Final Report for SW99-024B
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.
- 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.
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.
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
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.
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.
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.
Educational & Outreach Activities
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
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.
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:
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,
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.
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.,
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.
Participants in a recent cooperative extension project introducing use of milk urea
nieogen to fine tune dairy diets were able to reduce feed costs by an average of $6.00 per
cow per year by using information on bulk-tank MUN analysis once per month. There
were 450 participating farms averaging 108 cows per farm for a total impact of $292,000
We have introduced the use of MUN to over 450 farmers in Maryland, Pennsylvania,
Virginia, West Virginia and Delaware through a project in which we paid for sampling
and sent interpretive results. Participants in the project decreased MUN by 0.5 mg/dl
compared to non-participants. Participants with high MUN decreased MUN by 1 mg/dl
compared to non-participants, and participants with low MUN increased it by 3 mg/dl
compared to non-participants. Thus, it appears that participants in the program increased
or decreased protein feeding when recommended. The typical farm would have saved
$595 per annum in feed costs by reducing protein feeding.
Of 454 participants in the MUN study, 190 returned surveys about their participation, and
70% of these respondents reported using results from the program. Thirty percent
indicated that they planned to use MUN analysis again. While most farmers were unsure
of the economic impact the program had, several reported positive returns up to $1,500
from the program due to reduced feeding costs.
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.