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Bacterial biomarkers are linked more closely to wheat yield formation than overall bacteria in fertilized soil

Bibliographic Data

ID21649136
AuthorsLi Ma (0000-0002-8688-5588, The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of Education Yangling PR China), Wenquan Niu (0000-0003-1715-3372, The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of Education Yangling PR China), Guochun Li (0000-0002-1680-130X, The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of Education Yangling PR China), Erxin Zhang (College of Water Resources and Architectural Engineering Northwest A&F University Yangling PR China), Jun Sun (0000-0002-3545-1392, College of Water Resources and Architectural Engineering Northwest A&F University Yangling PR China), Qian Zhang (0009-0004-3866-2007, College of Water Resources and Architectural Engineering Northwest A&F University Yangling PR China), Kadambot H M Siddique (0000-0001-6097-4235, The UWA Institute of Agriculture The University of Western Australia Crawley Western Australia Australia)
Year2023
Volume34
Issue5
Pages1323-1336
Publication date2023-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.4535
OpenAlexW4309048684
LanguageEN
Citations received3
References cited81

Soil bacteria play pivotal roles in agroecosystem functioning. However, the immense diversity of soil bacterial communities masks the effects of some species, such as bacterial biomarkers, on soil nutrient cycling and crop growth. We analyzed biological and chemical soil parameters of five fertilization treatments (CK, LN, CN, HN, LNM: 0, 150, 200, 250 kg N hm −2 , 150 kg N hm −2 + 15,000 kg hm −2 sheep manure). The random forest models were used to select bacterial biomarkers and assess the contributions of bacterial biomarkers and overall bacteria to wheat yield. Moreover, we used a partial least squares path modelling to explore the relationship between fertilization, bacterial biomarkers, carbon (C) and nitrogen (N) cycling functions, soil nutrients, and wheat yield. The results showed that bacterial biomarkers are better predictors of wheat yield than overall bacteria, explaining 52.54% and 16.00% of the variation in yield, respectively. Bacterial biomarkers affected wheat production by increasing soil organic carbon, and available nitrogen content. The LNM treatment significantly improved the relative abundance of beneficial biomarkers, such as Sphingomonadales, Xanthomonadaceae, Lysobacter, and Streptomyces, compared to the LN treatment. In addition, the LNM treatment promoted chitinlysis, cellulolysis, xylanolysis, aromatic hydrocarbon degradation, and aerobic ammonia oxidation, relative to the other inorganic N treatments (LN, CN, and HN). Our results emphasize the role of bacterial biomarkers in wheat yield formation, providing new insights into maintaining agricultural productivity by taking advantage of soil bacterial biomarkers

Agriculture · Agroecosystem · Agronomy · Bacteria · Bacterial growth · Biology · Manure · Nutrient · Soil carbon · Soil microbiology · Soil water · Chemistry · Gut microbiota and health · Microbial Community Ecology and Physiology · Soil Carbon and Nitrogen Dynamics · Ecology · Environmental Chemistry

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  • An Ordination of the Upland Forest Communities of Southern Wisconsin

    Open Access•J Roger Bray, J T Curtis•Ecological Monographs•1957

  • A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding

    Open Access•Marion M Bradford, Richard W McEnally et al.•Analytical Biochemistry•1976

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Unique citing works3
Citations per year1
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

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