Final Report for SW99-024B

SW99-024B (project overview)

Project Type: Research and Education

Funds awarded in 1999: $19,184.00

Projected End Date: 12/31/1999

Region: Western

State: Utah

Principal Investigator:

RIchard Kohn

Expand All Collapse All

Project Information

Summary:

Software had been previously developed to quantify nitrogen and phosphorus balances on livestock farms in Maryland, and was beta tested in the western region. This software was distributed via the internet to users in 25 states and 27 countries. Our lab assisted with development of two papers on use of the software to characterize nutrient balances in the western region of the US. Our lab also tested the use of MUN on dairy farms in Maryland. We updated comprehensive web pages that disseminate information on reducing nutrient losses from agriculture, especially dairy fms.

Project Objectives:

The objectives of the overall project are as follows: 1) to verify the usefulness of milk urea nitrogen (MUN) analysis for accurately predicting aspects of N metabolism, 2) to detennine the potential use of herd MUN averages and recently developed computer worksheets for predicting N losses and whole-farm efficiencies on commercial dairies in UT and ID, and 3) to disseminate all results to dairy producers, extension personnel and scientists via extension publications, the World Wide Web, and peer-reviewed journal articles. Our contribution to the overall project is based on the following specific objectives: 1) to improve computer worksheets for calculating whole fmba lances by adapting them to the western region and by implementing changes identified by using the worksheets in this region, 2) to assist with evaluation and improvement in MUN analysis based on research conducted at Utah State University, and 3) to disseminate information from this project to fmers via extension publications and the World Wide Web.

Introduction:

In a nutritional program on a farm, milk urea nitrogen (MUN) can be an important tool for determining adequacy of protein feeding. A herd with high MUN results when cows are fed more protein than needed for milk production, growth, and pregnancy. A herd with low MUN indicates that protein is being utilized very efficiently, but there is a potential for underfeeding of protein. Unfortunately high MUN levels do not indicate why protein is not being used efficiently. Elevated MUN levels can occur because of an improperly balanced ration, inaccurate forage analysis, incorrectly predicted milk production, or a host of other reasons. By systematically looking at potential causes of high MUN levels, the cause can be isolated and a remedy provided. So the next logical question about MUN concerns the level at which MUN is considered high or low.

Research

Materials and methods:

Prior to this grant, our lab developed a software application to calculate phosphorus and nitrogen flows on livestock farms. In the first year, the software was tested in the western region of the US and refined. In the second year, the software was implemented to assist farmers with calculating nutrient balances, and to collect data from farms. In the final year, we collected and summarized data to improve our understanding of current practices affecting nutrient flows so as to improve incentive, regulatory or technology transfer programs. Experiments were conducted at Utah State University to verify a model we developed that uses milk urea nitrogen and other variables to predict aspects of nitrogen utilization efficiency by dairy cows. We conducted a series of investigations at the University of Maryland to better understand the differences. Using retrospective analysis of previous experiments conducted at the University of Maryland, we compared milk urea nitrogen results reported before and after a change was made in the way standards were used. We also compared 14 DHIA laboratories across the US by sending similar milk samples to all labs and noting the results reported.

Research results and discussion:

As a result of Beta testing, software used in this project was improved to make it more flexible to more regions of the U.S. For example, greater flexibility was added so that now up to 100 imported feeds can be entered, several manure storage facilities can be used on the same farm, 30 different crops can be entered, 50 fields can be defined, etc. In addition, the Save Farm and New Farm commands were updated to prompt for saving previous data before clearing. Several other small changes were made. We continued to interact with the western state users of the software to help with identifying appropriate use, and to continue improving the software. Experiments were conducted at Utah State University to verify a model we developed that uses milk urea nitrogen (MUN) and other variables to predict aspects of nitrogen utilization efficiency by dairy cows. While most of the equations were shown to be accurate under different conditions, the prediction of urinary nitrogen excretion as a function of MUN differed from the original model. We conducted a series of investigations at the University of Maryland to better understand the differences. First, milk samples were collected on 10 different farms in Maryland and sent to 14 Dairy Herd Improvement Association Laboratories across the U.S. including the lab that had been used in Maryland and the one used in Utah. Important differences were noted among laboratories that use a certain method of MUN analysis but the labs used by Maryland and Utah were not different. An abstract on this research will be published in the Journal of Dairy Science Supplement and a presentation will be made this summer. A journal article has been submitted to the Journal of Dairy Science and extension publications will be developed once this article is accepted. The inaccuracy of the model we developed was later demonstrated at Ohio State University. Thus, a second set of experiments were conducted at the University of Maryland to attempt again to identify the difference in prediction of urinary N between Utah and Ohio versus Maryland. Two feeding trials with lactating cows had been conducted at the University of Maryland. The first trial occurred in the spring of 1998 (prior to the Utah and Ohio experiments), and the second trial occurred in the spring of 1999 (at the same time as the other experiments). The original model was evaluated against these two sets of data. When evaluated against the first data set, the model was accurate. But when evaluated against the later data sets the model underestimated urinary N. Further investigation revealed that the laboratories had changed methods of developing standards for MUN analysis, which changed the reported results by 4 units. This change had not been quantified. In addition, we further improved the model for use in a variety of locations. The model was shown to be more accurate after adding a term that corrects for differences in body weight among animals. These results were submitted as an abstract and will be presented this summer and published as a separate article.

Research conclusions:

Dairy farmers can use MUN to fine tune diets and prevent overfeeding or underfeeding of protein to their cows. The work we conducted will make it possible for farmers to use this technology more effectively. If they reduce overfeeding of cows, it will reduce their cost of feed because protein is an expensive ingredient. In addition, cows use energy to excrete the excess nitrogen. Thus, by not overfeeding, energy costs or lost production can be reduced. In addition, with less protein being fed, less N will be excreted in manure. This effect will make it easier to comply with field-by-field nutrient management plans. Many farmers in the west export their manure to the nearest available land. By reducing N in manure, the distance the manure must be shipped is reduced. Finally, reducing N excreted to manure will reduce ammonia-N volatilization, N runoff, and N leaching proportionally. The software for calculating nutrient balances can be used to help farmers and consultants understand the balance of nutrients on their farm and to quantify the unaccounted for N and P. These unaccounted for nutrients may accumulate in soils or be lost to the environment.

Participation Summary

Research Outcomes

No research outcomes

Education and Outreach

Participation Summary:

Education and outreach methods and analyses:

Refereed Articles: Jonker J. S. and R. A. Kohn. 2002. Using milk urea nitrogen to evaluate diet formulation and environmental impact on dairy farms. In: Optimizing Nitrogen Management in Food and Energy Production and Environmental Protection: Proceedings of the 2nd International Nitrogen Conference on Science and Policy, The Scientific World 1:852-859. Kohn, R. A., K. E. Kalscheur, and E. Russek-Cohen. 2002. A comparison of models to measure milk urea and urinary N excretion. J. Dairy Sci. 85:227-234. Jonker, J. S., R. A. Kohn, and J. High. 2002. Dairy herd management practices that impact nitrogen utilization efficiency. J. Dairy Sci. Jonker, J. S., R. A. Kohn, and J. High. 2002. Use of milk urea nitrogen to improve dairy cow diets. J. Dairy Sci. 85:939-946. Abstracts: Jonker, J. S., R. A. Kohn, J. High, and A. Grove. 2000. A pilot project to introduce the routine use of milk urea N analysis for diet evaluation. J. Dairy Sci. Suppl. 83. Swain, R. A., J. L. Walters, R. A. Kohn, and A. J. Young. 2001. Whole-farm nitrogen eficency and balance compared with the milk urea nitrogen test. J. Dairy Sci. Suppl. 84: 271. Presentations: Kohn, R. A. 1999. Opportunities to reduce nutrient losses from animal agriculture. Colloquium: Large Scale Animal Production and Human Health. Johns Hopkins School of Hygiene and Public Health, May 25, Baltimore. Kohn, R. A. 1999. The impact of new technology in dairy cattle management and feeding on reducing nutrient losses to water resources. Department of Dairy and Animal Science Seminar, The Pennsylvania State University, November 3, 1999, State College, PA. Kohn, R.A. 1999. Improving nutrient utilization within the animal and its effect on nutrient losses from a farm. Ohio Composting and Manure Management Program, November 16, 1999, The Ohio State University, Columbus. Kohn, R. A. 1999. Shategies for whole farm nutritional modeling. Purina Mills Dairy Unit Seminar, Puina Mills Inc., St. Louis, MO, Dec. 16, 1999. Kohn, R. A. 2000. Current research in nutritional management. Dairy Environmental Summit. Consolidated Nutrition, Decatur, IL, Nov. 8,2000. Kohn, R. A. 2000. Integrated nutrient management. Dairy Environmental Summit. Consolidated Nutrition, Decatur, IL, Nov. 8, 2000. Kohn, R. A. 2000. Determining the efficiency of nitrogen utilization on dairy farms Nutrition Seminar, Dept. of Animal Science, Virginia Tech, Blacksburg, VA. Extension Articles: Jonker, J.S. and R.A. Kohn. 1998. MUN testing: useful but ambiguous. Hoard's Dairyman, Mar. 25, p. 252. Jonker, J. S. and R.A. Kohn. 1998. Measure MUN and evaluate dairy cow nutrition. Dairy, Food and Environmental Sanitation: a Publication of the International Association of Milk, Food and Environmental Sanitarians. vol. 18, p. 89. Kohn, R. A. 1999. Improving animal efficiency. Dairy Online Connection, Sep., Monsanto Inc. Kohn, R. A. 1999. The impact of herd management on nutrient losses to water resources. Dairy Online Connection, Sep, Monsanto Inc. Kohn, R. A. 1999. Using milk urea nitrogen to evaluate dairy cow nutrition. Michigan DHIA Annual Performance Summary 1999. p 26. Kohn, R. A. 2000. Caution needed when interpreting MUNs. Hoard's Dairyman, Jan. 25, p. 58. Kohn, R. A. 2002. Research helps refine use of milk urea nitrogen. Hoard's Dairyman, August 10, p. 530. Kohn, R. A. 2001. Nitrogen: the other nutrient. Maryland Dairy Talk vol. 4 (3) pp 1-3. Kohn, R A. 1999. Nutrient management update. Maryland Dairy Talk vol. 2 (2), pp. 4- 5, Maryland Cooperative Extension, College Park. Kohn, RA. 1999. Pilot project saves farmers money. Maryland Dairy Talk vol. 2 (3), pp. 4-5, Maryland Cooperative Extension, College Park.

Education and Outreach Outcomes

Recommendations for education and outreach:

Areas needing additional study

Nutrient balance is an important tool to reduce nutrient losses from dairy farms. Greater emphasis is now being placed on air emissions fiom animal agriculture, as well as water emissions. Improving nitrogen balance will play an even greater role considering the potential loss of nitrogen from farms as volatilized ammonia.

Return to Project Overview

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and should not be construed to represent any official USDA or U.S. Government determination or policy.