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The Central Mississippi River Basin (CMRB) Common Experiment, with its marginal soils and southern Corn Belt climate, is an ideal location for evaluating progress toward environmental, productivity, and climatic adaptation goals. Sustainable production with conventional row-crop systems is more challenging than in the upper Corn Belt, making evaluation and adoption of alternative farming practices crucial. This Common Experiment has a hydrologically restrictive layer causing reduced plant available water capacity in the root zone. The CMRB site joined the Long-Term Agroecosystem Research network in 2011 with the Cropland Common Experiment established in 2015. The Common Experiment contrasts prevailing and alternative practices at plot and field scale. Improvement of the soil ecosystem is key, as it underpins other objectives, including reduced nutrient losses, increased soil water holding capacity, and yield stability., (© 2024 The Author(s). Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Quantitative next-generation sequencing techniques have been critical in gaining a better understanding of microbial ecosystems. In soils, denitrifying microorganisms are responsible for dinitrogen (N 2 ) production. The nosZ gene codes for nitrous oxide reductase, the enzyme facilitating the reduction of nitrous oxide (N 2 O) to N 2 . The objectives of this research were to: 1) understand how soil depth influences RNA concentration and nosZ gene abundance; 2) assess the spatial dependence of nosZ gene abundance in two claypan soil fields; and 3) compare and evaluate multiple RNA-based sequencing methods for quantifying nosZ gene abundance in soils in relation to dinitrogen (N 2 ) production. Research sites consisted of two intensively studied claypan soil fields in Central Missouri, USA. Soil cores were collected from two landscape transects across both fields and analyzed for extractable soil RNA at two depths (0-15 cm and 15-30 cm). Measurements of nosZ gene abundance were obtained using real-time quantitative polymerase chain reaction (RT-qPCR), droplet digital polymerase chain reaction (ddPCR), and nanostring sequencing (NS). In both fields, soil RNA concentrations were significantly greater at 0-15 cm depth compared to 15-30 cm. These data indicated low overall soil microbial activity below 15 cm. Due to low quantities of extractable soil RNA in the subsoil, nosZ gene abundance was only determined in the 0-15 cm depth. Sequencing method comparisons of average nosZ gene abundance showed that NS results were constrained to a narrow range and were 10-20-fold lower than ddPCR and RT-qPCR at each landscape position within each field. Droplet digital PCR appears to be the most promising method, as it reflected changes in N 2 production across landscape position., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

Optical diffuse reflectance spectroscopy (DRS) has been used for estimating soil physical and chemical properties in the laboratory. In-situ DRS measurements offer the potential for rapid, reliable, non-destructive, and low cost measurement of soil properties in the field. In this study, conducted on two central Missouri fields in 2016, a commercial soil profile instrument, the Veris P4000, acquired visible and near-infrared (VNIR) spectra (343⁻2222 nm), apparent electrical conductivity (EC a ), cone index (CI) penetrometer readings, and depth data, simultaneously to a 1 m depth using a vertical probe. Simultaneously, soil core samples were obtained and soil properties were measured in the laboratory. Soil properties were estimated using VNIR spectra alone and in combination with depth, EC a , and CI (DECS). Estimated soil properties included soil organic carbon (SOC), total nitrogen (TN), moisture, soil texture (clay, silt, and sand), cation exchange capacity (CEC), calcium (Ca), magnesium (Mg), potassium (K), and pH. Multiple preprocessing techniques and calibration methods were applied to the spectral data and evaluated. Calibration methods included partial least squares regression (PLSR), neural networks, regression trees, and random forests. For most soil properties, the best model performance was obtained with the combination of preprocessing with a Gaussian smoothing filter and analysis by PLSR. In addition, DECS improved estimation of silt, sand, CEC, Ca, and Mg over VNIR spectra alone; however, the improvement was more than 5% only for Ca. Finally, differences in estimation accuracy were observed between the two fields despite them having similar soils, with one field demonstrating better results for all soil properties except silt. Overall, this study demonstrates the potential for in-situ estimation of profile soil properties using a multi-sensor approach, and provides suggestions regarding the best combination of sensors, preprocessing, and modeling techniques for in-situ estimation of profile soil properties.

Veterinary antibiotics (VAs) in manure applied to agricultural lands may change agrichemical degradation by altering soil microbial community structure or function. The objectives of this study were to investigate the influence of two VAs, sulfamethazine (SMZ) and oxytetracycline (OTC), on atrazine (ATZ) degradation, soil microbial enzymatic activity, and phospholipid fatty acid (PLFA) markers. Sandy loam soil with and without 5% swine manure (w/w) was amended with 0 or 500 μg kgC radiolabeled ATZ and with 0, 100, or 1000 μg kg SMZ or OTC and incubated at 25°C in the dark for 96 d. The half-life of ATZ was not significantly affected by VA treatment in the presence or absence of manure; however, the VAs significantly ( < 0.05) inhibited ATZ mineralization in soil without manure (25-50% reduction). Manure amendment decreased ATZ degradation by 22%, reduced ATZ mineralization by 50%, and increased the half-life of ATZ by >10 d. The VAs had limited adverse effects on the microbial enzymes β-glucosidase and dehydrogenase in soils with and without manure. In contrast, manure application stimulated dehydrogenase activity and altered chlorinated ATZ metabolite profiles. Concentrations of PLFA markers were reduced by additions of ATZ, manure, OTC, and SMZ; adverse additive effects of combined treatments were noted for arbuscular mycorrhizal fungi and actinobacteria. In this work, the VAs did not influence persistence of the ATZ parent compound or chlorinated ATZ metabolite formation and degradation. However, reduced CO evolved from VA-treated soil suggests an inhibition to the degradation of other ATZ metabolites due to an altered soil microbial community structure., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)