The adaptability of Phytophthora sojae to different types of soil determines the distribution of Phytophthora root rot of soybean in Heilongjiang Province of China

Liu, Haixu; Yu, Hansong; Zhang, Zhuoqun; Bi, Xiangqi; Yang, Zhangping; Chen, Yufei; Gu, Xiaobo; Wen, Jingzhi

doi:10.1007/s10658-021-02387-5

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…And in the 30-60 cm soil layer, Genu Microvirga (CK, 2.95%), Genu Domibacillus (P1, 3.50%), Genu norank_f__norank_o__norank_c__KD4-96 (P2, 3.07%), and Genu Brucella (P3, 4.05%) were most abundant. This difference may be caused by the gradient difference in nutrient content of the mixed soil (Table 1 and S1 Table ) or the adaptability of the mixed soil to the new environment is different [29,30].…”

Section: Plos Onementioning

confidence: 99%

Distribution of soil microorganisms in different complex soil layers in Mu Us sandy land

Guo

Zhang

et al. 2023

PLoS ONE

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The soft rock in Mu Us Sandy Land has rich resources and high content of clay minerals. The combination of soft rock with sand can play a certain role in sand fixation and promote the green development of ecological environment. In this paper, the aeolian sandy soil in Mu Us Sandy was taken as the research object, and it was mixed with soft rock to form composite soil. The four volume ratios of soft rock to sand were respectively 0:1, 1:5, 1:2 and 1:1. And CK, P1, P2 and P3 were used to represent the above four volume ratios in turn. By means of quantitative fluorescent PCR and high throughput sequencing, 16S rRNA gene abundance and community structure were investigated. The results showed that the soil organic carbon (SOC) and total nitrogen (TN) contents in 0-30cm soil layer were higher. Compared with CK, the SOC of P2 was improved by 112.77% and that of P1 was 88.67%. The content of available phosphorus (AP) and available potassium (AK) was higher in 30-60cm soil layer, and P3 was more effective. The abundance of 16S rRNA gene in the mixed soil bacteria ranged from 0.03×109 to 0.21×109 copies g-1 dry soil, which was consistent with the changes of nutrients. Under different soil layers, the three dominant bacteria in the mixed soil were the same, namely Phylum Actinobacteriota, Phylum Proteobacteria and Phylum Chloroflexi, and there were more unique genera in each soil layer. Both bacteria ɑ and β diversity showed that the community structure of P1 and P3 in 0-30cm soil layers was similar, and that of P1 and P2 in 30-60cm soil layers was similar. AK, SOC, AN (ammonium nitrogen), TN and NN (nitrate nitrogen) were the main factors contributing to the differentiation of microbial community structure under different compound ratios and soil layers, and Phylum Actinobacteria has the largest correlation with nutrients. The results showed that the soft rock could improve the quality of sandy soil, and that the growth of microbial growth was dependent on the soil physicochemical characteristics. The results of this study will be helpful to the study of the microscopical theory for the control of the wind-blown sand and the ecology of the desert.

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Section: Plos Onementioning

confidence: 99%

Distribution of soil microorganisms in different complex soil layers in Mu Us sandy land

Guo

Zhang

et al. 2023

PLoS ONE

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Comparative metabolomics reveal the participation of soybean unique rhizosphere metabolites in susceptibility and resistance of host soybean to Phytophthora sojae

Zhang

et al. 2022

Plant Soil

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The adaptability of Phytophthora sojae to different types of soil determines the distribution of Phytophthora root rot of soybean in Heilongjiang Province of China

Cited by 2 publications

References 18 publications

Distribution of soil microorganisms in different complex soil layers in Mu Us sandy land

Distribution of soil microorganisms in different complex soil layers in Mu Us sandy land

Comparative metabolomics reveal the participation of soybean unique rhizosphere metabolites in susceptibility and resistance of host soybean to Phytophthora sojae

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