Higher-Quality Pumpkin Cultivars Need to Recruit More Abundant Soil Microbes in Rhizospheres
文献类型: 外文期刊
第一作者: Sun, Yan
作者: Sun, Yan;Huang, Ziyue;Chen, Siyu;Yang, Da;Lin, Xinru;Yang, Shangdong;Liu, Wenjun
作者机构:
关键词: pumpkin (Cucurbita moschata Duchesne); quality; rhizosphere; microbial compositions
期刊名称:MICROORGANISMS ( 影响因子:4.926; 五年影响因子:5.143 )
ISSN:
年卷期: 2022 年 10 卷 11 期
页码:
收录情况: SCI
摘要: Two different qualities of pumpkin, cultivars G1519 and G1511, were grown in the same environment under identical management. However, their qualities, such as the contents of total soluble solids, starch, protein, and vitamin C, were significantly different. Do rhizospheric microbes contribute to pumpkin quality? To answer this question, this study investigated the soil microbial compositions in the rhizospheres of different quality pumpkin cultivars to determine the differences in these soil microbial compositions and thus determine how soil microbes may affect pumpkin quality. Firstly, a randomized complete block design with two pumpkin cultivars and three replications was performed in this study. The soil microbial compositions and structures in the rhizospheres of the two pumpkin cultivars were analyzed using a high-throughput sequencing technique. In comparison with the low-quality pumpkin cultivar (G1519), higher microbial diversity and richness could be found in the rhizospheres of the high-quality pumpkin cultivar (G1511). The results showed that there were significant differences in the soil bacterial and fungal community compositions in the rhizospheres of the high- and low-quality pumpkin cultivars. Although the compositions and proportions of microorganisms were similar in the rhizospheres of the two pumpkin cultivars, the proportions of Basidiomycota and Micropsalliota in the G1519 rhizosphere were much higher than those in the G1511 rhizosphere. Furthermore, the fungal phylum and genus Rozellomycota and Unclassified_p__Rozellomycota were unique in the rhizosphere of the high-quality pumpkin cultivar (G1511). All the above results indicate that soil microbes were enriched differentially in the rhizospheres of the low- and high-quality pumpkin cultivars. In other words, more abundant soil microbes were recruited in the rhizosphere of the high-quality pumpkin cultivar as compared to that of the low-quality cultivar. Rozellomycota and Unclassified_p__Rozellomycota may be functional microorganisms relating to pumpkin quality.
分类号:
- 相关文献
作者其他论文 更多>>
-
Effects of Different Light Spectra on Oxidative Stress and Nutritional Quality of the Fish Plectropomus leopardus
作者:Li, Wensheng;Zhang, Zheng;Liu, Baoliang;Fang, Yingying;Cao, Shuquan;Li, Wenyang;Fei, Fan;Li, Wensheng;Liu, Baoliang;Sun, Yan;He, Chengbin;Zhang, Chuanxin
关键词:light spectra; blood biochemistry; antioxidant stress; nutritional quality; Plectropomus leopardus; light spectra; blood biochemistry; antioxidant stress; nutritional quality; Plectropomus leopardus
-
Genome-Wide Identification and Expression Analysis Under Abiotic Stress of the Lipoxygenase Gene Family in Maize (Zea mays)
作者:Li, Sinan;Hou, Shuai;Sun, Yuanqing;Sun, Minghao;Sun, Yan;Li, Xin;Li, Yunlong;Wang, Luyao;Cai, Quan;Guo, Baitao;Zhang, Jianguo
关键词:maize; LOX; abiotic stress; gene family; expression analysis
-
Can the Endophytic Microbial Compositions in Tomato Roots be Reshaped by Application with Wood Vinegar Under Continuous Cropping System
作者:Xiao, Jian;Feng, Junqian;Yang, Shangdong;Ou, Hui-Ping;Yang, Shangdong;Xiao, Jian;Lin, Qiang
关键词:Wood vinegar; Tomato; Continuous cropping; Endophytic microbial composition; High-throughput sequencing
-
Integrated microbiome and metabolome approaches reveal the resistant mechanisms of leaf blight resistant plum cultivar
作者:Zhou, Xinyan;Wei, Yufei;Zhu, Yu;Li, Jiaoming;Yang, Shangdong;Zhou, Runche;Xiao, Qingju;Luo, Ruihong
关键词:Plum (
Prunus L.); Leaf blight; Endophytic microbes; Metabolites -
How the impact and mechanisms of digital financial inclusion on agricultural carbon emission intensity: new evidence from a double machine learning model
作者:Zheng, Fengtian;Chen, Siyu;Wang, Xizhao
关键词:digital financial inclusion; double machine learning (DML); carbon emission intensity (CEI); impact mechanisms; green transformation
-
EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research
作者:Bai, Defeng;Xun, Jiani;Ma, Chuang;Luo, Hao;Yang, Haifei;Hou, Huiyu;Lv, Hujie;Wan, Xiulin;Wang, Yao;Yousuf, Salsabeel;Zeng, Meiyin;Zhang, Tianyuan;Gao, Yunyun;Liu, Yong-Xin;Chen, Tong;Ma, Chuang;Yang, Haifei;Cao, Chen;Cao, Xiaofeng;Cui, Jianzhou;Deng, Yuan-Ping;Deng, Zhaochao;Yu, Hao;Zhang, Chunfang;Dong, Wenxin;Dong, Wenxue;Du, Juan;Fang, Qunkai;Fang, Wei;Fang, Yue;Luan, Yaning;Fu, Fangtian;Fu, Min;Fu, Yi-Tian;Gao, He;Ge, Jingping;Guo, Yuhao;Gong, Qinglong;Lou, Wenbo;Gu, Lunda;Yang, Li;Guo, Peng;Hai, Tang;Liu, Hao;He, Jieqiang;He, Zi-Yang;Huang, Can;Ji, Shuai;Jiang, ChangHai;Jiang, Gui-Lai;Jiang, Lingjuan;Jin, Ling N.;Li, Changchao;Kan, Yuhe;Kang, Da;Kou, Jin;Lam, Ka-Lung;Li, Chong;Li, Fuyi;Li, Liwei;Li, Miao;Li, Xin;Li, Ye;Li, Zheng-Tao;Zhu, Chengshuai;Liang, Jing;Mo, Jiayuan;Lin, Yongxin;Liu, Changzhen;Liu, Danni;Zhang, Jing;Chen, Shifu;Liu, Fengqin;Liu, Jia;Liu, Tianrui;Liu, Tingting;Wang, Xinlong;Liu, Xinyuan;Luo, Yuanyuan;Liu, Yaqun;Liu, Bangyan;Liu, Minghao;Lv, Hujie;Ma, Tengfei;Mai, Zongjiong;Niu, Dongze;Pan, Zhuo;Qi, Heyuan;Shi, Zhanyao;Song, Chunjiao;Sun, Fuxiang;Sun, Yan;Tian, Sihui;Wang, Guoliang;Wang, Hongyang;Wang, Hongyu;Wang, Huanhuan;Wang, Jing;Wang, Jun;Wang, Kang;Wang, Leli;Yao, Xiaofang;Wang, Shao-kun;Xiao, Zufei;Xing, Huichun;Xu, Yifan;Yang, Song;Yan, Shu-yan;Zhang, Yi-Bo;Yang, Yuanming;Lei, Yu;Yuan, Zhengrong;Zhang, Chunge;Zhang, Huimin;Zhang, Na;Zhang, Yupeng;Zhang, Zheng;Zhou, Mingda;Zhou, Yuanping;Zhu, Zhihao;Zhu, Lin;Zhu, Yue;Zou, Hongqin;Zuo, Anna;Dong, Wenxuan;Wen, Tao;Chen, Shifu;Chen, Shifu;Li, Guoliang
关键词:metagenome; microbiome; microbiota; pipeline; visualization
-
Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation
作者:Sun, Yan;Yan, Fang;Sun, Yan;Wu, Jiajing;Shen, Beilei;Luo, Rongbo;Zhang, Shijun;Li, He;Qian, Bingshuo;Fan, Lingjun;Zhang, Junkui;Wang, Tiecheng;Xia, Xianzhu;Gao, Yuwei;Yang, Hengzheng;Cui, Huizi;Han, Weiwei;Xia, Xianzhu
关键词:TRPV4; anti-influenza; machine learning; repurposing drugs; molecular docking