Final Report for LNC03-237
Project Information
Data needed to estimate dry matter intake and manure production on seven Wisconsin dairy farms practicing Management Intensive Rotational Grazing (MIRG) was collected in the summers of 2003 through 2005. Three methods were used to estimate dry matter intake, clipping, a pasture plate, pasture height or energy balance. The energy balance method proved to be the most accurate Dry matter intake based on this method were 20.9, 20.5 and 20.0 lbs/cow/day for 2003, 2004 and 2005 respectively. Milk production averaged 51 lbs/cow/day. Feces production average of 86 lbs/cow/day. This is significantly less than values currently used for nutrient management planning for cows in confinement. However when urine is included the total manure production values were similar to those used for confined animals.
Introduction:
Across the north central region, states have begun to implement programs that mandate nutrient management planning to reduce the impacts of manure nutrients on surface water quality. Wisconsin statutes require all farms in the state to meet nutrient management standards by 2008. Both farmers and other agricultural professionals are gaining experience in writing nutrient management plans, but few plans have been written for farms practicing management intensive rotational grazing. Few existing programs address nutrient management planning for grazing farms.
Grass-based dairy farms are fundamentally different from conventional farms in ways that are likely to affect manure nutrient management. The differences between a confinement system and an MIRG system are several, including amount and quality of feed and forage consumed, volume of milk produced per cow, and distribution of manure generated. While the estimates associated with these items are fairly well documented for confinement systems, it is questionable whether they are accurate for grass-based dairies.
Measuring dry matter intake (DMI) and manure production of grazing cattle is problematic given the nature of grazing systems. A simple method for estimating intake and manure production that could be used on working dairies would vastly improve accuracy of nutrient management plans for MIRG herds.
This project provides farmers practicing MIRG with new tools to enhance their understanding of land stewardship and nutrient management. It will allows for the farmer input and experience needed to develop meaningful NMPs for MIRG farms. It will allow us to collect accurately and systematically, on-farm data concerning pasture productivity, milk production, and manure generation in broad climatic areas of Wisconsin. This will be the most complete data set in the northern temperate climate region of North America and will serve to promote economically and environmentally sound livestock agriculture in the North Central region.
Producers using Management Intensive Rotational Grazing (MIRG) will increase their awareness of the need for Nutrient Management Planning (NMP) and will become more knowledgeable of what is required to develop accurate plans. Other audiences (agencies and private consultants) involved in the process will be more knowledgeable about NMP issues for grazing farms and improve their ability to assist/support the NMP process.
Accuracy of estimates of manure production by grazing dairy cows will be improved to facilitate NMP by MIRG farms.
Accuracy of estimates of dry matter intake by grazing dairy cows will be improved. Across the north central region, states have begun to implement programs that mandate nutrient management planning to reduce the impacts of manure nutrients on surface water quality. Wisconsin statutes require all dairy farms in the state to meet nutrient management standards by 2008. Both farmers and other agricultural professionals are gaining experience in writing nutrient management plans, but few plans have been written for farms practicing management intensive rotational grazing. Few of the existing programs address nutrient management planning for grazing farms.
Grass-based dairy farms are fundamentally different from conventional farms in ways that are likely to affect manure nutrient management. The differences between a confinement system and an MIRG system are several, including amount and quality of feed and forage consumed, volume of milk produced per cow, and distribution of manure generated. While the estimates associated with these items are fairly well documented for confinement systems, but not for grass-based dairies.
Measuring dry matter intake (DMI) and manure production of grazing cattle is problematic given the nature of grazing systems. A simple method for estimating intake and manure production that could be used on working dairies would vastly improve accuracy of nutrient management plans for MIRG herds.
This project provides farmers practicing MIRG with new tools to enhance their understanding of land stewardship and nutrient management. It will allow for the farmer input and experience needed to develop meaningful NMPs for MIRG farms. It will allow us to collect accurately and systematically, on-farm data concerning pasture productivity, milk production, and manure generation in broad climatic areas of Wisconsin. This will be the most complete data set in the northern temperate climate region of North America and will serve to promote economically and environmentally sound livestock agriculture in the North Central region.
Nutrient management plans for the participating farms will be developed, implemented, and monitored to demonstrate the NMP process to other MIRG farms.
Development and demonstration of a nutrient management planning framework which will enable grazing dairy farms in the north central region to meet current and future nutrient management standards.
Development/modification of supporting NMP software and related tools that provide farmers and their support network with a means for accurately planning and documenting nutrient flows throughout the farm in accordance with nutrient management standards.
MIRG farms in the North Central Region will develop and implement nutrient management plans that enhance their environmental stewardship and improve the natural resource base on which they depend
Research
This study involved sampling from 7 farms in central and southern Wisconsin. Samples were obtained 3 to 5 times from each farm in each of 2003, 2005 and 2005 68 sample dates for the three years of the study.
Manure Production Estimates
Daily manure production was estimated based on phosphorus (P) balance. P concentration in all feeds was determined through sampling. The amount of supplemental feeds was measured and the amount of pasture dry matter intake was estimated as described later in this section. Milk production was measured and P concentrations in milk was determined through sampling. P concentrations in manure was determined through sampling. Manure was sampled five times at each farm each year to provide average P concentration. Once P intake and P excretion in milk was known, we could determine P excretion in manure. Using P concentration in manure we could determine the amount of manure which needed to be produced to excrete that amount of P.
Dry Matter Intake
In confinement operations, lb DMI often can be determined by direct weighing of feed and adjusting for moisture content and refused feed. In grazing operations, however, pasture forage consumed cannot be weighed, so lb DMI cannot be measured directly, and therefore, lb nutrient intake cannot be calculated. On the other hand, lb nutrient retained or secreted in milk can readily be determined in both kinds of operations, and, when lb DMI data are available, lb nutrient excreted is calculated by difference.
We evaluated and compare four models for determining DMI in grazing operations:
1. DMI based on energy balance:
Mcal NEL intake – Mcal NEL for maintenance - Mcal NEL retained or secreted into milk = Mcal NEL excreted. Where NEL means net energy for lactation and Mcal means megacalories or 1 million calories. Since by definition Mcal NEL excreted equals zero:
Total Mcal NEL intake = Mcal NEL for maintenance + Mcal NEL retained or secreted into milk
Energy for maintenance means energy used to maintain the animal’s body and subsequently lost from the body as heat. Energy retained means a change in the amount of energy stored in body tissues as a result of growth or fattening; generally, a gain in body weight is positive retention of energy and a loss in body weight is negative retention of energy. Either situation is possible. Energy secreted into milk means the export from the body of calories contained in energy-rich milk components such as lactose, fat, and protein.
These energy “outputs” for maintenance, body retention, and milk production can be readily determined when appropriate data measurements are taken. Energy concentration in feed dry matter can be readily determined by sampling all feeds fed, including pasture forage, determining nutrient composition by analysis, and calculating energy value by established methods. Therefore, energy intake can be determined and used to calculate lb DMI:
lb DMI = Total Mcal NEL intake/NEL concentration in DM
Grazing dairy cows are often fed supplemental feeds such as grains. Therefore, this equation must be further developed to isolate the lb DMI from pasture forage. This is done by accounting for the contributions of any supplemental feeds fed in addition to the pasture forage:
Mcal NEL intake from pasture forage = Total Mcal NEL intake – [(lb supplement DMI)(NEL concentration in supplement DM)]
andlb DMI from pasture forage = Mcal NEL intake from pasture forage/NEL concentration in pasture forage DM.
To facilitate the use of this model the following data was collected within each herd :
a. Cow body weight for determination of maintenance energy requirements. Body weights were measured using weigh tapes. We measured body weight once each year at the beginning of the grazing season. We determined body weights of 20% of each herd obtain an estimate of average body weight.
b. Cow activity level for determination of maintenance energy requirements. Activity levels were estimated based on the amount of exercise cows must perform to graze as described by the NRC.
c. Cow lactation number for determination of growth energy requirements. Cows in their first and second lactations will be expected to retain body energy for growth. Growth requirements were estimated as a percentage of maintenance requirements, as described by the NRC.
d. Herd milk production and composition to determine energy secreted into milk. Milk production was measured by bulk tank receipts, plus any milk withheld from treated cows and/or fed to calves. Composition was determined by laboratory analysis or from purchaser records. We determined milk production 6 times during the grazing season (once/month).
e. Weights of supplemental feeds consumed daily and feed samples for determination of nutrient composition and energy content of those feeds. Supplemental hay was sampled by obtaining 20 cores and combining these into a single sample for analysis. Grains and other feeds were sampled by grab sampling 5 samples and combining into a single sample for analysis.
f. Samples of pasture forage for determination of nutrient composition, fiber and energy content. Pasture samples were taken 4 - 5 times during each growing season at each farm by taking grab samples at a typical grazing height. Five samples were taken and combined. This procedure was repeated five times at each sampling date. Sample were taken from the pasture animals as they prepared to enter at the time of sampling.
g. Body condition scores (BCS) of cows to determine changes in retention of body energy as fat stores. Each herd was scored twice each season by trained cooperators, and changes in BCS converted to changes in energy retention by methods specified by the NRC. BCS will be made on 20% of each herd at the beginning and end of each grazing season
2.Clipping, drying and weighing forage from a known area.
A 2 x 2 ft2 area was clipped dried and weighed both prior to a grazing and following a grazing event. The difference was calculated as dry matter intake in lbs/cow/day. This procedure was replicated 5 times for each grazing event at each farm.
3.Utilization of a plate meter.
Twenty measurements were made with a rising plate meter both prior to and after a grazing event. The difference was calculated as dry matter intake in lbs/cow/day. The lbs of dry matter/acre/inch was determined by clipping, drying and weighing an area under the plate in 5 areas of the pasture to calibrate the plate.
4.Measuring height.
Pasture height was measured 20 times both prior to and after a grazing event. The difference was calculated as dry matter intake in lbs/cow/day. The lbs of dry matter/acre/inch was determined by estimating pasture condition and applying an estimation based on NRCS guidelines.
In addition to measurements specified above soil samples were collected to determine existing nutrient levels on each farm. This information is needed to develop a nutrient management plan and calculate a nutrient budget for each farm. Twenty soil cores were taken in each separate pasture on each farm. Cores from each pasture were combined into a single sample. Soil sampling was be conducted once on each farm.
Manure Production Estimates
Manure nitrogen content was 10.5 lbs/ton and P2O5 averaged 7.9 lbs/ton. These values are similar to confined cows. Feces production was estimated to be 85 lbs/cow/day using P2O5 excretion as an estimator. This value is well below the 124 lbs/cow/day currently used to estimate manure production of 1200-lb cows. However, when urine production is included the total manure production increases to 120 pounds which is similar to the manure production estimates currently used for nutrient management planning purposes.
There appears to be no reason to conclude that grazing dairy cows produce less manure than their confined counterparts of a similar size and milk production level. The average cow size was around 1200 lbs and average milk production was 56 lbs/day or 17080 lbs/cow on a 305 day lactation. Both of these values are less than what one would find on a confinement dairy and so the manure production values used for nutrient management planning purposes should reflect this.
An important consideration when writing a nutrient management plan for grazing farms is the manure that is being distributed by grazing animals. Using manure estimates from this study along with animal numbers and grazing days one can get a fairly accurate prediction of the amount of manure and hence nutrients “applied” to pastures by animals.
Dry Matter Intake Estimates
Using uncompressed height to estimate dry matter intake consistently produced the highest estimates and showed the greatest variability. (46.8 lbs/DM/day ± 7.7) These intake estimates are unrealistic and likely due to this method’s failure to account for pasture density. This method could be improved by calibrating the ruler with clippings as we did for the pasture plate. Intake estimates would be more realistic, but the high variability makes this method unreliable when used to estimate dry matter intake.
The other three methods agreed closely with each other on average but not within individual years. The clipping method and the use of the pasture plate resulted in dry matter intake estimates that agreed closely with each other but showed significant variability both within and between years. In 2003 the clipping and plate methods estimated significantly lower DMI than the energy method. In addition the variability was much greater, particularly when reported as a percentage of the average. These values were 34% for clipping and 24% for the plate compared with 15% for the energy method. In 2004 and 2005 the variability associated with these two methods was even greater. Even when considering the three year averages this variability was significant. For example, the use of the pasture plate estimated a three year average of 20.1 lbs DM/yr ± 3.7. This means that, statistically, it could be as low as 16.4 or as high as 23.8. T ± 3.9 The clipping method showed a three year average dry matter intake of 18.9 lbs DM/yr This type of variability in forage dry matter intake estimates is too great to accurately balance dairy rations, and these two methods, while more accurate than height alone, should still be used with caution.
The energy balance method provided the most consistent estimates between years and also showed the least variability The estimates over the three years of the study varied by less than a pound. (20.9, 20.5 and 20.0 lbs DM/day for 2003, 2004 and 2005 respectively).On average the variability was only 7.3%. Due ti the low variability this intake estimation method was used to determine total P intake and manure production. While this method requires more information to use, it also provides the most accurate estimates of a cow’s actual dry matter intake. The energy balance method described herein is simple enough to use by grazers, yet accurate enough to produce useful, reliable results. The spread sheet used to estimate pasture intake with this method is located at www.uwrf.edu/grazing.
This data suggests that forage dry matter intakes of dairy cattle on pasture is approximately 20 lbs/cow/day. The farms involved in this study were all very well managed, productive farms. It is unlikely that pasture dry matter intakes could be increased significantly suggesting that this may well be a maximum level given our current technologies and genetics. It should be noted that on average these farms were providing 16 lbs/cow/day of supplement, mostly in the form of corn grain. This resulted in an average total dry matter intake of 36 lbs DM/cow/day and an average milk production of 56 lbs/cow/day. This is a relatively high amount of milk given the low dry matter intakes and reflects the extremely high quality forage these cows are consuming from pasture (average NEl = 0.74 Mcal/lb). Still, these low dry matter intakes are responsible for the 5000 lb/cow/year lower milk production observed from grazing compared to confined cows.
Estimating Utilization Percentage
Another useful offshoot of this study was the ability to use the before and after yield estimates to calculate a utilization percentage. There were no significant differences between the three methods (energy balance method was not used as there is no before and after measurements). There was much less variability between methods and years than with the intake values. The average utilization percentage over all years and methods was 44.3% As the height method is the easiest and quickest to use this data suggest this is a good method to determine the utilization levels of grazed pastures.
Forage Quality
Forage quality was consistent both between and within years. Average crude protein level was 21%, average neutral detergent fiber level was 43%, and average relative forage quality was 201. NDF digestibility was 64.7. Net energy for lactation was 0.72. Obviously, the forage quality of vegetative pasture is very high and sufficient not only for beef cattle but for lactating dairy cows as well.
Most results are described below in the publications section as the greatest impacts have come from the development of Software aimed at facilitating the development of meaningful NMP for grazing dairy farms. These outputs have the potential to touch every grazing dairy in Wisconsin as these farms develop their own nutrient management plans.
Nutrient management plans for 4 of the participant farms have been developed. The project has provided information regarding dry matter intake of cows on pasture. It also is providing pasture utilization percentages, milk production figures, and pasture quality values. These types of values have not previously been available and are being shared with others as representative of typical grazing dairy farms. At the conclusion of the project, this information will represent a unique and valuable database for grazers in the north central region.
Economic Analysis
No economic analysis was intended for this study.
Farmer Adoption
Each of Wisconsin’s’ grazing dairy farms either have or will be using data and software either developed or impacted by the results of this study. Wisconsin currently has 13600 dairy farms. University of Wisconsin estimates put the number of grazing dairies at 22% or approximately 3000 farms that will be using data of software generated by this study.
The same number have the potential to utilize our dry matter prediction software. The utilization of this has been less immediate but is being used by our county agents and grazing specialist.
Educational & Outreach Activities
Participation Summary:
Information generated from this project was incorporated into ten grazing schools held in Wisconsin in 2003, 2004, 2005and 2006. Results were presented at the 2004 Upper Midwest Grazing Conference in LaCrosse, WI and the Central Wisconsin Grazing Network Annual Conference in Marathon, WI. As well as the Wisconsin Grazing Conference in 2006. An article summarizing some of the results appeared in the Winter 2004 issue of Forage Focus, a publication of the Midwest Forage Association. A meeting of all participants was held at Wisconsin Dells in March 2005. Results obtained thus far were presented and discussed. Articles have been included in the Midwest Forage Association Forage Focus Magazine and the UW Extension Grazing Web site. Results were presented at he International Grasslands Congress in Dublin, Ireland in 2005.
The primary nutrient management planning software in Wisconsin, SNAP Plus has been updated to reflect the information generated form this study. A spreadsheet has been developed and is available on the Wisconsin Extension Grazing Web Site (www.uwrf.edu/grazing) to assist in determining manure and hence nutrients delivers to a pasture by grazing animals. Another spreadsheet has been developed and is available at the same site aimed at assisting producers in estimating dry matter intake using the Energy Balance method.
Project Outcomes
Areas needing additional study
One important area needing additional study is nutrient accumulation in out wintering areas and their environmental impacts. These are areas often over looked in Nutrient management systems on grazing dairies.
A second is methods of increasing dry matter intake of animals on pasture. As this study suggests, this is the most limiting factor constraining milk production of grazing dairy cows.