Tag: nitrogen

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High Clearance Robotic Irrigation Impacts on Soybeans and Corn Yield and Nutrient Application

Purpose

This collaborative project between The Ohio State University, Iowa State University, and 360YieldCenter intends to demonstrate the in-season application of commercial and animal nutrient sources and water application as a unified strategy to reduce nutrient losses while improving profitability with increased grain yields. A new and innovative high-clearance robotic irrigator (HCRI) is being used to apply liquid-phase nutrients in-season beyond all stages of row crops. Replicated strip trials of Fall, Spring, and in-season application will occur using the HCRI (e.g., 360 RAIN Robotic Irrigator, Figure 1). The in-season application consists of traditional N and P application rates as well as reduced rates to take advantage of better matching nutrient availability to crop needs during the growing season. Data were collected to verify nitrate-nitrogen leaching loss using liquid swine manure as a nutrient source in Iowa, while total and dissolved reactive phosphorus losses with both runoff and leaching using commercially available nutrients were collected in in Ohio. Secondly, as climate shifts result in water scarcity during critical crop growth stages, robotic irrigation water applications will be used to meet the crop needs. Higher crop yields are anticipated via precision water management.

Figure 1: 360 RAIN Unit (HCRI)
Figure 1: 360 RAIN Unit (HCRI)

What Did We Do?

OSU is conducting two field demonstrations, one with a focus on water quality, and a second for comparison of nutrient management practices. The HCRI is being utilized to apply commercial fertilizer in-season via dilution in irrigation water with up to 12 applications per growing season (effective 4.5 in. of precipitation season dependent). Nutrient injection rates (N and P) are scaled to plant nutrient uptake and irrigator pass intervals. Both sites are farmed in accordance with existing crop rotation and standard practices.

Beck’s Hybrid Site (West 1A) – The Beck’s Hybrid site (78 ac) is subdivided in accordance with the sub-watershed boundaries and managed with two treatments: 1) conventional commercial fertilizer application in accordance with the Tri-State Fertilizer recommendations, and 2) in-season nutrient management (N and P) using the HCRI and Tri-State Fertilizer Recommendations with the exception nutrient application  matching with plant nutrient uptake rates as judged by growing degree days (GDD). This site is instrumented as a paired watershed for surface water and subsurface tile drainage. Further, these watersheds are monitored for precipitation, flow, and water quality (nitrate, nitrite, total phosphorus and DRP).

Molly Caren Agricultural Center (MCAC) Site 1 (Field 7) – Field demonstrations at this site (140 ac) are laid-out in a randomized complete block design (RCBD) strip trial design with treatments that include: 1) commercial fertilizer application (N and P) in accordance with the Tri-State Fertilizer recommendations, 2) in-season nutrient management (N and P) using the HCRI and Tri-State Recommendations with the exception nutrient application matched with crop nutrient uptake rates based on growth stages as determined by GDD, and 3) in-season nutrient management (N and P) using the HCRI and 67.7% Tri-State recommend application rates matched with crop nutrient uptake rates based on growth stages (GDD). Strip trials are 160 ft. in width and approximately 1,170 ft. in length (4.3 ac treatments) with eight replicates.

MCAC Site 2 (Field 8A) – Field demonstration site used to test HCRI and “sandbox” for other RCBD trials outside of NRCS CIG grant to discovery and planning for future projects. This site varies depending on studies each year, but trials are completed via RCBD strips.

Data Collection and Analysis – Demonstration sites are grid sampled each season on a 1-ac grid (Beck’s) and within treatments (MCAC site) to monitor soil fertility levels. Soil moisture and temperature in situ sensors (CropX) are placed in both study locations (three per treatment, 15 total sensors). Tissue samples are collected by treatment type to assess nutrient uptake at three stages of crop growth. Harvested crops are scaled by treatment to ensure yield monitor accuracy. Remote sensing imagery (RGB, ADVI and thermal) is collected 10 or more times during the growing season to evaluate crop growth and development. Data is analyzed using RCBD procedures in SAS.

Water Quality Assessment – Surface and subsurface (tile) monitoring capacity was established in 2016 at the Beck’s Hybrid Site. Two isolated subareas within a single production field were identified and the surface and subsurface pathways were instrumented with control volumes and automated sampling equipment. Surface runoff sites were equipped with H-flumes while compound weirs were installed at each of the subsurface (tile) outlets. Each sampling point (two surface and two subsurface) is equipped with an automated water quality sampler and programmed to collect periodic samples during discharge events. Once collected, samples will be analyzed for N and P. An on-site weather station provides weather parameters. Water samples are collected weekly from the field plots during periods of drainage and follow the same ISU protocol for NO3–N. Dissolved reactive phosphorus (DRP) and digested (total phosphorous) samples are analyzed using ascorbic acid reduction method.

What Have We Learned?

2023 Results

At the Beck’s Hybrid location field West 1A was planted to corn for the 2023 cropping season. There was an 8.0 bu/ac difference between irrigated and non-irrigated treatments. Nitrogen was injected using the rain unit and put on crop for the first application and use of the rain machine. Not having the rain unit in June made a significant difference in this study. The results of this location from 2023 should be taken lightly as complete implementation was not done until August. Location study information can be seen in Figure 2 and results in Figure 3.

Figure 2: Study information for Beck's Hybrid location in 2023 cropping season.
Figure 2: Study information for Beck’s Hybrid location in 2023 cropping season.
Figure 3: Results for Beck's Hybrid field location in 2023.
Figure 3: Results for Beck’s Hybrid field location in 2023.

In 2023, field 7 at MCAC was in soybeans and had no irrigation completed for this growing season.

Field 8A at MCAC was in corn for the 2023 cropping season. Irrigation had a statistically significant effect on yield over all treatments. Nitrogen had statistical significance from 120 versus 170 and 220 units on nitrogen treatments. The 170 units of nitrogen was the optimal amount of nitrogen for all treatments. Not having the irrigator installed in early June caused there to be less yield in irrigated treatments. The results of this location from 2023 should be taken lightly as complete implementation was not done until August. Location study information can be seen in Figure 4 and results in Figure 5.

Figure 4: Study information for MCAC 8A location in 2023 cropping season.
Figure 4: Study information for MCAC 8A location in 2023 cropping season.
Figure 5: Results for MCAC 8A field location in 2023.
Figure 5: Results for MCAC 8A field location in 2023.

2024 Results

Field 7 at MCAC was in corn for the 2024 cropping season. Irrigation had a statistically significant effect on yield over all treatments. There was a 48 bu/ac between irrigated two-thirds nutrients and non-irrigated and 44 bu/ac between irrigated and non-irrigated for the 2024 growing season. A total of 773 gallons of diesel was used to run the irrigator for this trial for 2024 cropping season across 71 acres. A total of 25,739 kWh was used to run the electric pumps, base station, and well for 2024 growing season across 71 acres. These are the initial results that were published in efields and further results will continue to be analyzed to meet all project objectives. This data will be used to help in evaluating HCRI versus traditional crop production and management practices to meet project objectives. Location study information can be seen in Figure 6 and results in Figure 8. In Figure 7, aerial imagery can be seen from the 2024 cropping season.

Figure 6: Study information for MCAC 7 location in 2024 cropping season.
Figure 6: Study information for MCAC 7 location in 2024 cropping season.
Figure 7: Aerial imagery of field 7 (Top l) and field 8A (Bottom left) from 2024 cropping season.
Figure 7: Aerial imagery of field 7 (Top l) and field 8A (Bottom left) from 2024 cropping season.
Figure 8: Results for MCAC 7 field location in 2024.
Figure 8: Results for MCAC 7 field location in 2024.

Field 8A at MCAC was in soybeans for the 2024 cropping season. Irrigation had a statistically significant effect on yield over non-irrigated. A total of 211 gallons of diesel was used to run the irrigator for this trial for 2024 cropping season across 11 acres. A total of 3,475 kWh was used to run the electric pumps, base station, and well for 2024 growing season across 11 acres. Location study information can be seen in Figure 9 and results in Figure 10. In Figure 7, aerial imagery can be seen from the 2024 cropping season.

Figure 9: Study information for MCAC 8A location in 2024 cropping season.
Figure 9: Study information for MCAC 8A location in 2024 cropping season.
Figure 10: Results for MCAC 8A field location in 2024.
Figure 10: Results for MCAC 8A field location in 2024.

Future Plans

During the next 12 months, we are planning for the HCRI operation at the two sites for cropping practices and irrigation for 2025 growing season. We will be aggregating weather data, agronomic data, plant samples, surface and ground water quality samples, and machine performance data for all years of the project with the current end date as spring of 2026. We are hoping to continue to perform testing with this technology and implementing the dry product skid for field operations for the 2025 growing and full-scale implementation across all studies in 2026. The results from the Iowa State portion of this funded project will also be reported in the future as well. There is a significant need to further develop programs for injecting macro and micronutrients in liquid and granular form for growers. The potential to significantly cut application rates exists with this technology. Also, implementing this technology with liquid livestock manure producers will change the paradigm of how manure is managed in the future.

Authors

Presenting & corresponding author

Andrew Klopfenstein, Senior Research Engineer, The Ohio State University, Klopfenstein.34@osu.edu

Additional authors

Justin Koch, Innovation Engineer, 360YieldCenter; Kapil Arora, Field Agricultural Engineer, Iowa State University; Daniel Anderson, Associate Professor, Iowa State University; Matthew Helmers, Professor, Iowa State University; Kelvin Leibold, Farm Management Specialist, Iowa State University; Alex Parsio, Research Engineer, The Ohio State University; Chris Tkach, Lecturer, The Ohio State University; Christopher Dean, Graduate Research Associate, The Ohio State University; Ramareo Venkatesh, Research Associate, The Ohio State University; Elizabeth Hawkins, Agronomics Systems Field Specialist, The Ohio State University; John Fulton, Professor, The Ohio State University; Scott Shearer, Professor and Chair, The Ohio State University

Additional Information

eFields On-Farm Research Publication 2023 and 2024 Editions – https://digitalag.osu.edu/efields

Acknowledgements

Natural Resources Conservation Service – Conservation Innovation Grant (NR223A750013G037)

Ohio Department of Agriculture – H2Ohio Grant

USDA, NRCS, 360YieldCenter, Beck’s Hybrids, Molly Caren Agricultural Center, Rooted Agri Services, Iowa State University, The Ohio State University

 

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date.

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Assessing the impacts of crop and nutrient management practices on long-term water quality and quantity in a dairy intensive irrigated agricultural region using the SWAT model

Purpose

The dairy industry in Idaho has grown substantially over the past 30 years and is the state’s largest agricultural commodity, accounting for $3.7 billion in sales in 2022. Roughly 500,000 of Idaho’s 660,000 dairy cows reside in a six-county region known as the Magic Valley, a name originating in the early 1900s when large canal irrigation projects turned a dry landscape into verdant farmland. The Magic Valley is semi-arid, receiving around 254 mm of precipitation each year and requiring cropland to be irrigated throughout the growing season. Due to a limited amount of water available for irrigation each season cropland area has not expanded since the 1980s.

The large number of dairy cows in the Magic Valley has shifted crop production towards forage crops, predominantly silage corn and alfalfa. For example, between 1992 and 2022 the number of dairy cows in Twin Falls County increased from 18,000 to 108,000. During this same timespan corn silage and alfalfa saw a 14,000 and 5,000 hectare increases in land cover, respectively (Figure 1). This change in land cover has potentially increased consumptive water use within the region through the replacement of crops with shorter irrigation seasons (e.g., wheat and beans) with forage crops. In addition to changes in water use, the increase in dairy cattle has resulted in greatly increased manure applications to surrounding fields. It is typical for cropland to receive manure at rates of 52 Mg ha-1 year-1, which can input high amounts of nitrogen and phosphorus beyond what is removed by the crop. Over time, this could result in soil phosphorus enrichment and the leaching of nitrate to groundwater.

Figure 1. Population of dairy cows in Twin Falls County from 1992 to 2022 along with total hectares of corn silage and alfalfa.
Figure 1. Population of dairy cows in Twin Falls County from 1992 to 2022 along with total hectares of corn silage and alfalfa.

What Did We Do?

The study area for this project was the Twin Falls Canal Company, a large irrigation project in southern Idaho. Investigation into potential changes in water quality and quantity brought about by the growing dairy agriculture in southern Idaho was carried out using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physically based geospatial watershed-scale hydrologic model that incorporates climate, topography, soils, land cover, and management practice data. Model scenarios included examining changes in consumptive water use over time, effects of irrigation practices on the leaching of water and nutrients, and the impact of continuous manure applications on the buildup and leaching of nutrients. Nutrient cycling and crop nutrient uptake were calibrated in the model using two USDA-ARS eight-year studies. The first study applied manure under a corn-barley-alfalfa rotation only when soil nutrient concentrations were deficient, and the second study applied manure on a yearly basis in the spring at a rate of 52 Mg ha-1 under a barley-sugar beet-wheat-potato rotation.

Table 1. Crop areas and percentages under the 1992 and 2022 scenarios.

1992 km2 (%) 2022 km2 (%)
Alfalfa 189 (25.3) 244 (32.8)
Barley 104 (13.9) 132 (17.7)
Beans 169 (22.7) 60 (8.0)
Corn Silage 55 (7.4) 191 (25.7)
Potatoes 35 (4.6) 34.5 (4.6)
Sugar Beets 46 (6.2) 26 (3.5)
Wheat 148 (19.8) 57 (7.6)

Table 1. Crop areas and percentages under the 1992 and 2022 scenarios.

Consumptive water use within the Twin Falls Canal Company was compared between two distinct time periods: pre-dairy and present. 1992 was selected as the pre-dairy benchmark due to being before large increases in dairy cattle numbers. Modeled crops were alfalfa, barley, beans, corn silage, potatoes, sugar beets, and wheat, which account for over 95% of irrigated cropland within the TFCC. Land cover in 2022 was used as the present scenario, and crop distributions were altered for the 1992 scenario based on USDA agricultural census data (Table 1). The model was run using climate data from 2002 to 2022 to have consistency between the two scenarios and to allow for year-to-year variability weather patterns. Automatic irrigation routines were used in the model, with a 9.1 mm irrigation event being triggered when soil water content dropped 5 mm below field capacity. 9.1 mm was chosen as the daily irrigation amount because it is roughly equivalent to the flow rate of an 850 gallon per minute center pivot. Irrigation schedules varied by crop within the April 15th – October 31st irrigation season (Table 2).

Table 2. Irrigation seasons for modeled crops.

Irrigation Season
Alfalfa April 15th – October 9th
Barley April 15th – July 25th
Beans June 26th – September 10th
Corn Silage May 25th – September 18th
Potatoes May 15th – September 1st
Sugar Beets April 20th – September 25th
Wheat April 15th – July 16th

What Have We Learned?

Modeled changes in land use within the Twin Falls Canal Company towards forage crops for dairy cattle have increased consumptive use during the year by 9% on average. June, August and September showed the greatest average increases in evapotranspiration (ET) (Figure 2). Irrigation amounts increased under the 2022 land use scenario for all months except April. Percolation under the 2022 scenario also increased to an average of 155 mm each year, up from 132 mm in the 1992 land use scenario.

Figure 2. Modeled monthly average cropland ET for the pre-dairy (1992) and post-dairy (2022) land cover scenarios.
Figure 2. Modeled monthly average cropland ET for the pre-dairy (1992) and post-dairy (2022) land cover scenarios.

Typical yearly water diversions for the Twin Falls Canal Company were sufficient to meet the current and future irrigation demand. Diversion reductions in August and September are common depending on reservoir storage and the timing and volume of snowmelt. A shift towards greater cropland area irrigated during those months could require deficit irrigation during extreme drought years, which are likely to become more common given climate change projections indicating reduced snowpack and earlier snowmelt runoff.

SWAT was able to reasonably represent manure nitrification, including the increases in nitrification during the year following sugar beet and potato residue being left on the field (Table 3).  Crop nutrient uptake in the two USDA-ARS studies was also able to be accurately modeled after adjusting nutrient uptake parameters. Modeled soil nitrate and plant-available phosphorus concentrations were similar to field samples. Changes to SWAT source code was necessary to better partition “fast” and “slow” organic nitrogen fractions in manure between the two pools and limit mineralization when the air temperature is below 6 degrees Celsius. Under a manure application rate of 52 Mg ha-1 soil plant-available phosphorus levels exceed the allowed maximum of 40 mg kg-1 in just two years. Applying manure only when needed to satisfy crop nutrient requirements did not result in soil plant-available phosphorus approaching or exceeding the 40 mg kg-1 threshold. In addition to high soil phosphorus levels, nitrogen mineralization from yearly applications of manure resulted in high soil nitrate levels. Modeled percolation using actual irrigation amounts over the eight-year study totaled 1,176 mm and resulted in 1,256 kg ha-1 of leached nitrogen. This highlights the risk that yearly manure applications can have to water quality, especially if water is applied in excess of crop needs when also accounting for soil moisture. In addition, high variability in manure nitrogen and phosphorus concentrations suggests yearly fixed-rate applications are not the ideal for managing nutrient budgets.

Table 3. Yearly and in-season manure nitrogen mineralization from the SWAT model output compared to in-season nitrogen mineralization collected from field samples during the long-term manure study. Asterisks denote years in which sugar beet or potato residue was left on the field, resulting in greater N mineralization the following year.

Year SWAT N Mineralization SWAT In-Season N

Mineralization

 Field In-Season Mineralization
kg ha-1 kg ha-1 kg ha-1
2013 211 117 180
2014* 287 192 110
2015 442 308 280
2016* 321 205 190
2017 399 242 250
2018* 297 197 150
2019 393 285 230
2020 357 145 150
Total 2,707 1,690 1,540

Future Plans

Now that the SWAT model has been fully calibrated, the next step will be to test various scenarios in which yearly manure application amounts, crop rotations, and irrigation schedules are adjusted. Typical regional dairy crop rotations include silage corn, alfalfa, wheat, barley, triticale, and occasionally potatoes or sugar beets. Manure is not applied to alfalfa, possibly allowing for a drawdown of phosphorus that has accumulated over previous years. Changing irrigation schedules will alter the timing and quantity of percolated water which will change nutrient export characteristics. Incorporating these scenarios over a large irrigation district with variable soils should identify areas that are more at risk of nutrient losses through runoff or leaching. Results from this research will be used to inform management agencies on the water use and water quality implications of crop rotations, manure applications, and irrigation schedules in southern Idaho.

Authors

Presenting & corresponding author

Galen I. Richards, PhD Candidate, University of Idaho, grichards@uidaho.edu

Additional authors

Erin Brooks, Professor, Department of Soil and Water Systems, University of Idaho

Linda Schott, Assistant Professor and Nutrient & Waste Management Extension Specialist, Department of Soil and Water Systems, University of Idaho

Kossi Nouwakpo, Research Soil Scientist, USDA-ARS Northwest Irrigation and Soils Research Station

Daniel Strawn, Professor, Department of Soil and Water Systems, University of Idaho

Additional Information

https://www.uidahoisaid.com/

Acknowledgements

This research was funded under the University of Idaho Sustainable Agriculture Initiative for Dairy (ISAID) grant USDA-NIFA SAS 2020-69012-31871

I would like to thank USDA-ARS researchers April Leytem, Robert Dungan, and Dave Bjorneberg at the Northwest Irrigation and Soils Research Station in Kimberly, ID for providing me with data from their long-term research studies and general assistance in accurately modeling regional agricultural practices.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date. 

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Can Environmental Data Spark a Circular Economy? Exploring the Potential of a California Dairy Manureshed

Purpose

California’s San Joaquin Valley (SJV) has uniquely “wicked” problems with nitrogen (N) management as it is a highly productive agricultural region where many communities rely on nitrate-contaminated groundwater for drinking. Some of this N loading is attributed to manure from dairies whose N output often exceeds the requirement of forage N, resulting in surplus manure N. The counties in the SJV have the worst groundwater quality and represent the 8 highest dairy populations. But, they also make up 7 of the 10 counties with the highest fertilizer inputs which also contributes to groundwater degradation. There is no doubt that California dairies contribute to N loading, but they also hold unique potential to utilize their surplus manure N to replace a portion of the 550,000 tons of N fertilizer applied to California’s diverse agricultural production. If appropriate measures are taken, the California dairy industry is well positioned to improve water quality in California by limiting its own excess N application while simultaneously replacing its neighbors’ synthetic inputs. The purpose of this preliminary manureshed analysis is to: 1) identify where surplus manure may become a primary N resource in California and 2) quantify its potential to reduce synthetic fertilizer inputs.

Past manureshed analyses have demonstrated manure’s potential to address crop nutrient requirements while acknowledging difficulties with pathogens, lack of spatially available data for CAFOs, and unpredictable manure nutrient variability within and across facilities. A California manureshed is uniquely challenging because of its large proportion of human-consumed crops and surplus dairy manure, which has a low value-to-mass ratio. However, there has been a concerted effort from government entities and the dairy industry to properly account for dairy manure properties to understand the potential expansion of a dairy manure market. Part of this effort has led to reporting requirements, leading to an abundance of facility-level data including location and N generated. These data can be analyzed to understand the economic and environmental potential of using dairy manure beyond its current practices.

What Did We Do?

We applied past manureshed approaches with California-specific data to understand available dairy manure and crop N need in 2021, which was the most recent crop data available to the authors at the time of publishing these proceedings.

To account for N generated on each dairy, we used the herd data from the California Dairy & Livestock Database (CADD), compiled by the California Air Resources Board. We assumed a milk cow produced 70 lbs of milk a day and, per the ASABE standard, that resulted in 0.92 lbs N per milk cow per day. A calf, dry cow, and heifer were assumed to produce 0.14, 0.5, and 0.26 lbs N per animal per day, respectively.

To calculate recoverable plant available N (PAN) (Figure 1) from manure generated on-farm, we assumed that 30% was lost to ammonia before any land application (Chang et al. 2006) and that manure was 21% organic matter (with 30% of that becoming plant available) and 79% inorganic (NH4+). Of the inorganic fraction available for land application, we assumed that 40% was lost to leaching, volatilization, or denitrification (Chang et al. 2006). We acknowledge that these assumptions about manure handling and, therefore, N forms and transformations are highly variable depending on local conditions, but we feel confident that this represents an accepted target “average” as described by Chang et al. 2006. This paper is a result of an expert panel review and informed California’s current regulatory framework for dairies. We also highlight that our “recoverable” manure only includes that year’s plant available portion and does not account for organic N from previous manure applications that may be contributing to actual available N.

Figure 1: Assumptions to calculate recoverable plant available N
Figure 1: Assumptions to calculate recoverable plant available N

For crop N needs, we first identified farm boundaries and crops grown (up to 4 per year) based on LandIQ data and fertilizer N requirements from the California Crop Fertilization Guidelines and average county yields from USDA NASS. We assigned each LandIQ polygon a value for fertilizer N required (Figure 2). We summed N fertilizer requirements for all land polygons that were within 2, 5, and 10 miles of each dairy. A polygon was considered within a specified distance of a dairy based on the distance from any edge of the field to the latitude/longitude provided in the CADD database. Finally, all fertilizer requirements were multiplied by 1.16 to account for a 60% efficiency for manure and a 70% efficiency for fertilizer.

To determine (hypothetically) allocated manure to nearby fields, we used the Ford Fulkerson algorithm to maximize flow. This algorithm was necessary because there are areas with significant concentration of dairies (Figure 3). Therefore, if a dairy is within 2 (or 5 or 10) miles of a field, it would be competing with other dairies to supply the demand. There would be several combinations possible for each dairy (could access multiple fields) and each field (accessible by multiple dairies) (Figure 4). The algorithm maximized the amount of manure used, and prioritized forage fields (wheat/corn/grass). We assumed that a field could supply manure from multiple dairies and that a dairy could supply manure to multiple fields.

Figure 2: (Left) Recoverable Plant Available Nitrogen generated by dairy facility. (Right) N fertilizer requirement by polygon (lbs/acre) for 2021 (up to 4 crops in one year). Calculated via LandIQ (crop classification) and FREP (fertilizer recommendations, mostly pre-plant).
Figure 2: (Left) Recoverable Plant Available Nitrogen generated by dairy facility. (Right) N fertilizer requirement by polygon (lbs/acre) for 2021 (up to 4 crops in one year). Calculated via LandIQ (crop classification) and FREP (fertilizer recommendations, mostly pre-plant).
Figure 3: Number of dairies within 2, 5, or 10 miles of a field.
Figure 3: Number of dairies within 2, 5, or 10 miles of a field.
Figure 4: 5-by-5 mile area with dairies and field boundaries (actual data, chosen arbitrarily).
Figure 4: 5-by-5 mile area with dairies and field boundaries (actual data, chosen arbitrarily).

What Have We Learned?

Total manure N generated was 298,000 tons, and we estimate that 178,000 tons of that was plant available N (Figure 4). It should be noted that our assumptions about N loss are aligned with ambitious environmental goals and resulted in much higher recovery rates compared to NuGIS. We also make a blanket assumption about relative organic / inorganic forms. In our hypothetical exercise where this manure could be applied to all fields (prioritizing forage first) within 2 miles of dairies, 114,000 tons were allocated, leaving 64,000 tons of surplus manure N. If the boundary were expanded to 5 miles, 143,000 tons could be allocated leaving 35,000 tons of surplus manure N. Surplus manure N was only 15,000 tons if manure could be applied up to 10 miles away from dairies where 163,000 tons were applied. Note that these simulations assume that manure can be applied to any crop (including human-consumed ones), which is not currently realistic.

Figure 5: Recoverable PAN (tons) summed over 8 counties for the 2021 crop year. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the field’s edge.
Figure 5: Recoverable PAN (tons) summed over 8 counties for the 2021 crop year. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the field’s edge.

The amount of manure available for application varied by county. In Tulare, there was still a surplus N of 10,500 tons when assuming manure could be applied to all acreage within 10 miles of a dairy (Figure 6). However, in 3 counties (Fresno, San Joaquin, Madera), all hypothetical fertilizer N requirement could be met by applying manure within just 5 miles. Merced, Stanislaus, and Kern had fertilizer requirements met by expanding the allowed distance traveled to 10 miles. The crop types that were fulfilled by manure also differed by county (Figure 7, aggregated by county of field receiving manure).

Figure 6: Recoverable nitrogen (tons) summed by 8 counties for the 2021 crop year. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the edge.
Figure 6: Recoverable nitrogen (tons) summed by 8 counties for the 2021 crop year. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the edge.
Figure 7: Nitrogen fertilizer requirement fulfilled by manure*, categorized by crop. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the edge.
Figure 7: Nitrogen fertilizer requirement fulfilled by manure*, categorized by crop. *Maximum manure applied to fields is hypothetical and based on the Ford Fulkerson Algorithm where the goal was to maximize flow of manure to fields from dairies within 2, 5, or 10 miles from the edge.

The California agricultural landscape, with many fruits and vegetables that go directly to human consumption, makes our hypothetical application rate currently unviable. For example, the only dairy forage crops with substantial acreage that are currently eligible for raw manure application are wheat, alfalfa (which does not receive N), and corn. These make up between 18-44% of area within 2 miles of a dairy, and increasing the distance from a dairy up to 10 miles decreases the percentage of crops that are forage (Figure 8). In other words, the farther away from a dairy, the more likely land use is classified as a crop that would be flagged for pathogen concerns. This highlights that to effectively use manure in the SJV, there will need to be a concerted effort to address logistical issues associated with human-consumed crops. However, these crops are generally high value, and some commodities are concentrated within a county (Figure 7).

Figure 8: Crop acreage of fields around dairies. Fields were included if their edge was within 2, 5, or 10 miles of a dairy.
Figure 8: Crop acreage of fields around dairies. Fields were included if their edge was within 2, 5, or 10 miles of a dairy.

Future Plans

This phase of the manureshed analysis was intended to demonstrate the potential for manure to reduce fertilizer inputs; however, its practical applications are limited. In the next phase, we hope to improve our analysis by accounting for more details of manure, such as solid vs. liquid (for improved predictions of N content/transformation/transportability) and phosphorus and potassium concentration/stoichiometry. We will work with commodity groups, with a focus on those within 10 miles of dairies, to understand the current level of interest and obstacles for integrating different manure products into their cropping systems. These improvements to our methodology will result in a quantification of environmental and economic opportunity to increase the likelihood of a circular economy by expanding the use of dairy manure.

Authors

Presenting & corresponding author

Emily R Waring, Agricultural Practice Impact Analyst, Sustainable Conservation, ewaring@suscon.org

Additional authors

    • Ryan Flaherty, Senior Director of Circular Economies, Sustainable Conservation
    • Sarah Castle, Senior Scientist, Sustainable Conservation
    • John Cardoza, Project Director, Sustainable Conservation

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date. 

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Manure nutrient trends from 2012-2022

Purpose

Livestock manure nutrients can be variable depending on animal species, age, diet, management, housing, climate, and manure storage and handling. Thousands of samples are analyzed every year by agricultural laboratories across the United States (U.S.). While many published manure characteristics are two decades old, this study provides an updated glimpse into more recent manure data from thousands of samples across the country and reviewed possible trends from 2012-2022 by U.S. regions for common animal categories.

What Did We Do?

We collected manure nutrient data from participating U.S. laboratories and this data was aggregated by researchers at the University of Minnesota into ManureDB, a manure nutrient test database. By February 2024, ManureDB included over 490,000 samples from across the U.S. With ManureDB, data was filtered for the time period from 2012-2022 and common U.S. animal manure categories (solid beef, liquid beef, solid dairy, liquid dairy, solid chicken-broiler, solid chicken-layer, solid turkey, and liquid swine manure) to update nutrient summary statistics for total nitrogen (TN), ammonium-N (NH4-N), phosphorus (P2O5), and potassium (K2O) using the approximately 325,000 samples. Samples were divided by designating samples with <10% total solids as liquid manure and samples with >10% total solids as solid manure. Data was also analyzed to assess regional nutrient comparisons and trends for regions with sufficient samples.

What Have We Learned?

Regional differences impacted nutrient concentrations in solid and liquid manures. When comparing regions with at least 500 samples per animal manure category across 2012-2022 we found significant differences in nutrient concentrations in 66% of the individual year comparisons for solid manures and 91% of comparisons for liquid manures for all four analytes.

Between 2012 and 2022, significant increasing or decreasing nutrient (TN, NH4-N, P2O5, K2O) trends were evident in 25% of solid samples and 18% of liquid samples. The only significant trend for solid beef manure was a decreasing trend in the SE region for NH4-N. Both the solid chicken-broiler SE and NE regions had significant decreases in NH4-N, and only the SE had an increasing trend for K2O. The SE region for solid chicken-layer had decreasing trends for NH4-N, P2O5, and K2O. For solid dairy manure, the MW region only had a decreasing trend for P2O5, while the NE region had decreasing trends for N and NH4-N. Solid turkey manure only had significant trends for P2O5, with the MW increasing and the SE decreasing. Liquid beef manure had no significant trends. For liquid dairy manure, only the NE region had significant decreasing trends for all four nutrients. For liquid swine manure, only the SE region had significant increasing trends for NH4-N.

Standardizing nomenclature and increasing manure sample details, especially with animal life stage and manure storage information on manure sample submittal forms, will further improve ManureDB’s usefulness.

Future Plans

We continue to expand and refine ManureDB by adding data each year, additional labs, making the website more user-friendly, and enhancing data quality control. We archived the first set of data with Ag Data Commons in 2024 and plan to do that annually. We also plan to publish several papers regarding the development of the database and analysis of the manure nutrient data.

Authors

Presenting & corresponding author

Nancy L. Bohl Bormann, Researcher, University of Minnesota, nlbb@umn.edu

Additional authors

Melissa L. Wilson, Associate Professor, University of Minnesota

Erin L. Cortus, Associate Professor and Extension Engineer, University of Minnesota

Additional Information

Acknowledgements

ManureDB is supported through USDA NIFA Award 2020-67021-32465 and Cooperative Ecosystem Studies Unit program [grant no. NR253A750008C001] from the U.S. Department of Agriculture — Natural Resources Conservation Service.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7–11, 2025. URL of this page. Accessed on: today’s date.

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Soil Property Effect on Nitrogen Mineralization of Dairy Manure in the Pacific Northwest

Purpose

Growers often use total nitrogen (N) concentration of dairy manure to estimate plant available N for crop production. This estimate often does not take into account the role soil properties may have on N mineralization (Nmin) rates. This study aims to determine how soil properties impact Nmin rates of dairy manure and composted dairy manure by aerobic incubation. The soil properties investigated, including soil texture, percent organic matter, pH, EC, buffer pH, NO3-N, NH4-N, Olsen P, K, Ca, Mg, Na, CEC, S, Zn, Fe, Mn, Cu, B, and CaCO3 equivalent, which are all accessible to producers sending soil samples to a commercial soil laboratory. The goal of this project is to incorporate soil properties into N availability prediction models for dairy manure to improve N use efficiency of field-applied manure.

What Did We Do?

A total of 16 different soil series were sampled throughout Oregon, Washington, and Idaho in major dairy producing counties at a 12-inch depth. These soils represent over 1.6 million acres in the Pacific Northwest (PNW). One solid dairy manure was sampled in Idaho and one composted dairy manure was sampled in Oregon to be applied to the soils during incubation. All the soils were analyzed for a full suite of soil physiochemical properties at a local soil testing laboratory. The manures similarly received a full analysis at the same laboratory.

We conducted a 12-week incubation of manure-amended soils at 77°F (25°C), sampling periodically for nitrate and ammonium to determine the difference in Nmin rates with changes in soil physiochemical properties. Approximately 1.1 lbs (500 g) of soil was added to 1-gallon Ziplock bags and brought to 80% field capacity. The soils were treated with dairy manure, composted manure, or no manure at a rate of approximately 400 lb N/acre (200 mg N/kg soil) with four replicates for each soil and treatment. Each of the 192 samples were randomly assigned a sample number corresponding to their location inside the incubator. The closed and loosely rolled bags were stored in 12 by 9 by 7-inch cardboard boxes, then placed inside an incubator at 77°F for 12 weeks. Soils were sampled at weeks 0, 2, 4, 8, and 12, where part of the sample was used to monitor soil moisture, and the other was frozen for future analysis. Analysis of the frozen samples for nitrate and ammonium content was conducted using a microplate spectrophotometer using vanadium (III) chloride and sodium salicylate methods, respectively.

What Have We Learned?

The analysis of frozen samples has just begun at the time of submission. Initial results will be available on the poster presented.

Future Plans

The next steps of this project are to conclude the nitrate and ammonium analysis of the soil samples and create Nmin curves with this data for each soil and treatment. These curves will be analyzed to determine if the differences in Nmin rates correlate with any of the tested soil physiochemical properties and which properties are most influential. Finally, we will create a model based on correlation data to express the changes in nitrogen mineralization depending on soil physiochemical properties that can be used by producers to adjust their dairy manure application rates depending on their soil test results.

Authors

Presenting author

Ryan A. Auld, Soil Science Graduate Student, Oregon State University

Corresponding author

Amber Moore, Extension Soil Fertility Specialist, Oregon State University, Amber.moore@oregonstate.edu

Additional authors

Jennifer Moore, Research Soil Scientist, Forage Seed and Cereal Research Unit, U.S. Department of Agriculture Agricultural Research Service; Yakun Zhang, Associate Professor, Oregon State University; Christopher Rogers, Research Soil Scientist, Northwest Irrigation and Soils Research, U.S. Department of Agriculture Agricultural Research Service

Additional Information

Build DAIRY

Acknowledgements

I’d like to acknowledge the BUILD Dairy program and the Oregon Dairy Farmers Association for their support of this project, as well as the many producers who have allowed me to sample soils from their farms.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7–11, 2025. URL of this page. Accessed on: today’s date.

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Reducing Ammonia Emissions from Poultry Litter with Lignite and Lignosulfonate

Due to a technical glitch, we did not get this presentation recorded. Please accept our apologies.

Purpose

The purpose of this study was to determine the effectiveness of lignite, a low-quality coal, and lignosulfonate, a byproduct of paper milling, in reducing ammonia emissions from poultry litter.

What Did We Do?

We utilized a laboratory

 acid-trap chamber system to assess the effectiveness of varying rates of lignite and lignosulfonate on ammonia reduction when compared to an industry standard, sodium bisulfate (PLT), and an untreated control. In the volatilization experiment, 12 treatments were tested, including five application rates of lignite and lignosulfonate (0.75, 1.5, 3, 4.5, and 6 kg m-2), PLT, and an untreated control. Acid traps of 0.02 M phosphoric acid were changed 11 times over the 14-day experiment. Acid trap solutions were then analyzed for ammonia to quantify cumulative ammonia emissions.  

What Have We Learned?

Both lignite and lignosulfonate were effective in reducing ammonia volatilization in this laboratory setting. While both lignite and lignosulfonate required higher application rates to achieve the same ammonia reduction as PLT, these could be effective alternatives and should be further studied on a larger scale.

Future Plans

While we have no active plans to continue this work, future efforts should include small scale testing in a commercial setting, cost analysis, and sourcing options.

Authors

Presenting & Corresponding author

Stephanie Kulesza, Assistant Professor, North Carolina State University, sbkulesz@nscu.edu

Additional Information

This research is not yet published. Reach out to Stephanie Kulesza at sbkulesz@ncsu.edu if you would like to know more about this work.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7–11, 2025. URL of this page. Accessed on: today’s date.

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Integrated Best Management Practices to Minimize Nitrate Leaching in Corn

Purpose

In Nebraska, approximately 117 out of nearly 550 groundwater-based community public water systems are required to conduct quarterly sampling due to elevated nitrate-N levels, with ten systems having already implemented costly treatment measures such as reverse osmosis to mitigate this issue. The intensive production of row crops under irrigation in the state are a primary reason for elevated nitrate concentrations in groundwater. However, the environmental impact of nitrate leaching from agricultural fields is not confined to Nebraska; it is a widespread issue across the US Midwest, where intensive crop production is prevalent.

Despite advances in N management stemming from studies comparing nitrogen fate and transport under synthetic versus manure fertilizers, cover crops versus no cover crops, and other practices, research indicates that when manure is applied following research-based best management practices (BMPs), the risk of nitrate leaching is significantly lower compared to when synthetic fertilizers are applied following BMPs. While individual practices such as cover cropping or manure application have been shown to reduce nitrate leaching, their combined effects on both nitrate leaching potential and crop productivity, particularly in corn (Zea mays L.) systems, have not been thoroughly studied. There remains a critical need to comprehensively evaluate implementation of BMPs that can reduce nitrogen losses to groundwater in Nebraska and utilize evidence-based research to motivate the implementation of BMPs.

This study was conducted to evaluate the effects of the integrated use of beef manure, woodchips, and cover crops on corn (Zea mays L.) productivity and nitrate leaching.

What Did We Do?

A two-year study was conducted on drip-irrigated land with a loamy sand soil having 0 to 2% slopes at UNL’s Haskell Agricultural Laboratory research site near Concord, Nebraska from 2022 to 2023. A total of 24 plots were established, each measuring 6.1 m x 30.48 m, and six treatments were randomly assigned to plots in a factorial combination of two fertilizer sources (manure and inorganic fertilizer), two cover crops (rye cover crop and no cover crop), and two carbon amendment treatments (woodchips of mixed species and no woodchips). Each year, all the plots received the same total N rate, equating to 30% of the total N application broadcasted at planting in the form of Agrotain coated urea, which was calculated using University of Nebraska’s N rate algorithm. The manure plots received the remaining N (70% of the total) in the form of beef manure at planting using a manure spreader. The inorganic plots received the remaining N in the form of UAN side-dressed at the V6 corn growth stage. Each year, inorganic fertilizer plots received additional P, S, and Zn at the time of planting to balance the amount of these nutrients supplied by the manure.

Data collected included:

Soil. Deep core soil samples up to 120 cm were collected before planting in the spring and after harvest each fall, divided into four depths of 30 cm increment, composited by depth within each plot, and stored in a cooler before being transported to the lab for analysis.

Crop. Plant growth parameters assessed at V10 (±1) stage included plant height, leaf chlorophyll, and canopy fullness. Grain yield, harvest index, nitrogen harvest index and partial factor productivity were determined at harvest.

Water. Concentration of NO3-N and NH4-N in the pore water below the root zone was measured one to two times each week throughout the growing season with the help of suction cup lysimeters, two of which were installed 6 m apart between the center two rows of each plot at a depth of 1.2 m.

Cover crop failed to establish in 2023 spring due to dry conditions, therefore, cover crop data and its effects are not reported in this paper.

What Have We Learned?

Key results of this study include:

    • Manure significantly reduced nitrate leaching by providing a slower, more synchronized N release compared to inorganic fertilizers.
    • Woodchip mulch initially delayed N availability and biomass N uptake but ultimately helped reduce nitrate leaching by improving soil moisture retention and temperature moderation.
    • Aboveground biomass N uptake was significantly affected by fertilizer source with manure improving biomass N uptake by 11% compared to inorganic fertilizer.
    • Inorganic fertilizers boosted corn yields by 9% compared to manure treatments, but increased the risk of nitrate leaching, highlighting a trade-off between productivity and environmental impact.
    • Integrated management of manure and mulch was deemed crucial for optimizing N use efficiency and minimizing environmental risks in irrigated corn systems.

Future Plans

Identifying nutrient and land management practices that support sustainable agricultural practices by safeguarding groundwater quality while maintaining farm productivity are critical to the future of agriculture. Future research is expected to focus on refining the practices used in this study to maximize their benefits, including other practices such as in-season nitrogen management, and assessing outcomes under varying environmental conditions and soil types. Nitrogen availability from manure is heavily influenced by environmental and soil conditions, so multi-year data from this site and others should help determine when in-season nitrogen supplementation with inorganic fertilizer is needed to offset nitrogen deficits caused by slow conversion of organic nitrogen.

Because of the failure of cover crops to thrive in this study, future research to assess multiple practices in combination should include a cover crop versus no cover crop treatment.

Combining crop productivity and nitrogen fate and transport data with measures of soil biological conditions may also help identify trends in biological characteristics that contribute significantly to factors like nitrogen conversion and plant nitrogen uptake.

Authors

Presenting & corresponding author

Amy Millmier Schmidt, Professor and Livestock Bioenvironmental Engineering Specialist, University of Nebraska-Lincoln, aschmidt@unl.edu

Additional authors

Swetabh Patel, Assistant Professor, University of Minnesota; Michael Kurtzhals, Graduate Research Assistant, University of Nebraska-Lincoln; Arshdeep Singh, Graduate Research Assistant, University of Nebraska-Lincoln; Leslie Johnson, Extension Educator, University of Nebraska-Lincoln; Javed Iqbal, Assistant Professor, University of Nebraska-Lincoln

Additional Information

https://scisoc.confex.com/scisoc/2024am/meetingapp.cgi/Paper/156921

Acknowledgements

This research was funded by USDA-NIFA Award No. 2022-68008-36509.

The authors extend their sincere gratitude to Logan Dana, Operations Manager at the UNL Haskell Ag Lab, for his role in supporting this project.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7–11, 2025. URL of this page. Accessed on: today’s date.

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Conservation Planning for Air Quality and Atmospheric Change (Getting Producers to Care about Air)

Purpose

The United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS) works in a voluntary and collaborative manner with agricultural producers to solve natural resource issues on private lands. One of the key steps in formulating a solution to those natural resource issues is a conservation planning process that identifies the issues, highlights one or more conservation practice standards that can be used to address those issues, and allows the agricultural producer to select those conservation practices that make sense for their operation. In this conservation planning process, USDA-NRCS looks at natural resource issues related to soil, water, air, plants, animals, and energy (SWAPA+E). This presentation focuses on the resource concerns related to the air resource.

What Did We Do

In order to facilitate the conservation planning process for the air resource, USDA-NRCS has focused on five main issues: emissions of particulate matter (PM) and PM precursors, emissions of ozone precursors, emissions of airborne reactive nitrogen, emissions of greenhouse gases, and objectionable odors. Each of these resource concerns are further subdivided into resource concern components that are mainly associated with different types of sources or activities found on agricultural operations. By focusing on those agricultural sources and activities that have the largest impact on each of these air quality and atmospheric change resource concerns, USDA-NRCS has developed a set of planning criteria for determining when a resource concern exists. We have also identified those conservation practice standards that can be used to address each of the resource concern components.

What Have We Learned

Our focus on the agricultural sources and activities that have the largest impact on air quality has helped to evolve the conservation planning process by adding resource concern components that are targeted and simplified. This approach has led to a clearer definition of when a resource concern is identified, as well as how to address it. For example, the particulate-matter focused resource concern has been divided into the following resource concern components: diesel engines, non-diesel engine combustion equipment, open burning, pesticide drift, nitrogen fertilizer, dust from field operations, dust from unpaved roads, windblown dust, and confined animal activities. Each of these types of sources can produce particles directly or gases that contribute to fine particle formation. In order to know whether a farm has a particulate matter resource concern, a conservation planner would need to determine whether one or more of these sources is causing an issue. Once the source(s) of the particulate matter issue is identified, a site-specific application of conservation practices can be used to resolve the resource concern.

We expect that increased clarity in the conservation planning process will lead to a greater understanding of the air quality and atmospheric change resource concerns and how agricultural producers can reduce air emissions and impacts. Simple and clear direction should eventually lead to greater acceptance of addressing air quality and atmospheric change resource concerns.

Future Plans

USDA-NRCS will continue to refine our approach to addressing air quality and atmospheric change resource concerns. As we gain a greater scientific understanding of the processes by which air emissions are generated and air pollutants are transported from agricultural operations, we can better target our efforts to address these emissions and their resultant impacts. Internally, we will be working throughout our agency to identify those areas where we can collaboratively work with agricultural producers to improve air quality.

Authors

Greg Zwicke, Air Quality Engineer, USDA-NRCS National Air Quality and Atmospheric Change Team
greg.zwicke@usda.gov

Additional Authors
Allison Costa, Air Quality Engineer, USDA-NRCS National Air Quality and Atmospheric Change Team

Additional Information

General information about the USDA-NRCS can be found at https://www.nrcs.usda.gov. An overview of the conservation planning process is available at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/programs/technical/cta/?cid=nrcseprd1690815.

The USDA-NRCS website for air quality and atmospheric change is https://www.nrcs.usda.gov/wps/portal/nrcs/main/national/air/.

 

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2022. Title of presentation. Waste to Worth. Oregon, OH. April 18-22, 2022. URL of this page. Accessed on: today’s date.

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Potential soil health improvement through the integration of cover crops and manure in the upper Midwest

Purpose

Oftentimes fall manure application is associated with significant offsite transport of nitrogen and phosphorus into nearby bodies of water and the atmosphere. Mechanisms of losses include leaching, runoff, sediment transport, and volatilization processes. This is becoming more common as there has been a trend of increased wet springs that create difficult planting conditions. This prolonged period without an active root system leaves more time for nutrient loss from fall-applied manure to occur.

A strategy to offset nutrient losses in the fall and early spring is to plant a cover crop. The uptake of nutrients during this time in the field, which would otherwise be left fallow, allows for nutrients to be stored in the tissue of the cover crops, minimizing nutrient loss risk. Upon terminating the cover crops, the decomposing residues can supply nutrients to the succeeding row-crop. However, cover crop adoption is low in the upper Midwest US stemming from a short cover crop growing season due to the cold climate. This is especially the case for crops utilizing manure. A strategy to expand the cover crop growing season may be to interseed a cover crop into a maturing row-crop prior to harvest. Previous studies investigating the integration of manure and cover crops have seeded the cover crop after manure application. We wanted to measure the impacts of first planting a cover crop then applying manure once the cover crop has had ample time to get established. This may help expand the cover crop growing season and potentially limit the offsite transfer of pollutants to our water and air.

What Did We Do?

A small plot study was started in fall 2019 at the University of Minnesota West Central Research and Outreach Center near Morris, MN. We tested the effect of nitrogen source and cover crops on soil health, nutrient cycling, and agronomic responses using a randomized complete block design with split plots.

Cover crop mixtures of cereal rye and annual ryegrass were interseeded near corn’s fifth leaf collar (V5) growth stage, physiological maturity (R5 to R6 growth stage), or drilled after corn harvest. Dairy manure was sweep-injected to minimize soil disturbance in early and late fall, when soil temperatures were above and below 10°C (50°F), respectively. Non-manured plots received urea in the spring prior to corn planting. Urea applied plots (no manure) with no cover crops served as the control. Soil samples were taken throughout the cover crop and row-crop growing season from the 0-15, 15-30, and 30-60 cm (0-6, 6-12, and 12-24 in) soil layers. Cover crop biomass samples were taken in the late fall prior to the first frost event and prior to cover crop termination in the spring.

What Have We Learned?

Sweep injection is a reliable method to apply liquid manure to a field with an established stand of cover crops with minimal noticeable damage to the cover crops in the spring (Figure 1). Planting cover crops as soon as possible ensures more biomass is produced; planting after harvest consistently had lower cover crop yield than interseeding. Spring cover crop yield, right before termination, was highest when planted near physiological maturity [110 kg ha-1 (98 lb ac-1)] compared to drilling after harvest [87 kg ha-1 (78 lb ac-1)]. Nutrient source had a significant effect on silage yield. Manure, either applied in the early or late fall, had greater silage yield [58.5 and 58.7 Mg ha-1 (26.1 and 26.2 ton ac-1), respectively] than spring applied urea [53.6 Mg ha-1 (23.9 ton ac-1)]. Plots with cover crops interseeded at V5 had greater silage yield [59.5 Mg ha-1 (26.5 ton ac-1)] than all other treatments [54-56 Mg ha-1 (24-25 ton ac-1)] except no cover crops [57.8 Mg ha-1 (25.8 ton ac-1)].

Figure 1. Cover crops planted prior to late manure application. Photo was taken in the spring at cover crop termination.

Future Plans

Soil samples collected throughout the study are currently being analyzed for nutrient content and other soil health parameters. Results from this study will be used to develop best management practices for integrating cover crops and liquid injected manure in the upper Midwest.

Authors

Manuel J. Sabbagh, Graduate Research Fellow, University of Minnesota

Corresponding author email address

sabba018@umn.edu

Additional authors

Melissa L. Wilson, Assistant Professor, University of Minnesota; Paulo H. Pagliari, Associate Professor, University of Minnesota

Additional Information

Twitter: @mannyandmanure @manureprof

Lab website: https://wilsonlab.cfans.umn.edu/

Acknowledgements

This work is supported by the Conservation Innovation Grants program at the Natural Resources Conservation Service of the USDA, the Minnesota Corn Research and Promotion Council, and the Foundation for Food and Agriculture Research.

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How are Filth Flies Involved in Wasting Nitrogen?

Purpose

Filth flies are species from the Diptera order associated with animal feces and decomposing waste. Beef cattle raised on open pastures are especially susceptible to two species of filth flies: Face flies (Musca autumnalis De Geer) and Horn flies (Haematobia irritans (L.))  because these flies develop exclusively in fresh cattle manure. Filth fly impact on cattle health is related not only to the loss of body weight but also to the transmission of diseases like pink eye and mastitis (Basiel, 2020; Campbell, 1976; Hall, 1984; Nickerson et al., 1995).

Nitrogen losses from cattle’s manure has been reported for domestic flies (Musca domestica) and bottle flies (Neomyia cornicina) (Iwasa et al., 2015; Macqueen & Beirne, 1975). Despite the regular presence of face fly and horn fly in pastures, their effect on the nutrient cycles is little known. The purpose of this study is to understand the relationship between filth fly’s presence in cattle manure with the nitrogen losses caused by an increase in ammonia and nitrous oxide emissions.

What Did We Do?

The study was conducted in four pastures in the Georgia Piedmont: two near Watkinsville and two near Eatonton during June, July, and August of 2021. Ammonia volatilization and nitrous oxide emissions were measured on days 1, 4, 8, and 15 following dung deposition. Manure samples were collected on days 1 and 15. A static chamber was sealed for 24 h on each sampling date to capture manure’s ammonia and nitrous oxide emissions. In each chamber, a glass jar with boric acid was used to trap ammonia, and gas samples were collected. The gas samples were analyzed for nitrous oxide with a Varian Star 3600 CX Gas Chromatograph using an electron capture detector.

The number of filth flies was determined using a net trap covered by a black cloth that was set after 1 min of manure deposition, allowing the flies to oviposit for 10 min. On the days in which ammonia was not measured, a net trap was set to avoid additional oviposits, and record the emergence of filth flies. On the 15th day, we collected the filth flies that emerged from the eggs deposited in the manure during the first day.

What Have We Learned?

We found that cattle’s manure nitrogen loss as nitrous oxide (N2O) and ammonia (NH3) emissions have a direct relationship with the number of horn flies and face flies in the dung, Figure 1. Eighty percent of the flies trapped were horn flies. Dung with less than 5 flies can emit as little as 0.11 mg of N/kg of manure per day, while cattle manure with more than 30 flies can increase this emission by more than 10 times.

Figure 1 Nitrogen emissions such as nitrous oxide and ammonia (mg/kg of manure) and number of filth flies.

Every extra filth fly in manure can increase N emissions by 0.03 mg per kg of manure per day. According to NRCS, 59.1 lbs. of fresh manure is produced by a cow (approx. 1 000 pounds animal) every day (NRCS, 1995). Considering an average of 85 % relative humidity, 4.03 kg of dry manure can be produced per cow day. The actual economic threshold for horn fly is 200 flies per animal (Hogsette et al., 1991; Schreiber et al., 1987), considering a 1 to 1 sex ratio during emergence (Macqueen & Doube, 1988) we are assuming 100 female flies. Since the capacity of horn flies is 8-13 eggs per day (Lysyk, 1999), 100 female horn flies can generate approximately 1,000 new flies every day.  Calculating the nitrogen emissions (4.03 kg of dry manure X 0.03 mg N kg manure x 1,000 flies per day) results in 121 mg of N loss per cow per day when assuming the number of flies is just at the economic threshold. In January of 2022, USDA released the Southern Region Cattle Inventory with a total of 91.9 million head, from which 30.1 million were beef cows (USDA, 2022). Considering the earlier numbers, the horn fly presence in the beef cattle of the Southern Region could be emitting 3,639 kg of Nitrogen to the atmosphere every day.

Future Plans

We will continue the study on ammonia and nitrous oxide emissions under the same conditions during another year to confirm the trends and accuracy of the results. Also, we will implement a study to analyze the effect of the introduction of a parasitic wasp Spalangia endius as a biological control on horn fly and face fly populations and therefore on the manure’s nitrogen losses.

Authors

Presenting author

Natalia B. Espinoza, Research Assistant, Department of Crop and Soil Science, University of Georgia

Corresponding author

Dr. Dorcas H. Franklin, Professor, Department of Crop and Soil Sciences, University of Georgia

Corresponding author email address

dfrankln@uga.edu or dory.franklin@uga.edu

Additional authors

Anish Subedi, Research Assistant, Department of Crop and Soil Science, University of Georgia

Dr. Miguel Cabrera, Professor, Department of Crop and Soil Sciences, University of Georgia

Dr. Nancy Hinkle, Professor, Department of Entomology, University of Georgia

Dr. S. Lawton Stewart, Professor, Department of Animal and Dairy Science, University of Georgia

Additional Information

Basiel, B. (2020). Genomic Evaluation of Horn Fly Resistance and Phenotypes of Cholesterol Deficiency Carriers in Holstein Cattle [PennState University]. Electronic Theses and Dissertations for Graduate Students.

Campbell, J. B. (1976). Effect of Horn Fly Control on Cows as Expressed by Increased Weaning Weights of Calves. Journal of Economic Entomology, 69(6), 711-712. https://doi.org/DOI 10.1093/jee/69.6.711

Hall, R. D. (1984). Relationship of the Face Fly (Diptera, Muscidae) to Pinkeye in Cattle – a Review and Synthesis of the Relevant Literature. Journal of Medical Entomology, 21(4), 361-365. https://doi.org/DOI 10.1093/jmedent/21.4.361

Hogsette, J. A., Prichard, D. L., & Ruff, J. P. (1991). Economic-Effects of Horn Fly (Diptera, Muscidae) Populations on Beef-Cattle Exposed to 3 Pesticide Treatment Regimes. Journal of Economic Entomology, 84(4), 1270-1274. https://doi.org/DOI 10.1093/jee/84.4.1270

Iwasa, M., Moki, Y., & Takahashi, J. (2015). Effects of the Activity of Coprophagous Insects on Greenhouse Gas Emissions from Cattle Dung Pats and Changes in Amounts of Nitrogen, Carbon, and Energy. Environmental Entomology, 44(1), 106-113. https://doi.org/10.1093/ee/nvu023

Lysyk, T. J. (1999). Effect of temperature on time to eclosion and spring emergence of postdiapausing horn flies (Diptera : Muscidae). Environmental Entomology, 28(3), 387-397. https://doi.org/DOI 10.1093/ee/28.3.387

Macqueen, A., & Beirne, B. P. (1975). Influence of Some Dipterous Larvae on Nitrogen Loss from Cattle Dung. Environmental Entomology, 4(6), 868-870. https://doi.org/DOI 10.1093/ee/4.6.868

Macqueen, A., & Doube, B. M. (1988). Emergence, Host-Finding and Longevity of Adult Haematobia-Irritans-Exigua Demeijere (Diptera, Muscidae). Journal of the Australian Entomological Society, 27, 167-174. <Go to ISI>://WOS:A1988P906100002

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