy interval partial least square coupled competitive adaptive reweighted sampling (Si-CARS-PLS) was used for the prediction. A decent discrimination using principal component analysis (PCA) was observed by mean of spectroscopic and antioxidant properties data with total cumulative variance of 99.26% (PC1 = 95.07%, PC2 = 2.98%, PC3 = 1.21%) and 96.60% (PC1 = 64.28%, PC2 = 32.32%) respectively. The Si-CARS-PLS yielded optimal performance, R = 0.9616, RPD = 3.807 for TPC, R = 0.9657, RPD = 3.367 for TFC, R = 0.9683, RPD = 2.728 for ABTS assay, and R = 0.914, RPD = 2.669 for FRAP assay. These findings revealed that NIR integrated with Si-CARS-PLS could be used for the prediction of antioxidant properties of walnut.
台式近红外（NIR）光谱结合多元分析用于核桃抗氧化性能的分类和预测。总酚含量（TPC）、总黄酮含量（TFC）、ABTS 法和 FRAP 法均采用分光光度法进行测定。采用协同区间偏最小二乘耦合竞争自适应重加权采样（Si-CARS-PLS）进行预测。通过光谱和抗氧化性能数据的主成分分析（PCA）观察到良好的区分，总累积方差为 99.26%（PC1=95.07%，PC2=2.98%，PC3=1.21%）和 96.60%（PC1=64.28%，PC2=32.32%）。Si-CARS-PLS 表现出最佳性能，TPC 的 R=0.9616，RPD=3.807，TFC 的 R=0.9657，RPD=3.367，ABTS 测定的 R=0.9683，RPD=2.728，FRAP 测定的 R=0.914，RPD=2.669。这些结果表明，NIR 与 Si-CARS-PLS 结合可用于预测核桃的抗氧化性能。
