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Composting mitigates environmental risks associated with using solid digestate as fertilizer. However, evidence is lacking on benefits of using composted digestate as fertilizer in enhancing soil health and increasing agronomic yield compared to non-composted digestate (hereafter, digestate). A field study was conducted consisting of digestate, composted digestate, co-composted digestate with biogas feedstocks (corn [Zea mays L.] silage, poultry litter, corn silage + poultry litter or food processing by-product), inorganic nitrogen fertilizer, and control (no treatment applied) on soil microbial biomass, enzyme activities (EA), soil organic carbon (SOC), bioavailable P (P), total nitrogen (TN), soil health index (SHI), and sunflower (Helianthus annuus L.) yield. The Partial Least Square Path Model (PLS-PM) was used to predict: 1) nutrient cycling in response to changes in microbial growth and EA and 2) agronomic yield in response to SHI and soil nutrients dynamics. Composted digestate had equivalent soil health benefits with most of co-composted materials and digestate, albeit agronomic yield was greatest with composted digestate, which was 40 % and 100 % greater than with inorganic nitrogen fertilizer and digestate, respectively, indicating composted digestate's potential to replace the synthetic N fertilizer. Moreover, composts from a sole digestate, rather than the ones from co-composted with fresh feedsstocks, can be promising organic amendments and fertilizers for growing sunflower. The PLS-PM model identified that triggered microbial biomass growth and EA, following digestate and composted digestate applications, catalyzed organic matter decomposition, resulting in enhanced nutrients contents and soil health. However, the model revealed that improved SHI did not predict agronomic yield, as opposed to P and TN, suggesting agronomic performance may have been more sensitive to changes in specific soil nutrients status than the overall soil health condition. We conclude that the benefits of composted digestate as fertilizer hint the significance of digestate valorization via post-digestate composting and compost utilization for sustainability of the bioenergy sector., 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., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The magnitude of bacterial transport through runoff into surface water or infiltration into groundwater is influenced by the adsorption processes in soil. The objective of this study was to evaluate fluorescent-labeled Escherichia coli (E. coli) adsorption by soil under agroforestry buffer (AB), grass buffer (GB), and row crop (RC) management. Adsorption experiments were conducted by inoculating three masses (0.5, 1, and 10 g) of each treatment (AB, GB, and RC) with E. coli O157:H7-GFP with concentration ranges of 10 5 -10 8 colony-forming units (cfu) ml -1 . Adsorption data were evaluated using Langmuir, Freundlich, and Temkin adsorption isotherm models. The Freundlich isotherm model described the observed data well for all treatments using the 10-g soil mass, with the R 2 values closer to unity in all treatments. The Freundlich K f parameter, an indicator of adsorption capacity, was higher for the AB treatment (9.93 cfu ml -1 ) compared with the GB and RC treatments (2.32 and 1.27 cfu ml -1 , respectively). The multiple pairwise comparisons test (Tukey test) of the Freundlich 1/n f parameter demonstrated a significant difference (p < .05) between the AB treatment and the RC and GB treatments. Similarly, the K f values were significantly (p = .05) higher for the 10-g mass under the same test conditions, but no significant differences were observed in the 0.5- and 1-g masses. This study demonstrated that AB has a higher E. coli adsorption capacity and the potential for mitigating the effects of E. coli O157:H7 transport to surface or groundwater through the soil ecosystem., (© 2022 The Authors. Journal of Environmental Quality © 2022 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Agroforestry practices have been acknowledged for reducing pesticide losses while maintaining land productivity. Pesticide removal from overland flow results from great infiltration capacities of the buffer soils. This can in turn threaten the quality of groundwater in case of poor pesticide sorption and degradation in the root-influenced zone. These mechanisms and their balance are likely to be influenced by plant species. However, little is known about the role of agroforestry species in the infiltration of herbicides. The aim of this study was thereby to evaluate how popular agroforestry species modulate the infiltration of water and of a widely used herbicide. We established large buffer microcosms by planting Brome grass, Black walnut, Pin oak and Poplar trees in repacked soil columns. After a growth season of 4 months, we performed ponded infiltration experiments with bromide and S-Metolachlor. We used then the HYDRUS 1D model to compare the hydrodynamic properties and S-Metolachlor transport patterns between the microcosms. In addition, we compared the sorption properties of the rhizosphere and bulk soils. We found that the tree species increased the sorption of S-Metolachlor in soil with Kd being 3 times greater than in the un-vegetated and Brome grass microcosms. Poplar trees increased the hydraulic conductivity (Ksat) compared to the control and was associated to a low retardation of S-metolachlor, which increases the risk of groundwater contamination. With slightly reduced Ksat and retardation factor in the root zone, 1.6 to 1.8 times greater than in the control treatment, Black walnut appears as an optimal species for mitigating S-Metolachlor. The Brome grass and oak microcosms had the lowest Ksat of all treatments and S-Metolachlor retardation factors were equal and slightly increased compared to the control, respectively. These results show that agroforestry buffer's efficiency can be optimized by selecting appropriate species., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Computer models are commonly used for predicting risks of runoff P loss from agricultural fields by enabling simulation of various management practices and climatic scenarios. For P loss models to be useful tools, however, they must accurately predict P loss for a wide range of climatic, physiographic, and land management conditions. A complicating factor in developing and evaluating P loss models is the relative scarcity of available measured field data that adequately capture P losses before and after implementing management practices in a variety of physiographic settings. Here, we describe the development of the P Loss in runoff Events from Agricultural fields Database (PLEAD)-a compilation of event-based, field-scale dissolved and/or total P loss runoff loadings from agricultural fields collected at various research sites located in the US Heartland and southern United States. The database also includes runoff and erosion rates; soil-test P; tillage practices; planting and harvesting rates and practices; fertilizer application rate, method, and timing; manure application rate, method, and timing; and livestock grazing density and timing. In total, >1800 individual runoff events-ranging in duration from 0.4 to 97 h-have been included in the database. Event runoff P losses ranged from <0.05 to 1.3 and 3.0 kg P ha for dissolved and total P, respectively. The data contained in this database have been used in multiple research studies to address important modeling questions relevant to P management planning. We provide these data to encourage additional studies by other researchers. The PLEAD database is available at ., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Hydrologic models are essential tools for environmental assessment of agricultural nonpoint-source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, limiting their application. The study objective was to develop and evaluate a stepwise, multiobjective, multivariable automatic calibration method for the Agricultural Environmental Policy eXtender (APEX) model for simulating runoff, sediment, total phosphorus (TP), and total nitrogen (TN). The most sensitive parameters were grouped according to the process they primarily affect (runoff, sediment transport, soil biological activity, TP transport, and TN transport) and were optimized separately and consecutively. Two multiobjective functions comprising combinations of coefficient of determination (), regression slope, and Nash-Sutcliffe coefficient (NSC) and a global objective function, the Generalized Likelihood Uncertainty Estimation, were considered to select the optimal parameter combination. A previously manually calibrated and validated APEX model for three adjacent row-crop field-size watersheds in northeast Missouri was used as the baseline. The greatest improvements in model performance for sediment, TP, and TN, but not for runoff, were found after runoff parameter optimization, indicating that runoff parameter optimization was crucial for good simulation of sediment and nutrients. The values for sediment, TP, and TN improved from 0.59-0.87 to 0.77-0.94. The NSC values for TP also improved after soil biological activity and TP parameter optimizations, but subsequent optimizations did not improve sediment or TN simulations. The objective function based on , slope, and NSC outperformed the other objective functions. Modelers can benefit from this cost-efficient optimization technique (2570 runs for 23 parameters)., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

The Agricultural Policy Environmental Extender (APEX) model is used to evaluate best management practices on pollutant loading in whole farms or small watersheds. The objectives of this study were to conduct a sensitivity analysis to determine the effect of model parameters on APEX output and use the parameterized, calibrated, and validated model to evaluate long-term benefits of grass waterways. The APEX model was used to model three (East, Center, and West) adjacent field-size watersheds with claypan soils under a no-till corn ( L.)/soybean [ (L.) Merr.] rotation. Twenty-seven parameters were sensitive for crop yield, runoff, sediment, nitrogen (dissolved and total), and phosphorous (dissolved and total) simulations. The model was calibrated using measured event-based data from the Center watershed from 1993 to 1997 and validated with data from the West and East watersheds. Simulated crop yields were within ±13% of the measured yield. The model performance for event-based runoff was excellent, with calibration and validation > 0.9 and Nash-Sutcliffe coefficients (NSC) > 0.8, respectively. Sediment and total nitrogen calibration results were satisfactory for larger rainfall events (>50 mm), with > 0.5 and NSC > 0.4, but validation results remained poor, with NSC between 0.18 and 0.3. Total phosphorous was well calibrated and validated, with > 0.8 and NSC > 0.7, respectively. The presence of grass waterways reduced annual total phosphorus loadings by 13 to 25%. The replicated study indicates that APEX provides a convenient and efficient tool to evaluate long-term benefits of conservation practices., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Despite increased attention and demand for the adoption of agroforestry practices throughout the world, rigorous long-term scientific studies confirming environmental benefits from the use of agroforestry practices are limited. The objective was to examine nonpoint-source pollution (NPSP) reduction as influenced by agroforestry buffers in watersheds under grazing and row crop management. The grazing study consists of six watersheds in the Central Mississippi Valley wooded slopes and the row crop study site consists of three watersheds in a paired watershed design in Central Claypan areas. Runoff water samples were analyzed for sediment, total nitrogen (TN), and total phosphorus (TP) for the 2004 to 2008 period. Results indicate that agroforestry and grass buffers on grazed and row crop management sites significantly reduce runoff, sediment, TN, and TP losses to streams. Buffers in association with grazing and row crop management reduced runoff by 49 and 19%, respectively, during the study period as compared with respective control treatments. Average sediment loss for grazing and row crop management systems was 13.8 and 17.9 kg ha yr, respectively. On average, grass and agroforestry buffers reduced sediment, TN, and TP losses by 32, 42, and 46% compared with the control treatments. Buffers were more effective in the grazing management practice than row crop management practice. These differences could in part be attributed to the differences in soils, management, and landscape features. Results from this study strongly indicate that agroforestry and grass buffers can be designed to improve water quality while minimizing the amount of land taken out of production., (American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Restored prairies are expected to improve soil physical properties, yet little is known about the extent of change to soil properties and how rapidly these changes take place. The objective of this study was to compare effects of prairie restoration on computed tomography (CT)-measured pore parameters. Undisturbed soil cores (76 mm diam. by 76 mm long) from native prairie (NP), restored prairie (RP), conservation reserve program (CRP), and no-till corn (Zea mays L.)-soybean (Glycine max (L.) Merr.; CS) sites were collected with six replicates from the 0- to 40-cm depth in 10-cm increments. Five CT images were acquired from each soil core using a medical CT scanner with 0.2 by 0.2 mm pixel resolution with 0.5 mm slice thickness, and then images were analyzed. Soil bulk density and hydraulic conductivity (K(sat)) were also measured. Soils under NP, RP, CRP, and CS areas had 83, 43, 48, and 26 pores on a 2500 mm(2) area, respectively, for the 0- to 40-cm depth. The number of pores, number of macropores (>1000 microm diam.), macroporosity, mesoporosity (200-1000 microm diam.), and fractal dimension were significantly higher and pore circularity was lower for NP, RP, and CRP than the CS treatment. The CT-measured mesoporosity and macroporosity of the CS treatment were 20 and 18% of the values for the NP site. CT-measured number of pores and macropores explained 43 and 40% of the variation for K(sat). The study showed that prairie restoration improves CT-measured soil pore parameters and decreases bulk density which are related to soil water infiltration.

Effects of precipitation, runoff, and management on total phosphorus (TP) loss from three adjacent, row-cropped watersheds in the claypan region of northeastern Missouri were examined from 1991 to 1997 to understand factors affecting P loss in watersheds dominated by claypan soils. Runoff samples from each individual runoff event were analyzed for TP and sediment concentration. The annual TP loss ranged from 0.29 to 3.59 kg ha(-1) with a mean of 1.36 kg ha(-1) across all the watersheds during the study period. Significantly higher loss of TP from the watersheds was observed during the fallow period. Multiple small runoff events or several large runoff events contributed to loss of TP from the watersheds. Total P loss in 1993, a year with above-normal precipitation, accounted for 30% of the total TP loss observed over seven years. The five largest runoff events out of a total of 66 events observed over seven years accounted for 27% of the TP loss. The five largest sediment losses were responsible for 24% of the TP loss over seven years. Runoff volume and sediment loss explained 64 to 73% and 47 to 58% of the variation in TP loss on watersheds during the study. Flow duration and maximum flow accounted for 49 and 66% of TP loss, respectively. The results of this study suggest that management practices that reduce runoff volume, flow duration, maximum flow, and sediment loss, and that maintain a suitable vegetative cover throughout the year could lower P loss in claypan soils.

A paired watershed study consisting of agroforestry (trees plus grass buffer strips), contour strips (grass buffer strips), and control treatments with a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation was used to examine treatment effects on runoff, sediment, and nutrient losses. During the (1991-1997) calibration and subsequent three-year treatment periods, runoff was measured in 0.91- and 1.37-m H-flumes with bubbler flow meters. Composite samples were analyzed for sediment, total phosphorus (TP), total nitrogen (TN), nitrate, and ammonium. Calibration equations developed to predict runoff, sediment, and nutrients losses explained 66 to 97% of the variability between treatment watersheds. The contour strip and agroforestry treatments reduced runoff by 10 and 1% during the treatment period. In both treatments, most runoff reductions occurred in the second and third years after treatment establishment. The contour strip treatment reduced erosion by 19% in 1999, while erosion in the agroforestry treatment exceeded the predicted loss. Treatments reduced TP loss by 8 and 17% on contour strip and agroforestry watersheds. Treatments did not result in reductions in TN during the first two years of the treatment period. The contour strip and agroforestry treatments reduced TN loss by 21 and 20%, respectively, during a large precipitation event in the third year. During the third year of treatments, nitrate N loss was reduced 24 and 37% by contour strip and agroforestry treatments. Contour strip and agroforestry management practices effectively reduced nonpoint-source pollution in runoff from a corn-soybean rotation in the clay pan soils of northeastern Missouri.