Introducing ManureDB: A new way to view manure variability and trends

Figure 1. Screenshot of ManureDB website home page.

By: Nancy Bohl Bormann, Graduate research assistant

Manure is used as an organic fertilizer source on approximately 31 million United States (U.S.) acres, equating to 10% of US cultivated land the Conservation Effects Assessment Project (CEAP) II survey of practices from 2013-2016 estimates (USDA NRCS, 2022). Manure book values, approximate nutrient concentrations, are used for developing manure management plans, designing manure storages, creating best management practices for manure land application, and agricultural modeling. They show a range of nutrient values that can be expected from typical manure storages and encourage farmers to test their manure often. However, current book values are several decades old and may not reflect current production practices. Recent laboratory data from the Midwest indicated manure nutrient data has changed compared to published Midwest Plan Service (MWPS) book values (Bohl Bormann, 2022; Lorimor et al., 2004). Different animal diets, treatments, genetics, housing, and manure storage and handling practices can impact these manure nutrient values.

Researchers at the University of Minnesota received Agriculture and Food Research Initiative (AFRI) National Institute of Food and Agriculture (NIFA) grant funding in 2020 to create a manure nutrient database called ManureDB using FAIR principles (Findable, Accessible, Interoperable, and Reusable) in collaboration with the Minnesota Supercomputing Institute. This project partners with laboratories and universities that analyze manure for business and/or research. A project team comprised of commercial manure laboratories, livestock commodity groups, regulatory and agency staff, agriculture professionals, researchers, engineers, and alternative energy groups guides the development process.

This project highly values data privacy. A data use agreement gets signed between the participating laboratory and the University of Minnesota. Laboratories can share past manure data and annual data going forward with no customer names or addresses shared to avoid privacy concerns. Only the state or first three digits of a ZIP code are entered into the database. The ZIP codes and laboratory identities will not be included in the public-facing database. At least five samples per year from a state or region will be needed to show up in public summaries.

As one can imagine, all the laboratories report their results in many ways and producing a standardized template was a high priority. The database only requires the year the sample was analyzed but offers many other reporting options and sample notes. A manure type, animal or other amendment type, manure treatment, if agitated, bedding type, storage type, length of storage, and application method options can be selected if known. The template offers a wide selection of analyte options from macronutrients, micronutrients, and other metals and ratios. For each analyte reported the analytical method, units reported, and wet or dry basis is selected. The project based the analytical method selections off of the recently updated Recommended Methods of Manure Analysis (Wilson et al., 2022), the AgGateway Modus Agricultural Lab Test Data Standard (AgGateway, 2023), and interviews with laboratories. A spreadsheet validation step ensures the data conforms to the template parameters prior to uploading to the database. Once uploaded, each sample is given a unique ManureDB identifier and conversion equations are used to display data in consistent units.

The public facing ManureDB database launched in summer 2023 at ManureDB.umn.edu and recently released a data download feature in January 2024. See Figure 1 for a screenshot of the homepage. New features and improvements continue to roll out. Sign up for the email list at z.umn.edu/ManureDB-signup to be notified of updates. The database interface offers data aggregation with preliminary filters and provides some overview statistics. As of February 2024, ManureDB includes >490,000 samples from 49 states, 14 laboratories, over 65 animal types, and 18 organic amendments. With other data use agreements signed and some pending, the database will continue to grow with additional datasets and annual data additions from participating laboratories. The team continues to refine and build features in ManureDB, with plans to add data visualization displays, make the website mobile-friendly, and streamline the annual data update process. Eventually a log-in feature is planned for laboratories to view their lab-specific data relative to the aggregated database. The team plans to archive data on an annual basis in the USDA National Agricultural Library’s Ag Data Commons. We continue to seek out laboratory, university, and consultant data collaborators; if interested in learning more, please email manure@umn.edu.

What are the steps to submit data in ManureDB?

1. Contact manure@umn.edu or one of the project leaders
2. We can set up an initial meeting to learn more about the manure database project and your laboratory
3. Send out the data use agreement for signatures
4. Once signed by the lab, University of Minnesota will sign and return the fully executed agreement
5. We can meet again to review the lab’s methods, analytes, column names if needed
6. Send a spreadsheet of your lab’s data, as far back as you wish to go
7. We work through the spreadsheet validation process and may have a few questions for the lab as we go
8. Import into ManureDB!

While this manure database resource will give better manure nutrient estimates, the wide variability should also encourage farmers to test their manure more frequently. Tight margins make utilizing manure nutrients where they get the most value economically important. Having a better idea and confidence in manure’s nutrient value will ensure crops get the required amount of nutrients for full economic optimum yield potential. That knowledge should reduce manure overapplication, which would lessen the environmental risk of nutrient loss. If plants cannot use all the nutrients applied, there is a greater probability of environmental contamination.

With many states working on nutrient reduction strategies for water quality improvements, knowing more about manure characteristics can improve those strategic plans. Animal feeding operation regulations could be improved with updated manure book values by having better estimates of how much land would be required for new animal feeding operation construction. A new barn location could be compared to available land for manure application to prevent manure overapplication in a specific area. Knowledge of what are appropriate manure application rates for agronomic and environmental reasons can assist environmental regulators in farmer education and relevant nutrient management policy for their region. This database can also show improved estimates of other less studied manure components such as carbon and chloride. Regional comparisons between animal types (Table 1), comparisons between different manure types (Table 2), and manure trends over time (Table 3) are some examples of what can be done with this new data resource. With the largest manure dataset of its kind, this manure database is poised to be a valuable resource for understanding manure trends and variability into the future.

Table 1. Comparison of nutrient contents in poultry samples between regions from 1998-2023. 

Table 2. Nutrient comparisons between dairy manure types from 1998-2022. 

Table 3. Liquid manure P₂O₅ medians for samples labeled swine-finisher in the Midwest Region of IA, IL, IN, MI, MN, MO, OH, and WI from 2001-2023. 

This article first appeared in the November 2023 issue of the Journal of Nutrient Management and has been republished here with permission.

Additional resources:

• Video: Presentation on best practices for manure sampling & ManureDB update - February 2024 Nutrient Management Conference
• UMN Manure YouTube channel

Acknowledgments

I would like to recognize the Minnesota ManureDB team of Melissa Wilson, Associate Professor, Erin Cortus, Associate Professor and Extension Engineer, Kevin Janni, Extension Engineer (retired), and Kevin Silverstein, Scientific Lead Informatics Analyst, all from the University of Minnesota, and Larry Gunderson, Pesticide & Fertilizer Management, Minnesota Department of Agriculture, along with the ManureDB Stakeholder Committee and participating laboratories. This work is supported by the AFRI Foundational and Applied Science Program [grant no. 2020-67021-32465] from the USDA National Institute of Food and Agriculture, the University of Minnesota College of Food, Agricultural and Natural Resource Sciences, Minnesota Supercomputing Institute, and the Hueg-Harrison Fellowship.

References

AgGateway. (2023). Modus Agricultural Lab Test Data Standard. Modus Agricultural Lab Test Data Standard. https://aggateway.atlassian.net/wiki/spaces/MOD/overview

Bohl Bormann, N., & Other. (2022). How is manure changing over time? Trends in Midwest manure sample data. https://blog-crop-news.extension.umn.edu/2022/07/how-is-manure-changing-over-time-trends.html

Lorimor, J., Powers, W., & Sutton, A. (2004). Manure Characteristics. MidWest Plan Service, Iowa State University, Ames, IA.

USDA NRCS. (2022). Conservation Practices on Cultivated Cropland A Comparison of CEAP I and CEAP II Survey Data and Modeling. Conservation Effects Assessment Project. https://nrcs.usda.gov/sites/default/files/2022-09/CEAP-Croplands-ConservationPracticesonCultivatedCroplands-Report-March2022.pdf

Wilson, M. L., Cortus, S., Brimmer, R., Floren, J., Gunderson, L., Hicks, K., Hoerner, T., Lessl, J., Meinen, R. J., Miller, R. O., Mowrer, J., Porter, J., Spargo, J. T., Thayer, B., & Vocasek, F. (2022). Recommended Methods of Manure Analysis, Second Edition. University of Minnesota Libraries Publishing. http://conservancy.umn.edu/handle/11299/227650

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