Posts – Page 51 – Livestock and Poultry Environmental Learning Community

Purpose

The Natural Resources Conservation Service (NRCS) and partners worked with Eileen Fabian-Wheeler of the Pennsylvania State University to study the manure gas risks associated with gypsum bedding at dairy farms. This was a NRCS Conservation Innovation Grant (CIG) project. As a result of the information gathered and the published final report, NRCS has taken the following actions which are described below.

What did we do?

1. The NRCS National office has published National Bulletin 210-15-9 dated 7/14/15 detailing safety risks from manure storages of dairy cows bedded with gypsum.

2. The NRCS National Standard 333 for Amending Soil Properties with Gypsum Products has included a safety reference warning about adding gypsum to liquid manure storage facilities.

3. Pennsylvania NRCS has led and participated in numerous safety programs discussing the relationship between gypsum added to liquid manure storage facilities and the production of hydrogen sulfide (H2S). Within Pennsylvania (PA), NRCS and agency partner employees have been made aware of the risks of gypsum and excessive H2S production through the repeated use of a wide variety of educational medium.

4. Pennsylvania NRCS developed a new safety sign titled, “During Agitation, Deadly Gases Possible”. The sign was developed in direct response to the new Penn State Conservation Innovation Grant report that H2S is proven to be released during the agitation of manure with gypsum. There are possible ties to other high sulfur materials.

5. Pennsylvania NRCS developed a new PA Fact Sheet #5 titled, “Under Barn Storage Facilities, (Pros and Cons)”. The factsheet was developed to increase awareness of safety risks with under barn manure storages including extreme risks with H2S coming from high sulfur manure/bedding additives. (Can also include other high sulfur feed materials)

6. Pennsylvania has added safety requirements and clarifications to the PA 313 Waste Storage Facility Standard including;

a. requirements for agitation signs at covered/uncovered manure storages,

b. gypsum cannot be added to solid covered or under-the-barn waste storages (known to produce excessive H2S gas production),

c. silage leachate or other materials containing high sulfur cannot be stored in covered under-the-barn storages.

7. Pennsylvania NRCS has added safety warnings and clarifications to the PA 634 Waste Transfer Standard; “Gypsum bedding, silage leachate, and other waste components containing high amounts of sulfur can produce excessive amounts of manure gases…can create dangerous manure gas situations….”

8. Pennsylvania NRCS has rewritten the PADEP/PSU Fact Sheet MM2, to include up-to-date safety information, especially highlighting known H2S gas origins and hazards. Now titled PA NRCS Fact Sheet #10, this is a ready reference available to be supplied to producers at time of manure storage planning and design.

9. Pennsylvania NRCS engineers and others are currently on alert for the proper reporting of manure gas accidents. They are investigating H2S as a probable most significant cause of manure gas accidents. Hydrogen sulfide should be the first manure gas suspected and investigated.

10. Pennsylvania NRCS is alerting our field employees and partner agency field employees about the high sulfur content in ethanol by-products, which is different than brewer’s grain by-products. The ethanol production process normally includes the addition of significant amounts of sulfuric acid into the ethanol process for multiple purposes including chemistry, sanitation, pH control, and others, but leaving behind significant sulfur, which can cause unexpected H2S production with by-product reuse.

11. Pennsylvania NRCS has purchased 4 multi-gas meters for in-state training use. Meters measure 4 gases. The NRCS meters are intended for educational / awareness use and encouraging landowners / manure haulers to purchase for their own use.

Corresponding author, title, and affiliation

W. Hosea Latshaw, PE, USDA NRCS Pa State Conservation Engineer

Corresponding author email

hosea.latshaw@pa.usda.gov

Acknowledgements

Manure Gas Risks Associated with Gypsum Bedding at Dairy Farms, Final Project Report, USDA NRCS Conservation Innovation Grant, Pennsylvania State University, Project Manager: Eileen Fabian-Wheeler, December 2017

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. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

March 5, 2019March 19, 2019

Effectiveness of Livestock Exclusion in a Pasture of Central North Carolina

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*Do not make slides downloadable

Purpose

Jordan Lake (Reservoir), located in central North Carolina, is a 5,650-ha impoundment with a 436,860-ha watershed of which 18% was urban, 20% agricultural, and 56% forested. Like many lakes in the eastern U.S., the use of this water resource is being threatened by excessive nutrient inputs. A proposed nutrient reduction strategy set overall nitrogen (N) and phosphorus (P) load reduction goals for the watershed at 8-35% for N and 5% for P. Because much of the agricultural land in the watershed was used for pasture, the initial focus of reduction efforts was on pastures with livestock exclusion fencing identified as having the most potential. The objective of this project was to document the effectiveness of a combination of livestock exclusion fencing and nutrient management implemented on a beef cattle pasture typical of pastures in the Jordan Lake watershed and of the Piedmont region of NC.

What did we do?

figure 1a The paired watershed experimental approach used in this project, required simultaneous monitoring of two watersheds (treatment and control), during a calibration and a treatment period. The calibration period was from 12/30/07 to 10/5/11 and the treatment period was from 10/6/11 to 12/18/15. During both periods, the rainfall and quantity and quality of discharge were monitored continuously. Land use information (number of cattle, fertilization, soil test results) was collected at least annually. The treatment watershed (Past-treat) encompassed 54.5 ha all but 7.3 ha of which was used for beef cow pasture. The control watershed (Past-cont) encompassed 78.1 ha 39.5 ha of which was pasture, while most of the remainder (27.5 ha) was wooded.

In the treatment watershed the exclusion fenceline was constructed in October, 2011 about 3 m from the top of the streambank on either side and was limited to the main stream channel only (fig. 1b). Nutrient management was also implemented which eliminated P application as soil tests showed that there was adequate P in the soil to support the growth of pasture grasses such as fescue. In the control watershed, beef cattle had unlimited access to the stream channel during the entire project (fig. 1a). Monitoring included collecting flow-proportional samples during storm events and analyzing them for total Kjeldahl (TKN), ammonia (NH3-N), and inorganic (NOx-N) nitrogen as well as total phosphorus (TP) and total suspended solids (TSS).

What have we learned?

figure 1b Statistical analyses of storm event load data documented that during the post-fencing period, mass loading of TKN (34%), NH3-N (54%), TN (33%), TP (47%), and TSS (60%) was reduced significantly in the treatment relative to the control watershed, while storm discharge and NOx-N loads were not significantly different. These data showed that even a relatively narrow exclusion corridor implemented on only the main stream channel can significantly reduce the export of nitrogen, phosphorus, and sediment from a beef cattle pasture.

Future Plans

Evaluate livestock exclusion fencing at another Piedmont site with a wider exclusion corridor.

Corresponding author, title, and affiliation

Daniel Line, Extension Specialist at NC State University

Corresponding author email

dan_line@ncsu.edu

Other authors

Deanna Osmond, Professor, NC State University

Additional information

Published in J. Environmental Quality 45:1926-1932

Acknowledgements

This project received support from the National Institute of Food and Agriculture, U.S. Department of Agriculture, Integrated Water Quality Grant award 2011-0515 as well as funding from NCDEQ-DWR as pass-through funds from U.S. EPA 319.

March 5, 2019March 20, 2019

Innovative Business Models for On-farm Anaerobic Digestion in the U.S.

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Purpose

AgSTAR is a collaborative voluntary program of the Environmental Protection Agency (EPA) and United States Department of Agriculture (USDA). AgSTAR promotes the use of anaerobic digestion (AD) systems to advance economically and environmentally sound livestock manure management. AgSTAR has strong ties to industry, government, non-profit and university stakeholders and assists those who enable, purchase or implement anaerobic digesters by identifying project benefits, risks, options and opportunities.

Anaerobic digestion (AD) continues to be a sustainable manure management opportunity with growing interest in innovative business models for project development. AD systems provide a number of benefits, including improved nutrient management, locally sourced renewable energy, and diversified revenue streams for farmers. As energy prices remain low across the country, and interest grows in managing food waste and organics outside of landfills, new business models have been implemented to make these on-farm AD projects viable. This presentation will provide a national overview of the livestock AD sector, explore new AD projects across the U.S., and highlight successful projects with innovative business models.

The presentation will cover several case studies of AD projects on topics including:

Third-party ownership and development of projects;
Food waste collection and boosting project profitability through tip fees and increased biogas production;
Eco-market products from dairy manure fibers; manure-based alternatives to peat moss for the horticulture industry; and
Biogas to vehicle fuel; opportunities and financial considerations.

With only 244 operating on-farm AD projects across the U.S., there exists a great opportunity for market share growth at the approximately 8,000 farms that could support a project. This, coupled with the desire for alternative management of organic waste streams, provides a unique opportunity for this sector to grow in the near future.

Pigs in a field Cows in a field

Corresponding author, title, and affiliation

Nick Elger

Program Manager

AgSTAR & Global Methane Initiative

U.S. Environmental Protection Agency

1201 Constitution Ave NW, Mail code: 6207J

Washington, D.C. 20460

Phone: 202.343.9460

Email: elger.nicholas@epa.gov

https://www.epa.gov/agstar

https://www.globalmethane.org/

March 5, 2019March 20, 2019

Effects of pH on Urease Activity in Swine Urine and Urea Solution

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Purpose

A major source of pollution and loss of nutrient value from animal manure results from the conversion of urea nitrogen into ammonia by the naturally occurring urease enzyme in solid/liquid waste streams. Studies often focus on either urease inhibition in soil to prevent the volatilization of applied urea fertilizer or recovery of ammonia from wastewater, but few have studied urease inhibition in manure slurry directly from the barn. If the urea in fresh urine can be preserved at the source it would prevent the volatilization of ammonia that represents the loss of a valuable nutrient as well as the adverse effects of ammonia on livestock, humans and the environment. Our study investigated methods of inhibiting urease activity in fresh swine urine to preserve the urea nitrogen content during storage, processing and transport.

What did we do?

The study was comprised of 4 experiments:

1) Jack bean urease was introduced to a 1M aqueous urea solution and fresh swine urine. Samples were taken hourly for five hours and lab tested for total ammoniacal nitrogen (TAN) to compare urease activity of the urea solution with that of actual urine.

2) Using the same 1M urea solution, the effects of pH < 3.0 and pH > 12.0 on urease activity was measured relative to the commercially available inhibitors N-(n-butyl) thiophosphoric triamide (NBPT), salicylhydroxamic acid (SHAM), and Thymol (a phenol obtained from thyme oil or other volatile oils). Each treatment was sampled weekly for Total Kjeldahl Nitrogen (TKN), TAN and pH over six weeks to see which treatment best preserved urea nitrogen.

3) To determine if a smaller pH adjustment would be an effective inhibitor, we compared the activity of urease in a 1M urea solution across a pH range from 4.0 to 11.0. This was done by either lowering the pH of the urea solution with 0.1N sulfuric acid or raising it with 0.5N sodium hydroxide. The samples were tested at 7 days for pH, TKN and TAN.

4) Finally, we explored the effect of pH < 3.0 and pH > 12.0 on urease activity in swine urine to compare the effect with that in the urea solution. The initial pH, TKN and TAN of the swine urine was observed relative to the pH and concentrations of samples taken at 7 days and 14 days.

What have we learned?

Figure 1: A comparison of total ammoniacal nitrogen (TAN) concentrations indicates similar urease activity in swine urine and urea solution

1) The conversion of urea nitrogen to ammonia (as measured by TAN) follows a similar trend in both a urea solution and freshly collected sow urine (Figure 1). This indicates that a urea solution may be an acceptable alternative for testing urease inhibition when fresh urine is not available.

2) In a comparison of NBPT, Thymol, and SHAM to pH < 3.0 and pH > 12.0, it was observed that the high and low pH had the most significant inhibitory effect on urease enzyme activity, as almost none of the TKN in the samples observed over a 6-week study period was converted to TAN, relative to the other inhibitors tested (Figure 2).

Figure 2: Average increase of TAN from urease activity in urea solution using five different inhibitor treatments over a 6-week period

3) Testing a range of nominal pH values between 4.0 and 11.0 it was observed that while urease enzyme remained active over a 2 week period across all values, activity declined with an increase or decrease in pH from the highest activity observed at pH 7.0. However, at a pH below 3.0 the urease enzyme was completely denatured and could not be restored by increasing the pH.

4) When testing high and low pH on swine urine it was observed to have a similar inhibitory effect on urease activity compared with the urea solution, that the effect is lasting over 14 days, and that the high pH is slightly more effective than the low pH (Figure 3).

Figure 3: Analysis of urease activity as indicated by increase in TAN in swine urine at low and high pH. Results indicate urease inhibition treatment is most effective at pH 2.5 and ph > 12.0

Future Plans

A follow up study will be conducted using a pilot scale scraper separation system to collect fresh urine from about 30 swine through a 16 week growing cycle. We will be testing urea preservation using 3 different inhibitor treatments including pH > 12, pH < 3 and the commercial soil urease inhibitor, NBPT. We will also study the effect of UV light on urease activity during the control periods. The experiment will be repeated for each inhibitor over 3 feeding phases to simulate grower farm conditions.

Corresponding author, title, and affiliation

Alison Deviney, Graduate Research Assistant at Biological and Agricultural Engineering Department, North Carolina State University

Corresponding author email

avdevine@ncsu.edu

Other authors

John J. Classen, Ph.D. and Mark Rice, Extension Specialist at Biological and Agricultural Engineering Department, North Carolina State University

Additional information

Alison Deviney

Biological and Agricultural Engineering Department

North Carolina State University

Raleigh, NC 27695

Acknowledgements

Jason Shye and Dan Wegerif, Managing Members

Waste 2 Green, LLC, Cocoa, Florida, USA

March 5, 2019March 20, 2019

Evaluation of Greenhouse Gas Emissions from Dairy Manure

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Purpose

Greenhouse gas (GHG) emissions from dairy manure can be affected by barns, bedding and manure collection, as well as processing and storage. To reduce life cycle environmental impacts of milk production, it is important to understand the mechanisms involved in production and emission of GHGs from dairy manure. In addition to the GHGs emitted from the manure surface, the production of these gases in manure at different depths is an important but poorly understood driver of emissions. Because it is often not practical to measure GHG production and emissions directly in the field, simulation of these processes, both experimentally and through modeling, is needed to help understand the GHG emission mechanisms.Because manure samples are heterogeneous and their composition varies based on the bedding materials and bedding rate as well as cleaning frequency, it is also necessary to consider the impacts of these different types of manure heterogeneity and their impact on emission processes. Another important element that can impact GHGs emissions from dairy manure is oxygen. GHG emission rates can be different based on manure storage status (aerobic, anaerobic, and mixed conditions) and storage time. Several other factors, such as manure bedding materials, bedding rate, applied stress, temperature and moisture content can also impact the microbial activities that produces these GHGs. Our goals are to enhance understanding of the relationships between these factors and GHG emissions from dairy manure, and to identify strategies by which substantial reductions in GHG can be realized in a practical way.

What did we do?

In a controlled laboratory environment we investigated three different dairy manures: sand stacked manure, sawdust bedded manure, and organic sawdust bedded manure. The first two manures were studied and measured in 2016, and the last one was collected and measured in February 2017. After sample collection, manures were mixed in a cement blender to be more homogeneous, and were then transported to buckets and jars for compaction and storage. Nine buckets were filled with manure in layers, and each layer was characterized for physical and biochemical properties. Three levels of stress (0 N/m2, 4196 N/m2, and 12589 N/m2) were applied above the manure to emulate the impact of overburden at various pile depths. Manure bulk density and permeability for each bucket were measured, and the average of each treatment was summarized to evaluate relationships with GHG emissions. Four gases (NH3, CH4, CO2, and N2O) were investigated. The manure moisture content and water holding capacity were measured adjusted to create aerobic, anaerobic, and mixed conditions for manure microorganisms. Three moisture contents were applied to 300 g manure samples, each three replicates. Each manure storage condition was simulated in 2L glass vessels for five durations (one day, two weeks, one month, two month, and three months). The relationship between storage time and GHG rates was assessed.

Picture of cement blender Picture of buckets and manure compaction Picture of dairy manure storage after blending and compaction

What have we learned?

The results showed that there are good prospects that GHGs reductions can be realized in dairy manure management. In this work, manure that was characterized between each sample layer in the buckets showed similar results, which means the samples are pretty homogeneous. Bulk density and permeability decreased with increasing applied stress. GHG emissions and ammonia emissions showed correlation with the compaction density. Using different bedding materials did impact the GHGs rate.

Future Plans

The combination of prediction models (DNDC and IFSM) and real-word data will be discussed next.

Corresponding author, title, and affiliation

Fangle Chang, post-doctoral at Penn State University, State College PA

Corresponding author email

fuc120@psu.edu

Other authors

Micheal Hile, Eileen E. Fabian (Wheeler),

Additional information

Micheal Hile, mlh144@psu.edu

Eileen E. Fabian (Wheeler), Professor of Agricultural Engineering, Environmental Biophysics, Animal Welfare, and Agricultural Emissions, Integrated Research and Extension Programs, Penn State University, State College PA, fabian@psu.edu

Tom L. Richard, Professor of Agricultural and Biological Engineering, Director of Penn State Institutes for Energy and the Environment, Bioenergy and Bioresource Engineering, Penn State University, State College PA, tlr20@psu.edu

Acknowledgements

This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 2013-68002-20525. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture.

March 5, 2019March 19, 2019

Methane Mitigation Strategies for Dairy Herds

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Purpose

The U.S. dairy industry has committed to lowering the carbon footprint of milk production by 25% by 2020. A key factor in meeting this goal is reducing enteric greenhouse gas (GHG) emissions which represent about 51% of the carbon footprint of a gallon of milk. Methane (CH4) is the primary GHG emitted by dairy cows. Total methane emissions represented 10.6% of the total U.S. GHG emissions in 2014. Enteric CH4 emissions were 22.5% of the total methane emissions. Methane emissions from dairy cattle were 5.7% of total U.S. methane emissions or 0.6% of all U.S. GHG emissions. The purpose of this project was to examine nutrition and management options to lower methane emissions from dairy cattle.

What did we do?

This project utilized a number of approaches. One was to develop a base ration using the Cornell Net Carbohydrate and Protein System (CNCPS) model to evaluate the impact of level of dry matter intake and milk production on methane emissions. A second approach was to compile a database of commercial herd rations from 199 dairy farms. This database was used to examine relationships between the feeding program and CH4 emissions. A third component was to utilize published review papers to estimate potential on-farm CH4 reductions based on research data.

What have we learned?

A base ration developed in the CNCPS model was evaluated at milk production levels ranging from 40 to 120 pounds of milk. As milk production increased, CH4 emissions increased from 373 to 509 grams/cow/day. This is primarily due to increasing levels of dry matter intake as milk production increases. However, the CH4 emissions per pound of milk decreased from 9.32 to 4.24 g as milk production increased. The 199 commercial herd database had an average input milk of 83.7 pounds per day with a range from 50 to 128 pounds. Daily dry matter intake (DMI) averaged 51.4 pounds with a range of 35.2 to 69.8. Simple correlations were run between CH4 emissions and ration components. Dry matter intake had a positive (0.795) correlation with CH4 emissions (g/day). However, the correlation between DMI and CH4/pound of milk was -0.65. These results agree with published research on the relationship of DMI and CH4 emissions. Starch intake also had a positive correlation (0.328) while percent ration starch was negatively correlated (-0.27) with CH4 emissions. There was also a positive correlation (0.79) between the pounds of NDF intake and CH4 emissions.

A review paper indicated that the maximum potential reduction in CH4 emissions by altering rations was 15% (Knapp et. al., 2014). Projected reductions from genetic selection, rumen modifiers and other herd management practices were 18, 5 and 18% in this same paper. The reduction by combining all approaches was estimated to be 30%. A second review paper listed mitigation strategies as low, medium or high (Hristov et. al. 2013). Potential reductions for the low group was <10% while the medium group was 10-30%. The high group had >30% potential to lower CH4 emissions. Ionophores, grazing management and feed processing were in the low group. Improving forage quality, feeding additional grain and precision feeding were in the low to medium group. Rumen inhibitors were listed in the low to high group. No items were listed only in the high group. These results provide guidance in terms of items to concentrate on at the farm level to reduce methane emissions.

Future Plans

The number of commercial herds in the database will be expanded to increase the types of rations represented and the simple correlations run. In addition, a multiple regression approach will be used to better understand the relationships of ration components and CH4 emissions. Whole herd data will be obtained and examined to determine the proportion of the total herd CH4 emissions contributed by the various animal groups. The CNCPS program will also be used on rations at constant DMI to better understand the impact of specific ration components on CH4 emissions. These results of these will permit a more defined and targeted approach to adjusting rations to decrease CH4 emissions.

Corresponding author, title, and affiliation

Dr. Larry E. Chase, Professor Emeritus, Dept. of Animal Science, Cornell University

Corresponding author email

lec7@cornell.edu

Additional information

Hristov A.N., J. Oh, J.L. Firkins, J. Dijkstra, E. Kebreab, G. Waghorn, H.P.S. Makkar, A.T. Adesogan, W. Yang, C. Lee, P.J. Gerber, B. Henderson and J.M. Tricarico. 2013. Mitigation of methane and nitrous oxide emissions from animal operations: I. Review of enteric methane mitigation options. J. Anim. Sci. 91:5045-5069.

Knapp J.R., G.L. Laur, P.A. Vadas, W.P. Weiss an d J.M. Tricarico. 2014. Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions. J. Dairy Sci. 97:3231-3261.

Acknowledgements

This material is based upon work that is supported by the National Institute of Food and Agriculture U.S. Department of Agriculture under award number 2013-68002-20525. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author and do not necessarily reflect the view of the U.S. Department of Agriculture.

March 5, 2019February 24, 2020

Climate Change Mitigation and Adaptation in Dairy Production Systems of the Great Lakes

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Purpose

To better understand how dairy agriculture can reduce its impact on climate change, the USDA has supported a large, transdisciplinary research project to examine dairy production systems across the Great Lakes region of the United States. The goals of the Sustainable Dairy Coordinated Agricultural Project are to identify where in the life cycle of a dairy system can beneficial management practices (BMP) be applied to reduce greenhouse gases (GHG) without sacrificing productivity or profit to the farmer. Since 2013, a team of 70 researchers has been collaborating across institutions and disciplines to conduct the investigations.

What did we do?

Experimental data were collected at the cow, barn, manure, crop and soil levels from 2013-2016 by agricultural and life scientists. Modelers continue to conduct comparative analyses of process models at the animal, field and farm scales. Atmospheric scientists have down-scaled global climate models to the Great Lakes region and are integrating climate projections with process modeling results. The Life Cycle Assessment team is evaluating select beneficial management practices to identify where the greatest reduction of greenhouse gases (GHG) may occur. Results of focus groups and farmer surveys in Wisconsin and New York will help us understand how producers currently farm and what types of changes they may be willing to implement, not just to reduce emissions but to adapt to long-term changes in climate.

What have we learned?

Through the Dairy CAP grant, researchers have developed and refined the best ways to measure GHG emissions at the cow, barn, manure, crop and soil levels, and these data are archived through the USDA National Agricultural Library. Results show that the greatest levels of methane produced on a farm come from enteric emissions of the cow and changes in the diet, digestion and genetics of the cow can reduce those emissions. Another significant source of methane—manure production, storage and management—can be substantially reduced through manure management practices, particularly when it is processed through an anaerobic digester. Changes in timing of nitrogen application and use of cover crops practices are found to improve nitrogen efficiency and reduce losses from the field.

A comparative analysis of process models showed multiple differences in their ability to predict GHG emissions and nutrient flow (particularly nitrogen dynamics) at the animal, farm, and field scales. Field data collected were used to calibrate and refine several models. The Life Cycle Assessment approach shows that a combination of BMPs can reduce GHG emissions without sacrificing milk production. The application of down-scaled climate data for the Great Lakes region is being used in conjunction with the suite of BMPs to develop mitigation and adaptation scenarios for dairy farming in the Upper Midwest.

Research findings are shared through a series of fact sheets available on the project website, and a web-based, virtual farm that presents educational materials for 150- and 1500-cow operations to a variety of audiences, ranging from high school students to academics.

Future Plans

The Dairy CAP grant sunsets in 2018, but research questions remain relative to the efficacy of beneficial management practices at different stages in the life cycle of a farm. Challenges revolve around the complexity of farming practices, the individuality of each farm and how it is managed, and uncertainty associated with the predictive capabilities of models. Mitigation and adaptation strategies will be shared with the dairy industry, educators and extension partners who will be responsible for working with farmers at the field level. Implementation of these strategies will make dairy farming in the Great Lakes region more resilient.

Corresponding author, title, and affiliation

Carolyn Betz, Research Project Manager, University of Wisconsin-Madison. Department of Soil Science

Corresponding author email

cbetz@wisc.edu

Other authors

Matt Ruark and Molly Jahn

Additional information

http://www.sustainabledairy.org

http://virtualfarm.psu.edu

Acknowledgements

This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 2013-68002-20525.

March 5, 2019March 6, 2019

A Model Comparison of Daily N2O Flux with DayCent, DNDC, and EPIC

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Purpose

Process-based models are increasingly used as tools for studying complex agroecosystem interactions and N2O emissions from agricultural fields. The widespread use of these models to conduct research and inform policy benefits from periodic model comparisons that assess the state of agroecosystem modeling and indicate areas for model improvement. The increasingly broad application of models requires an assessment of model performance using datasets that span multiple biogeophysical contexts. While limited in the capacity to identify specific areas for model improvement, general evaluations provide a critical perspective on the use of model estimates to inform policy and also identify necessary model improvements that require further evaluation.

What did we do?

The objectives of this model comparison were to i) calibrate and validate three process-based models using a large dataset; ii) evaluate the performance of a multi-model ensemble to estimate observed data; and iii) construct a linear model to identify and quantify possible model bias in the estimation of soil N2O flux from agricultural fields. We selected three models that have been used to evaluate N2O emissions from agricultural fields: DayCent, DNDC, and EPIC. Using data from two field experiments over five years, we calibrated and validated each model using observations of soil temperature (n = 887), volumetric soil water content (VSWC) (n = 880), crop yield (n = 67), and soil N2O flux (n = 896). Our model validations and comparisons consisted of commonly conducted statistical evaluations of root mean squared error, correlation, and model efficiency. Additionally, the large sample sizes used here allowed for more robust linear regression models that offered additional insight into relationships between model estimations and observations of N2O flux. We hypothesized that such a linear model would indicate if there was model bias in estimations of soil N2O flux. Ensemble modeling can reduce the error associated with climate projections and has recently been applied to the estimation of N2O flux from agroecosystems. Thus, we also constructed a multi-model ensemble to evaluate the use of multiple models to improve estimates of soil N2O flux.

What have we learned?

In a comparison of three process-based models, calibration to a large dataset produced favorable estimations of soil temperature, VSWC, average yield, and N2O flux when the models were evaluated using RMSE, R2, and the Nash-Sutcliffe E-statistic. However, an evaluation of linear regression models revealed a consistent bias towards underestimating high-magnitude daily N2O flux and cumulative N2O flux. Observations of soil temperature and VSWC were unable to significantly explain model bias. Calibration to available data did not result in consistent model estimation of additional system properties that contribute to N2O flux, which suggests a need for additional model comparisons that make use of a wide variety of data types. The major contribution of this work has been to identify a potential model bias and future steps required to evaluate its source and improve the simulation of nitrogen cycling in agroecosystems. Process-based models are powerful tools, and it is not our objective to undermine their past and future application. However, more work is left to be done in understanding the biogeophysical system that produces soil N2O and in harmonizing the process-based models that simulate that system and which are used to evaluate management and generate policy.

Future Plans

Future work should test our findings in additional agroecological contexts to determine the extent to which a bias towards underestimating peak N2O flux persists. A meta-analysis of published data may be the most direct method for doing so. New datasets will need to be collected that represent simultaneous observations of multiple system properties (e.g. soil NO3-, soil NH4+, and heterotrophic respiration) from different soil layers and at increased temporal frequencies. Model developers should use these rich datasets to identify the source of N2O estimation bias and improve the structure and function of process-based models.

Corresponding author, title, and affiliation

Richard K. Gaillard, Graduate Student, University of Wisconsin-Madison

Corresponding author email

rgaillard@wisc.edu

Other authors

Curtis D. Jones, Assistant Research Professor, University of Maryland; Pete Ingraham, Research Scientist, Applied Geosolutions;

Additional information

sustainabledairy.org

Acknowledgements

Additional Authors:

Sarah Collier, Research Associate, University of Wisconsin-Madison;

Roberto Cesar Izaurralde, Research Professor, University of Maryland;

William Jokela, Research Scientist (retired), USDA-ARS;

William Osterholz, Research Associate, University of Wisconsin-Madison;

William Salas, President and Chief Scientist, Applied Geosolutions;

Peter Vadas, Research Scientist, USDA-ARS;

Matthew Ruark; Associate Professor; University of Wisconsin-Madison

March 5, 2019July 13, 2020

Replacing Commercial Sidedress Nitrogen with Liquid Livestock Manure on Emerged Corn

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Purpose

Livestock producers can more fully utilize the nutrients in livestock manure to reduce purchased fertilizer costs if they can apply manure when crops need the nutrients. Better capturing manure nutrients can reduce phosphorus and nitrogen losses into surface water bodies. To help decrease the incidences of harmful algae blooms in the Western Basin of Lake Erie, Ohio State University (OSU) Extension research has sought to develop an in-season window to apply manure to emerged corn. By incorporating livestock manure as a sidedress nitrogen fertilizer for corn, nutrients are less exposed to movement by water and a greater percent of the nitrogen is utilized by the growing corn crop.

Surveys of livestock farmers, who attended OSU Extension field days in western Ohio reveal approximately 49% of livestock manure is applied in the months of October, November, and December following crop harvest. Typically, there is no growing crop at that time of year to capture the available nitrogen in the manure. The surveys also reveal only 19% of manure is applied in the months of April, May and June. Ohio has about 2.5 billion gallons of liquid dairy manure and almost one billion gallons of liquid swine manure needing applied to farm fields each year.

What did we do?

Ohio State University conducted replicated small-plot research from 2012 to 2016 using swine and dairy manure as sidedress nitrogen sources compared to incorporated 28% Urea Ammonium Nitrate (UAN) on pre-emergent and post-emergent corn. The nitrogen in manure is primarily in two forms; ammonium and organic. Ammonium nitrogen is readily available to a growing crop. Organic nitrogen has to undergo a mineralization process for a percentage of the nitrogen to eventually be released in the ammonium form each crop season.

More than 45 on-farm plots with livestock producers were also completed over five seasons using field sized replicated plots. Liquid swine, dairy, and beef manure were applied to corn in the V2 to V4 stage of growth using a 5,250 gallon Balzer tanker and six-row Dietrich manure injection toolbar. The flotation tires on the tanker were replaced with rims and narrow tires allowing the tanker to follow the tractor down the rows of corn. In replicated plots, the liquid manures produced similar yields to commercial fertilizer when applied at similar nitrogen fertilizer amounts.

OSU Extension also conducted swine finishing manure drag hose plots with a pork producer where manure was incorporated into emerged corn at the V2 to V3 stage of growth and compared to incorporated 28%UAN. The manure application rate was approximately 6,500 gallons per acre using a seven-shank rotary injector toolbar. The drag hose was six inches in diameter and the pumping rate was 1,300 gallons per minute. The farmer planted the fields on a 45 degree angle to accommodate the drag hose manure application.

What have we learned?

Below are five years of liquid manure side-dress research on corn plots at the Northwest Station of the Ohio Agricultural Research and Development Center. In these research plots liquid swine and liquid dairy manure were used in pre-emergent and post-emergent plots and compared with incorporated 28%UAN. Manure was applied to the pre-emergent plots each season within three days of planting. Manure was applied to the post-emergent plots at the V3 stage of corn growth. The manure was applied to a depth of approximately five inches using a 1,250 gallon manure tanker with Dietrich manure injection sweeps and covering wheels.

For these plots, the swine finishing manure application rate was 5,000 gallons per acre to provide 200 pounds of available nitrogen. The dairy pond manure application rate was 13,500 gallons per acre (140 pounds of available nitrogen) plus 20 gallons of 28% UAN nitrogen applied just ahead of the manure for a total of 200 pounds of nitrogen. The 28%UAN treatments also received 200 pounds of nitrogen per acre each year.

Chart 1. OARDC manure side-dress plot results

2012-2016 OARDC Manure Sidedress Yields; bushels per acre

The long-range goal of Ohio State University Extension’s manure application research is to utilize a drag hose to incorporate liquid manure of any species into corn from the date of planting up to the V4 stage of growth. Three years of drag hose manure side-dress plots in Darke County indicate this manure application method has great potential. Applying manure to a growing crop can capture more of the manure nutrients than applying manure without a crop in the field.

Chart 2. Drag hose research yields on corn in Darke County, Ohio

Year	Swine manure (bu/acre)	28%UAN (bu/acre)
2016	222	216
2015	154	121
2014	204	204

In addition to the three crop seasons of drag hose sidedress of corn in Darke County, we also have three years of drag hose damage research from the Ohio Agricultural Research and Development Center’s Northwest Station near Hoytville. Based on this research, we believe we can use a drag hose across emerged corn through the V3 stage without a loss of yield and probably through the V4 stage if early season conditions are drier than normal.

Chart 3. 2014-2016 OARDC drag hose damage yield losses in corn

Corn growth stage	Plant population 2014	Yield bu/acre 2014	Plant population 2015	Yield bu/acre 2015	Plant population 2016	Yield bu/acre 2016	3-year population average	3-year average bu/acre
No drag hose	30,166	145.1	31,850	167.2	28,625	145.1	30,214	152.5
V1	29,660	154.3	31,750	166.1	28,625	149.5	30,012	155.4
V2	30,166	157.9	32,000	165.3	28,500	141.2	30,222	154.8
V3	28,933	153.9	31,375	172.3	29,250	144.4	29,853	156.9
V4	29,264	149.7	23,500	123.5	27,500	152.1	26,755	141.8
V5	15,366	109.8	——-	——	16,000	126.3	15,683*	118.0*

*Indicates only two years of data

Future Plans

Funds are being solicited to purchase 12-row drag hose manure incorporation toolbars to have available to livestock producers and commercial manure applicators to use in Ohio for the 2017 crop season and beyond. Thanks to donations from the Columbus Foundation, Ohio Farm Bureau, Dietrich Inc., Cooper Farms, Hord Livestock, Conservation Action Project, and Bazooka Inc. we have almost secured the funds to build two toolbars.

Corresponding author, title, and affiliation

Glen Arnold, Associate Professor & Field Specialist Manure Nutrient Management Application, The Ohio State University

Corresponding author email

Arnold.2@osu.edu

Other authors

Eric Richer, Sam Custer, Sarah Noggle, Jeff Stachler, Jason Hartschuh, Amanda Douridas

Additional information

Additional on-farm manure plot research results are available at www.agcrops.edu

YouTubes of OSU Extension manure application to emerged corn can be found at: https://www.youtube.com/channel/UC7jUsQNGM8fCHjbZUdT9pKw

Acknowledgements

Thanks to the Ohio Environmental Education Fund, Ohio Pork Producers Council, Ohio Dairy Research Fund, Ohio Corn Marketing Board, Ag Credit, Farm Credit Services, Ohio Soybean Council, the Ohio Farm Bureau, and the Conservation Tillage Conference for funding support.

March 5, 2019May 7, 2019

Review of Odor Management Planning Templates and Calculators Across the US

Proceedings Home | W2W Home

Purpose

Odor is a common and prevalent problem for new and existing livestock operations, and odor is often a source of conflict between neighbors. Odor cannot be removed in entirety from livestock production, but it can be managed. A few states have developed odor management plan guidelines or templates that may be mandatory, or voluntarily for the sake of good stewardship. Our long term goal is to construct an odor management plan template for South Dakota and beyond, and improve producer-neighbor relationships. Towards this goal, we present a review of established tools, templates and odor impact calculators that are in use in the United States.

What did we do?

We sent a questionnaire to four odor management plan (OMP) developers in Minnesota, Michigan, Nebraska and Pennsylvania. The questionnaire asked questions about the development process, users, marketing, and evaluation of odor management planning guides. We compared and contrasted the responses and identified opportunities to build on these past experiences elsewhere. Similarly, based on existing literature and online tools, four odor impact estimation calculators, or footprint tools were reviewed. These include the South Dakota Odor Footprint Tool, Odor From Feedlots Setback Emissions Tool (Minnesota), Odor Footprint Tool (Nebraska), and Purdue Odor Setback Model (Indiana).

What have we learned?

From the questionnaire it was clear that though an odor management plan is not a mandatory requirement in most of the states surveyed, the developers produced these guides for the betterment of the livestock industry of their state. During development of the OMPs, there was little exchange between producers, neighbors or policy makers collectively. Also, the use, evaluation and impact of the OMP templates was not tracked. There was not extensive marketing for the odor management plan guides aside from extension news updates and some presentations.

The pattern or format of the OMPs from the four different states was similar. Documentation of odor sources and record keeping of odor complaints was encouraged in all with a tabulated form. Michigan’s was the only guide to suggest quantitative estimation of odor impact, even though there are some nice and effective tools available to make these calculations for most states and regions. Odor monitoring was suggested in two states and one state suggested third party monitoring keep the assessment unbiased. Table 1 presents an overall review of questionnaire findings for the four states surveyed.

Table 1. Summary of responses for select questions posed to developers of odor management planning (OMP) templates or guides

All four odor footprint tools were compared based on the odor emission estimates and dispersion model incorporation. Two of the tools considered terrain factors in odor dispersion calculations. Additional comparisons are shown in Table 2.

Table 2. Comparison of odor setback/odor footprint estimation tools

Future Plans

Building off of the feedback from OMP developers in other states, we plan to engage multiple interest groups in identifying the scope, use and dissemination of an OMP developed for South Dakota. There will be an emphasis on conflict resolution in the event of odor complaints so that odor complaints can be resolved locally (between neighbors) as much as possible.

Corresponding author, title, and affiliation

Suraiya Akter, Graduate Research Assistant, Agricultural and Biosystems Engineering, South Dakota State University

Corresponding author email

suraiya.akter@sdstate.edu

Other authors

Erin Cortus, Associate Professor and Environmental Quality Engineer, Agricultural and Biosystems Engineering, South Dakota State University

Additional information

erin.cortus@sdstate.edu

Acknowledgements

We would like to thank Dr. Jerry May (MSU), Mr. David Schmidt (UMN), Mr. Karl Dymond (Pennsylvania State), Dr. Richard Koelsh (UNL) for their kind response to the questionnaire.