Abstract:

【Background】 The plum is one of the most widely distributed and cultivated fruit trees globally. The Chinese plum (Prunus salicina L.), originating from China, is known for its beauty, fragrance, juiciness, and rich nutritional value. It exhibits significant genetic heterogeneity and diversity in fruit traits. In recent years, there has been an increasing demand for the sensory quality of plum fruit aroma, prompting breeders to place greater emphasis on identifying and selecting germplasm with unique aromas. Those onventional methods for detecting fruit aroma involve complex preprocessing, high testing costs, and require high technical skills for operation. Additionally, these methods lack the advantages of rapid response and high detection speed, making non-destructive testing difficult and unable to accurately simulate consumer olfactory experiences. 【Objective】 The aim of this study aimed to use electronic nose technology to evaluate the diversity of aroma composition in Chinese plum germplasm, so as to provid essential materials and data support for plum breeding research and production practices in China. 【Method】 Using electronic nose technology, ten odor sensors were employed to identify the different fruit fragrances of 94 Chinese plum germplasm resources. The samples were then grouped and evaluated based on the results of K-means clustering. 【Result】Overall, the average values of different odors showed a normal distribution, but significant differences existed between different odor channels. The W1W channel exhibited the highest odor response value, while the W1C channel had the lowest value. Additionally, variance analysis of different odor channels revealed that W1W had the highest degree of dispersion in odor response values, followed by W5S, while W1C, W3C, W5C, and W3S showed lower dispersion and relatively concentrated distribution. The aroma data of 94 Chinese plum samples were divided into six groups using K-means clustering analysis, each representing plum fruits with specific aroma characteristics. Group one included germplasm sensitive to aromatic hydrocarbons, Group two to ethanol and nitrogen oxides, Group three to hydrogen, Group four to hydrogen and aromatic hydrocarbons, Group five showed low sensitivity to aromatic hydrocarbons, and Group six to hydrogen sulfide. These groupings provided important insights for further research on the aroma components and sensory quality of Chinese plum fruits. Significant differences in maximum, minimum, and median values of different odors were observed between groups. Further correlation analysis revealed significant positive or negative relationships between some odors. Principal component analysis (PCA), linear discriminant analysis (LDA), and uniform manifold approximation and projection (UMAP) were used for dimensionality reduction and visualization of aroma data, and the results indicated that these methods could distinguish the tested plum germplasm to varying degrees and correspond to their cluster groupings, each with different advantages and disadvantages in feature extraction and data visualization. Particularly, the independent use of LDA analysis had certain limitations and shortcomings. This study screened a batch of plum resources with prominent aroma characteristics, including ‘Wuxiangli’ ‘Zaoshuli’ ‘Lishuihong’ ‘Longnanli’ and ‘Xiangjiaoli (Fuxian)’. 【Conclusion】This study utilized electronic nose technology to analyze the aroma composition and distribution of Chinese plum germplasm, revealing that the W1W, W1S, and W5S channels had higher response values, primarily sensitive to volatile compounds such as hydrogen sulfide, methane, and nitrogen oxides. Six Chinese plum groups had different distinct aroma characteristics. In several response values, the mean difference between cluster 6 and the other five groups was significant, indicating that cluster 6 had unique characteristics in these response values.

Key words: Chinese plum, germplasm resource, electronic nose, aroma analysis, K-means clustering