Sachadyn-Król Monika, Budziak-Wieczorek Iwona, Jackowska Izabella
Department of Chemistry, Faculty of Food Sciences and Biotechnology, University of Life Sciences in Lublin, Akademicka 15, 20-950 Lublin, Poland.
Antioxidants (Basel). 2023 Sep 5;12(9):1719. doi: 10.3390/antiox12091719.
Strawberry cultivars Portola and Enduro, as well as raspberry cultivars Enrosadira and Kwazi, were evaluated for their antioxidant potential after treatment with gaseous ozone and different refrigeration storage conditions. Their antioxidant capacity was investigated with ABTS and DPPH methods, and the chemical composition was determined by measuring the total phenolic (TPC) and flavonoid (TFC) compounds. The classification of different samples of berry puree was influenced significantly by both the cultivars and the refrigeration storage method. Moreover, FTIR spectroscopy coupled with chemometrics was used as an alternative technique to conventional methods to determine the chemical composition of strawberries and raspberries. The chemometric discrimination of samples was achieved using principal component analysis (PCA), hierarchical clustering analysis (HCA) and linear discriminant analysis (LDA) modelling procedures performed on the FTIR preprocessed spectral data for the fingerprint region (1800-500 cm). The fingerprint range between 1500 and 500 cm, corresponding to deformation vibrations from polysaccharides, pectin and organic acid content, had a significant impact on the grouping of samples. The results obtained by PCA-LDA scores revealed a clear separation between four classes of samples and demonstrated a high overall classification rate of 97.5% in differentiating between the raspberry and strawberry cultivars.
对草莓品种Portola和Enduro以及树莓品种Enrosadira和Kwazi在气态臭氧处理和不同冷藏储存条件下的抗氧化潜力进行了评估。采用ABTS和DPPH方法研究了它们的抗氧化能力，并通过测量总酚（TPC）和类黄酮（TFC）化合物来确定其化学成分。浆果泥不同样品的分类受到品种和冷藏储存方法的显著影响。此外，傅里叶变换红外光谱（FTIR）结合化学计量学被用作传统方法的替代技术，以确定草莓和树莓的化学成分。使用主成分分析（PCA）、层次聚类分析（HCA）和线性判别分析（LDA）建模程序对FTIR预处理后的指纹区域（1800 - 500 cm）光谱数据进行分析，实现了样品的化学计量学判别。1500至500 cm之间的指纹范围对应于多糖、果胶和有机酸含量的变形振动，对样品分组有显著影响。PCA - LDA得分获得的结果显示四类样品之间有明显分离，并且在区分树莓和草莓品种时总体分类率高达97.5%。
