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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #378439

Research Project: Assessment and Improvement of Soil Health under Modern Cropping Systems in the Mid-Southern United States

Location: Crop Production Systems Research

Title: Shifts in bacterial community in response to conservation management practices within a soybean production system

Author
item Tyler, Heather

Submitted to: Biology and Fertility of Soils
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/4/2021
Publication Date: 3/12/2021
Publication URL: https://handle.nal.usda.gov/10113/7335609
Citation: Tyler, H.L. 2021. Shifts in bacterial community in response to conservation management practices within a soybean production system. Biology and Fertility of Soils. https://doi.org/10.1007/s00374-021-01550-8.
DOI: https://doi.org/10.1007/s00374-021-01550-8

Interpretive Summary: Conservation management practices, such as elimination of tillage and planting winter cover crops, have been used to enhance soil quality and mitigate the environmental impacts of conventional row crop agriculture on downstream ecosystems. These practices have the potential to alter the community composition of microorganisms that carry out many important functional roles in the soil, such as nutrient cycling, plant growth promotion, and disease suppression. Scientists from the USDA-ARS Crop Productions Systems Research Unit in Stoneville, MS conducted a three-year field study examining the effects of two winter cover crops, Elbon rye and Crimson clover, in plots under long term till and no till management, on bacterial community composition in soybean field soils. Tillage significantly impacted bacterial community composition at all timepoints, while the effects of cover crop increased over the study period. Tilled soils had higher diversity, along with greater numbers of bacterial groups associated with carbon and phosphate decomposition and plant disease suppression. Cover cropped plots had higher levels of bacteria associated with nitrogen cycling soil and root nodulation in soybean. This study demonstrates how tillage and cover crop treatments each promoted the proliferation of different beneficial bacterial groups. These results will provide information to scientists determining how agricultural management practices can alter the functional potential of field soils and how these insights can be used to make better field management decisions depending on the needs of the farmer.

Technical Abstract: Conservation practices, such as no till management and winter cover crops, are employed to increase environmental sustainability in agricultural row crop production systems through decreasing nutrient and sediment losses in runoff. These practices also have the potential to alter microbial community composition in soils that carry out important functions, such as nutrient cycling, plant growth promotion, and disease suppression. A three-year field study was conducted to assess effects of two winter cover crops, Elbon rye (Secale cereal L.) and Crimson clover (Trifolium incarnatum L.), under till and no till management, on bacterial community composition in soybean (Glycine max L.) field soils using high-throughput sequencing of the 16S rRNA gene. Effects of tillage and cover crop on bacterial composition at the phylum level were minor, with most significant differences between treatments occurring at finer taxonomic levels. Tilled plots displayed higher levels of Xanthomonadaceae, while cover cropped soils had greater Bradyrhizobium abundances. Functional gene prediction indicated genes associated with decomposition of C and P compounds, as well as biocontrol agents, were elevated in tilled plots, genes associated with root growth promotion were elevated in cover crop treatments, and nitrate reductase and denitrification genes were elevated in both no till and cover crop plots. While valuable functional insights can be gained from sequence analyses, not all differences observed at the sequencing level will translate into functional differences due to variation in gene expression, and further study is needed to validate which functions can be predicted from sequencing data.