Evaluation of the Differences of Sour Jujuba Fruits from Diverse Regions Based on the Collaborative Analysis of Organic Acids and Flavor Characters
摘要
Sour jujuba (Ziziphus jujuba var. spinosa (Bunge) Hu ex H.F.Chou, Rhamnaceae) is an indigenous plant in northern China, whose fruits boast highly valuable nutrition and a distinctive flavor. Organic acids, as a vital compound, play a great role in the quality determining and unique flavor formation of sour jujuba fruits. In this study, HPLC–DAD was employed for both qualitative and quantitative analyses of organic acids in sour jujuba fruits and electronic tongue was used for flavor evaluation. Chemical pattern recognition analyses, such as principal component analysis and orthogonal partial least squares discriminant analysis, were conducted to visualize regional disparities in sour jujuba fruits. Subsequently, the correlation between the organic acid content and the flavor outcomes was analyzed, revealing significant distinctions among sour jujuba fruits samples from diverse regions. Based on the analysis of organic acid content and geographical distribution, the five regions of sour jujuba were categorized into two different groups with 113° longitude as the boundary, including group A (Shanxi, Shaanxi, and Henan Provinces) and group B (Hebei Province and Tianjin city). Three organic acids (malic acid, citric acid, and fumaric acid) and five flavors (saltiness, richness, aftertaste-A, astringency, and aftertaste-B) were identified as crucial indicators for distinguishing different regions of sour jujuba fruits. The organic acid content and some flavor of sour jujuba fruits samples in group A were significantly higher than those in group B. Pearson’s correlation analysis illustrated the correlation between organic acids and flavors, suggesting that the three organic acids might serve as foundational elements for four flavor profiles in sour jujuba fruits. In conclusion, this study provided a scientific reference for the development and utilization of sour jujuba.
Graphical Abstract