鑫 郑

Mr. 鑫 郑


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 September 2025 in Genes
Verified
Journal Article
Open access
PDF file
SGSuying Guo
Suying Guo
鑫郑鑫 郑
鑫 郑
SWShuaiyi Wang
Shuaiyi Wang
YAYuran Ai
Yuran Ai
RZRengui Zhao
Rengui Zhao
JLJin-Hao Lan
Jin-Hao Lan
Background: This study aims to systematically evaluate the genetic divergence among 200 fresh maize inbred lines using both phenotypic and molecular markers, and to compare the efficacy of these two approaches for genetic classification. Methods: Phenotypic clustering analysis was conducted based on eight key agronomic traits, including plant height and ear length. Additionally, molecular analysis was performed using 40 Simple Sequence Repeat (SSR) primer pairs, resulting in the generation of 230 polymorphic alleles. The polymorphism information content (PIC) was calculated to evaluate the discriminatory power of the markers. Results: Phenotypic analysis categorized the inbred lines into four groups, comprising 25, 38, 97, and 40 lines, respectively, with benchmark lines distributed across Groups I and III. SSR analysis revealed a high level of genetic diversity, with an average of 5.75 alleles per locus and a mean polymorphic information content (PIC) of 0.70. Molecular grouping further divided the population into four distinct clusters, representing 26.5%, 51.0%, 14.0%, and 8.5% of the total, which exhibited different distribution patterns compared to the phenotypic grouping. The distribution of benchmark lines across various molecular groups confirmed their genetic divergence. Conclusions: SSR-based clustering demonstrated superior robustness and reliability compared to phenotypic grouping for genetic discrimination. These findings confirm the substantial genetic diversity present in fresh maize inbred lines and support the preferential use of SSR markers in maize breeding programs for precise genetic characterization.