Yang Leng

Mr. Yang Leng


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

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

Representative Publications

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11 January 2023 in Agronomy
Verified
Journal Article
Open access
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SWSirou Wei
Sirou Wei
BLBoheng Liu
Boheng Liu
Kang NiKang Ni
Kang Ni
LMLifeng Ma
Lifeng Ma
Yuanzhi ShiYuanzhi Shi
Yuanzhi Shi
Jianyun RuanJianyun Ruan
Jianyun Ruan
Rhizosphere microbes play pivotal roles in regulating the soil ecosystem by influencing and directly participating in the nutrient cycle. Evidence shows that the rhizosphere microbes are highly dependent on plant genotype and cultivars; however, their characteristics in soils with different tea (Camellia sinensis L.) cultivars are poorly understood. Therefore, the present study investigated the rhizosphere soil properties, microbial community composition, and their potential functions under four tea cultivars Huangjinya (HJY), Tieguanyin (TGY), Zhongcha No.108 (ZC108), and Zijuan (ZJ). The study found a minor impact of cultivars on rhizosphere soil properties but a significant influence on microbial community structure. Except for available potassium (AK) (HJY > TGY > ZC108 > ZJ), tea cultivars had no significant impact on other soil properties. The tea cultivars resulted in substantial differences only in the diversity of soil bacteria of lower taxonomic levels (family to species), as well as significantly changed communities’ structure of bacteria and fungi (R2 = 0.184, p = 0.013 and R2 = 0.226, p = 0.001). Specifically, Proteobacteria, Actinobacteria, Chloroflexi, Acidobacteriota, and Firmicutes accounted for approximately 96% of the bacterial phyla in the tea soils, while Ascomycota, Mortierellomycota, Rozellomycota, Basidiomycota, and Monoblepharomycota (90% of the total) predominated the soil fungal community. Redundancy analysis (RDA) identified soil pH (14.53%) and ammonium-nitrogen (NH4+-N; 16.74%) as the key factors for the changes in bacterial and fungal communities, respectively. Finally, FAPROTAX analysis predicted significant differences in the carbon, nitrogen, and sulfur (C-N-S)-cycling among the soils with different tea cultivars, specifically, ZJ cultivar showed the highest C-cycling but the lowest N- and S-cycling, while FUNGuild analysis revealed that the pathotroph group was significantly lower in ZC108 than the other cultivars. These findings improve our understanding of the differences in microbial community characteristics among tea cultivars and provide a basis for precisely selecting and introducing excellent tea varieties in the agriculture practices.

31 December 2025 in Horticulturae
Verified
Journal Article
Open access
PDF file
JMJuan Mao
Juan Mao
HHHuang Huang
Huang Huang
KWKejian Wang
Kejian Wang
HPHong Peng
Hong Peng
XYXinhua Yao
Xinhua Yao
YLYang Leng
Yang Leng
From the 1950s to the 1970s, approximately 80,000 kg of tea seeds were introduced from mainland China to the Xizang Autonomous Region for experimental cultivation. To assess the genetic diversity patterns of these tea accessions following more than half a century of acclimatization to plateau environments, we analyzed genetic variation, population structure, and genetic distinctiveness among fifty tea germplasm using nine phenotypic traits and 30 SSR markers. Phenotypic analysis revealed a moderately high level of genetic diversity, as indicated by the mean Shannon diversity index (H′ = 1.29). Principal component analysis (PCA) indicated that phenotypic variation was not geographically structured across the collection sites. The SSR markers exhibited a high degree of polymorphism, with an average polymorphic information content (PIC) of 0.610 and a genetic diversity index (I) of 1.437, indicating substantial genetic variation. Analysis of molecular variance (AMOVA) revealed that genetic differentiation occurred predominantly within populations, accounting for 91.49% of the total genetic variation. Similarly, 97.86% of the variation was attributed to differences within elevational gradients. Discriminant analysis of principal components (DAPC) and Bayesian population structure modeling (STRUCTURE) both identified two genetic clusters among the studied genotypes. Our results have practical implications for tea breeding programs by providing guidance for parental selection, informing germplasm collection management, and supporting the conservation of genetic resources.