Miricioiu Marius Gheorghe, Ionete Roxana Elena, Costinel Diana, Botoran Oana Romina
ICSI Analytics Group, National Research and Development Institute for Cryogenics and Isotopic Technologies-ICSI, 240050 Râmnicu Vâlcea, Romania.
Academy of Romanian Scientists, Splaiul Independentei 54, 050094 Bucharest, Romania.
Foods. 2022 Sep 14;11(18):2838. doi: 10.3390/foods11182838.
The H-NMR carbohydrates profiling was used to discriminate fruits from family in terms of botanical origin and harvest year. The classification was possible by application of multivariate data analysis, such as principal component analysis (PCA), linear discriminant analysis (LDA) and Pearson analysis. Prior, a heat map was created based on H-NMR signals which offered an overview of the content of individual carbohydrates in plum, apricot, cherry and sour cherry, highlighting the similarities. Although, the PCA results were almost satisfactory, based only on carbohydrates signals, the LDA reached 94.39% and 100% classification of fruits according to their botanical origin and growing season, respectively. Additionally, a potential association with the relevant climatic data was explored by applying the Pearson analysis. These findings are intended to create an efficient NMR-based solution capable of differentiating fruit juices based on their basic sugar profile.
利用氢核磁共振碳水化合物谱，根据植物来源和收获年份区分不同科的水果。通过应用多元数据分析，如主成分分析（PCA）、线性判别分析（LDA）和皮尔逊分析，可以实现分类。在此之前，基于氢核磁共振信号创建了一个热图，该热图概述了李子、杏子、樱桃和酸樱桃中各种碳水化合物的含量，突出了它们之间的相似性。虽然仅基于碳水化合物信号的主成分分析结果几乎令人满意，但线性判别分析根据水果的植物来源和生长季节分别达到了94.39%和100%的分类准确率。此外，通过应用皮尔逊分析探索了与相关气候数据的潜在关联。这些发现旨在创建一种基于核磁共振的有效解决方案，能够根据果汁的基本糖谱区分果汁。
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