The Impact of Dairy Herd Management on Nutrient Losses to Water Resources By Richard Kohn, Ph.D., University of Maryland

Introduction Current programs to reduce nutrient losses from farms have focused on soil and manure management. These practices by themselves are not adequate to reduce nutrient losses by 40% as needed to restore the Chesapeake Bay ecosystem.

The feeding and management of dairy cattle have a profound impact on reducing nutrient losses to water resources. With improved herd management, less manure is produced so fewer manure nutrients are left to runoff or be leached. In addition, productivity can be maintained with less feed, which means there is a lower requirement for crop production and fertilizer use.

The objectives of the current research are 1) to evaluate new technologies in herd management and feeding for their potential to reduce nitrogen and phosphorus excretion in manure, and their potential to reduce nutrient losses from the farm, 2) to estimate the cost-effectiveness of these technologies, and 3) to make recommendations for technology transfer, cost-share, tax credit, or other incentive programs to encourage implementation of desired programs.

Several new technologies were evaluated for their impact on changes in nutrient excretion to manure by summarizing data in the literature and developing mathematical models. Most animal research is conducted on individual animals and so the impact on the herd was calculated from the results of animal trials by aggregating according to expected herd distributions. The predicted change in nutrient losses from the farm that results from application of new technologies was calculated using a model adapted from previous efforts.

This research was supported by the US EPA Chesapeake Bay Program.

Results

• Management that increases production per cow can reduce nutrient losses to manure for the herd. Administration of bovine growth hormone to selected lactating cows, extending photoperiod with artificial lighting, and milking three times daily would each reduce nutrients in manure by 8, 5 and 7% respectively.
• A method was developed to fine tune dairy cow diets for protein feeding from analysis of milk composition. The amount of milk urea N and other variables can be used to predict N consumed in feeds and identify when cows are eating too much protein. Using this method to fine tune diets could reduce N output to manure by 6% initially, and lead to the discovery of other methods to improve N utilization in dairy cows.
• Current recommendations for phosphorus feeding assume that consumed phosphorus (P) is only 50% digestible. Research trials are needed to test the accuracy of this assumption. If P digestibility can be assumed to be 65% digestible, P in manure could be reduced by 35% and many farms that are currently accumulating P in soils will come into P balance.
• Most dairy cattle diets in the U.S. are balanced using the National Research Council (NRC) recommendations. A newer model called the Cornell Net Carbohydrate and Protein System (CNCPS) is often suggested to feed cattle more efficiently. We compared both models on two different large data sets. Using the CNCPS would have over fed or under fed dairy cows depending on the feeds used in the diets, and it is not recommended for routine formulation of diets for dairy cows. Further diet formulation research is needed.
• Theoretically, the use of protected amino acid supplements can reduce the total amount of protein needed in a ration and result in up to 20 to 40% less N in the manure produced by a dairy herd. Despite the theoretical benefits of using protected amino acids, in practice, further work is needed to improve our understanding of animal amino acid requirements. Research is needed to improve diet formulation models to balance for amino acid requirements.
• Dairy farmers typically feed all of the cows in a particular pen or barn the same diet. Each animal produces a different amount of milk, gains a different amount of weight, etc. and therefore each animal actually requires a different amount of energy, protein and minerals. Grouping cows affects nutrient balance in the herd. When feeding to meet the requirements of one cow in a group, a different cow may be overfed or underfed. When feeding all lactating cows together according to current recommendations, about 10% more N and P would end up in manure than when feeding each cow individually according to her requirements.
• Grazing is often considered an environmentally friendly method of animal production. Total N losses per acre were predicted to be 3.7 times greater for confinement systems compared to the grazing systems. However, milk production per acre was 4.3 times greater for the confinement systems. Grazing systems resulted in lower nutrient losses per acre but greater nutrient losses per unit of milk and meat produced.
• The potential to reduce nutrient losses by optimizing crop selection to meet annualized herd feed requirements with minimal nutrient losses from growing crops was investigated. Corn silage-based farms that import all grains would be able to comply with N-based nutrient management planning and need to purchase chemical N, while alfalfa-based farms that import grains would apply excess N. Nonetheless, the alfalfa-based farms would result in 3.3 units of N loss per unit of N in meat and milk while the corn-based farms would have resulted in 3.5 units of N loss per unit of N in meat and milk. The combination of alfalfa and corn silage was the best with only 2.9 units of N loss per unit of N in meat and milk.

Conclusions

Using multiple strategies to improve nutrient utilization in dairy cattle could reduce N and P feeding by more than 50%. About half the manure N will be lost from the farm before becoming available to crops in soils, and about half of the soil available N will be lost from the soil before being taken up and harvested in crops. With these assumptions, reducing feed N requirements by 50% without harming production could reduce the need for feed N by 50%, and reduce manure N output by 59%. In a typical dairy production system (including the production of imported feeds), improving N utilization in the animal by 50% would decrease total farm N losses by 55%.

Source: University of Maryland
Author: Richard Kohn, PhD

Environmental Benefits of rbST Supplements

PRODUCING MILK USING FEWER RESOURCES & GENERATING LESS WASTE

The net benefits of producing 10% more milk than the 1996 annual supply (19 billion gallons) using the same number of dairy cows and 100% adoption of rbST would include:

Water – irrigation for feed grains. 100% adoption of supplemental rbST would save 180 billion gal/yr of water, or the equivalent of 700,000 U.S. homes’ annual usage.Land – used for feed grain farming. 100% adoption of supplemental rbST would save 1.7 million acres of land, or 1/3 the land area of New Jersey.Fuel – for grain, dairy operations, and (including) rbST production. 100% adoption of supplemental rbST would save 150 million gal/yr of fuel, or 240,000 homes’ annual consumption.

Gases – methane (greenhouse) gases from cows. 100% adoption of supplemental rbST would reduce 4.9 million tons/yr gas emissions.

Manure – 100% adoption of supplemental rbST would reduce 0.9 million metric tons/yr of manure.

Soil loss — erosion from grain farming. 100% adoption of supplemental rbST would reduce 5.3 million tons/yr soil loss, or 1% of the U.S. total soil.

Source: Kansas State University
Author: Brouck, Smith

Tracking Mass Nutrient Balance on Delmarva Dairy Farms - The Phosphorous Dilemma J. A. Moore and J. M. Hart, Bioresource Engineering Department and Crop and Soil Science Department, Oregon State University

The production goal for most dairy farms is to maximize income through high milk output combined with low cost, high quality feed input. A dilemma develops as producers monitor and try to minimize soil phosphorus levels while simultaneously trying to achieve production goals. Phosphorus is imported onto a dairy in two forms. One, as fertilizer to meet one of the requirements for optimum forage production and secondly as a dietary supplement for maintaining healthy productive cows. Typical dairies on the Delmarva Peninsula have two exports containing phosphorous, milk and cull cows. Unfortunately the amount of imported phosphorus far exceeds the exports leading to a positive mass nutrient balance (an increase in soil phosphorus). As nutrient management regulations are written in Maryland and surrounding states the phosphorous dilemma becomes more challenging. How will a producer be able to maintain an economically viable number of animal units per acre without exceeding the allowable phosphorous limit (environmental degradation)?

Phosphorous loading within the confine of a dairy farm or any larger geographical area is serious issue large animal production agriculture is facing. The dilemma can be lessened if producers are more aware of the mass balance of nutrients on his or her farm. Software programs are available that track the mass balance of nitrogen, phosphorus, and potassium on dairy farms. All the inflows of these nutrients from fertilizer, feed, bedding, and animal entries are monitored. Also the outflow away from the farm of the same nutrients are measured in milk and animals sold, grains and forages sold, and manure exported. The remaining balance of these nutrients becomes a useful monitor of the accumulation on the farm and/or the potential for unplanned nutrient loss away from the farm.

For more information on the software to track Mass Nutrient Balance contact:

Richard A. Kohn
Department of Animal and Avian Sciences, University of Maryland
College Park, MD 20742
rkohn@wam.umd.edu

Stu Klausner
NRAES, Cooperative Extension
152 Riley-Robb Hall Ithaca, New York 14853-5701
sklausner@aol.com

Al Rotz
PSWMRL, The Pennsylvania State University
Curtin Rd., University Park
PA 16802-3702
alrotz@psu.edu

Source: Monsanto Dairy Group
Author: Hart, Moore

(TTV) FLUSH SYSTEM FOR DAIRY FACILITIES

J.P. Harner, J.P. Murphy and J.F. Smith

summary

Flushing characteristics of a tower tank valve flushing system with 12 in diameter manual valve were determined. Data were obtained using the outside cow alleys in a four row freestall barn. The alleys were 12 ft wide and 420 ft long with a 2 percent slope. The average flow rate exceeded 8,000 gpm when the average head was above 30 ft and the manual valve opened 80 degrees. Opening the valve to 90 degrees increased the flow rate to over 9,700 gpm. The velocity of the flushing wave was 8.5 fpm with a flow depth of 3.5 in. The estimated wave duration or alley contact time was 14.6 sec with a 25-40 sec release time from the flush tank. The flow rate ranged from 5,300 gpm to 7,200 gpm when the average head was between 16 and 28 ft.

(Key Words: Flushing, Manure, Water, Freestall.)

Introduction

Flushing systems which collect and transport manure are utilized in dairy operations.

It offers the advantage of labor reduction with automated systems, limited scraping requirements, lower operating cost, drier floors, potential reduction in odor and cleaner facilities. An optional method of handling the manure may be necessary during colder weather which is a disadvantage. Other disadvantages include the water requirements per cow and the initial fixed cost.

Designed flush systems utilize a flush device to release the correct volume of water at the appropriate discharge rate and length of time. This achieves the designed flow velocity, contact time, and depth of water in the gutter to obtain adequate cleaning.

Daily water requirements for flushing vary depending on the width, length and slope of the flushed area. Buildings with alleys sloping 2 to 4 percent will use less water for flushing when compared to alleys with a 1 percent slope. At an optimal slope of 3 percent, a minimum flush volume is 100 gal per ft of gutter width for flushing lengths of less than 150 ft. Longer lengths require more water with a suggested maximum release of 175 gal per ft. One study found 40 to 50 gal per cow per flush were required for effective flushing. A study of six dairies found flush water requirements ranging from 240 to 620 gal per cow per day. Another design procedure suggests selecting the larger of two volumes - either 52 gal per cow per flush or 1.35 gal per sq ft of alley per flush.

Most flushing systems utilize purchased components which include pipe line systems using pop-up valves or plates and underground piping. The objective of this study was to develop a tower tank valve (TTV) flushing system which could be incorporated into an existing or new dairy using sand bedded freestalls. Desired flushing characteristics included a release rate of 9,000 to 10,000 gpm, water usage of 4,200 gal per flush, 30 sec flushing interval and the ability to move sand laden manure. Procedures A TTV system was installed at a dairy in North Central Kansas. The freestall building was 420 ft long with a 2 % slope. The alleys had a one in slope towards the freestall curb from the outside wall. The four row barn had 84 freestalls per row. The feed alley was 14 ft wide and the cow alley was 12 ft wide.

The TTV flush system consisted of open-top flush tanks which are 10.4 ft. in diameter and 38.5 ft. tall. The flushing system uses a 6 to 7 ft section of 16 in pipe exiting the tank at a right angle. The 16 in pipe has a 45 degree slope inside the tank. Another 6 to 7 ft section of 12 in pipe, which includes a 12 in manual gate value, is then used to carry the water to the flush alleys. The pipe outlet directs the water along the freestall curb.

Data and measurements were taken using the upper 200 ft of the 12 ft alleys while the cows were milking. Except for the first flush, the alleys were free of manure and sand. During the study, the gate value was opened 80 degrees for the first study and then 90 degrees during the sec.

Tests were conducted at the site on two separate days. Measurements taken during the study used the 12 ft outside alleys and the data averaged together based on initial head. The flush water velocity was measured at a distance of 50 ft and 100 ft from a reference point. The reference point was located 90 ft from the outlet of the flush tank. The water front reached uniform flow prior to the reference point. Stop watches were started as the wave front passed the reference point and then stopped as it traveled past the known distance. The flush velocity was determined by averaging the velocities of the wave traveling 50 and 100 ft.

The flush tanks were equipped with pressure gages to measure the water pressure before and after each flush. The difference in pressure was used to determine the drop in water elevation and the water volume released. The average discharge rate was determined by the water volume release during a given time. The time interval was based on the time the valve was opened. The actual flush was normally 2 to 3 sec longer which was the time interval required to fully open the valve. The flush value was closed after the front had traveled 200 ft. or approximately 30 sec. The steady state release volume was not measured. However, based on Bernoulli equation and using the friction losses of the different components, the estimate steady state rate was 10,500 gpm.

The flow depth was determined at the reference point and the 50 and 100 ft intervals. The depth was determined by measuring the distance from the top of the curb to the top of the flush water and then subtracting this value from the total curb height. After the flush tanks were filled, the fill value was closed. Multiple tests were conducted until the tank depth was below 10 ft.

Results and Discussions

Table 1 present the results of the data collected when the valve was 80 degrees open. The discharge rate was a function of initial head and varied from 8,700 gpm to 5,000 gpm. The initial head varied from 34 ft to 16 ft. The wave velocity ranged from 7 to 10 fpm with an overall average of 8.5 fpm. The average water depth was 4 in.

Table 2 presents the results of the sec. study with the valve opened 90 degrees. Discharge rates increased a minimum of 500 gpm as compared to opening the valve only 80 degrees with a similar initial head. There was a reduction in velocity from 11.5 fps to 6.7 fps as the head reduced from over 30 ft to less than 10 ft. The depth of wave also reduced about 50 percent as the initial head reduced.

The water usage based on a 8,500 gpm discharge rate and a 30 sec flush is equal to 0.84 gal per square ft, a flow rate of 700 gpm per ft width of gutter and a water usage of 350 gal per ft of gutter. Based on number of freestalls and flushing three times per day, the water usage was 48 gal per stall per flush or 140 gal per day per stall. Based on a 30 sec flush three times per day in the milk parlor, the water usage in the milk parlor was 39 gal per stall per day. The flush system removed the sand and manure from the alleys based on visual inspections.

Summary

Procedures were developed for determining on-site the performance flushing systems. The flushing parameters of tower tank valve flush system exceeded current design recommendations. The modifications simplified the construction process and ease of maintenance. If repairs are necessary, the whole system does not have to be drained unless the pump has to be replaced. The manual values can be replaced by electric driven actuators with flush intervals based on time. The TTV flush system is also able to adapt to existing dairies providing there is room to handle the flush water at the lower end. One disadvantage to a TTV flush systems is more tanks are required. The initial cost appears to be similar to pipe line systems which use underground piping to equalize the pressure between two tanks.

It is important that the flush tank release rate be considered at the upper and lower end of the alleys. Sand traps and gravity solid settling basins need to be designed to handle higher velocities of flush water. Based on visual inspection of the alleys, it is suggested with sand bedded freestalls the minimum flush velocity be 7.5 fps with 10 fps being preferred. Current recommendations on release rates appear to be adequate based on this study and with 400 ft alleys. The water depth at the freestall curb should be a minimum of 3 in with 4 in preferred. The energy of the flush water needs to be directed along the freestall curb rather than in the center of the alley with sand bedded freestalls. This enables the flushing system to remove sand away from the curbs and avoids having to occasionally scrape the sand away from the curbs. Properly designed flush systems can be utilized for effective removal of sand laden manure in new or existing dairy facilities.

Table: 1 Characteristics of flushing system with valve 80 degrees open

1 Average flow rate based on from opening to closing of valve.

2 Estimated based on released rate, flow depth, velocity.

Table: 2 Characteristics of flushing system with valve 90 degrees open

1 Average flow rate based on from opening to closing of valve.
2 Estimated based on released rate, flow depth, velocity.

Source: Kansas State University
Author: Murphy Smith

Cooling Cows:

How Does Sprinkling Frequency and Airflow Impact Animal Response?

M.J. Brouk, J.F. Smith, and J.P. Harner

Kansas State University

Summer heat stress is just around the corner and the results of a study conducted by the dairy team from Kansas State University will help you keep your cows cooler this summer. Have you ever wondered if you should soak cows, increase airflow or both? Many producers have questioned which is most important. Last summer the team conducted a study to determine the effect of soaking frequency and airflow on respiration rates and skin temperature of heat stressed dairy cattle. Sixteen heat stressed lactating cows (8 primiparous and 8 multiparous) were arranged in a replicated 8×8 Latin Square design. Cattle were housed in freestall dairy barns and milked 2x. During testing, cattle were moved to a tie-stall barn for a 2-hour period from either 1- 3 pm or 3-5 pm on 8 different days in late August and early September. Afternoon temperatures ranged between 88 and 96 °F. During the testing period, respiration rates were determined every five minutes by visual evaluation. Skin temperature of three sites was measured with an infrared thermometer and recorded every 5 minutes. Treatments (Table 1) were 4 different soaking frequencies with and without supplemental airflow. Soaking frequencies were control (no soaking), every 5, every 10 or every 15 minutes. Supplemental airflow was either none or 700 cfm. Each soaking cycle provided similar amounts of water for all treatments. Initial data were collected for three 5-minute periods prior to the start of the treatments.

Cows soaked every 5 minutes with supplemental airflow (5+F) responded with the fastest and largest drop in respiration rate reducing the initial respiration rate by 47% at the end of 90 minutes of treatment (Figures 1 and 2). Soaking cows every 5 minutes without airflow (5) resulted in a similar response as soaking cows every 10 minutes with airflow (10+F). Soaking cows every 15 minutes with airflow (15+F) and soaking cows every 10 minutes without airflow (10) resulted in similar responses until the last 30 minutes of the study. Supplemental airflow without soaking (0+F) resulted in little improvement over no soaking or airflow (0). Soaking had a greater effect on respiration rate than airflow. However, the combination of wetting and airflow had the greatest effect on the respiration rate. When cooling heat stressed dairy cattle, the most effective treatment included continuous supplemental airflow and wetting every 5 minutes.

Skin temperatures are shown in figures 3, 4 and 5. Temperature of the thurl and ear were likely directly affected by the presence of water from the soaking procedure. However, the skin temperature of the rear udder was not directly affected by water from soaking. The rear udder skin remained dry throughout treatment. The reduction in rear udder skin temperature is the result of cattle directing less blood flow to the skin surface. This indicates that the cooling 2 systems were reducing heat stress as indicated by a reduction in respiration rates. The most effective treatment was the 5 minute soaking with supplemental air flow.

This data suggests that different cooling strategies could be developed for different levels of heat stress. Under severe heat stress soaking every 5 minutes with fan cooling will be the most effective. Under periods of moderate stress soaking every 10 minutes with fan cooling may be adequate. Reducing soaking frequency when temperatures are lower could significantly reduce water usage. Data clearly indicate that the combination of soaking and supplemental fan cooling are superior to either single treatment. If used singularly, soaking cows would have more impact than the use of fans only for cow cooling. These data indicate that about 1/3 of the total reduction in cow respiration rates was due to airflow and the remainder due to soaking. Under periods of severe heat stress, soaking every 15 minutes with airflow is not adequate and soaking frequency must be increased.

These data also suggest that different cooling strategies might be nearly as effective. For example, the effects of the 10 + F treatment were similar to those of the 5 minute soaking interval without supplemental airflow. This was also true of the 15 + F and 10 minute soaking interval without supplemental airflow. In situations where supplemental airflow is not provided, increasing soaking frequency may provide similar heat abatement as less frequent soaking with supplemental airflow. However, the data does clearly show that maximum cooling is achieved with frequent soaking with supplemental airflow.

Cow cooling with soaking and supplemental airflow is very effective in reducing respiration rate. Many systems may be ineffective because they do not deliver adequate water to soak the cow and/or have an inadequate soaking frequency.

Table 1. Experimental Treatments

*.35 gallon/headlock applied in 1 minute

Figure 1. Effect of Sprinkling Frequency and Airflow on Respiration Rate of Heat Stressed Dairy Cattle

Figure 2. Initial, Final and Percentage of Initial Respiration Rate of Heat Stressed Dairy Cattle Treated with Different Cooling Strategies

Figure 3. Cooling strategy effect on thurl skin temperature over 1.5 hours of cooling.

Figure 4. Cooling strategy effect on shoulder skin temperature over 1.5 hours of cooling.

Figure 5. Cooling strategy effect on rear udder skin temperature over 1.5 hour of cooling.

CALIFORNIA DEMO PROJECT REPRODUCTIVE ANALYSISPREGNANCY RATE:

Pregnancy Rate is a measure of how fast cows get pregnant once the breeding period begins. It is based on the number of pregnancies that occur per 100 eligible heat cycles. An eligible heat cycle is any cycle that occurs after the end of the voluntary wait period. This particular definition of pregnancy rate is sometimes referred to as a 21-day pregnancy rate.

21-day Pregnancy Rate = (No. Pregnancies / No. Eligible Heats) x 100

Eligible heats are defined as sequential 21-day periods following the end of the voluntary wait (VWP) period, until such time as the cow becomes pregnant, is coded as “do not breed” (DNB), or culled. In many herds, cows are bred and conceive prior to the end of the stated VWP policy. In this situation, the VWP is defined by how many days in milk the cow with the earliest pregnancy is when she conceives.

One example of how this formula works in practice is to consider the pregnancy rate for a single cow (Cow A). If Cow A is in a herd in which the voluntary wait period is 50 days and she becomes pregnant on day 120 then the calculation is as follows:

No. eligible days = 120 - 50 = 70 daysNo. eligible heat cycles = 70 / 21 = 3.33 cycles whichmeans she became pregnant in her 4 th eligible cycleNo. pregnancies = 1

21-day Pregnancy Rate = 1 / 4 = 25%
A pregnancy rate is also estimable for an animal that is not pregnant. Consider Cow B in the same herd is 90 days in milk and not yet been bred.

No. eligible days = 90 - 50 = 40 daysNo. eligible heat cycles = 40 / 21 = 1.9 cycles which isrounded to 2 heat cycles (round to the nearest wholenumber for open cows)

No. pregnancies = 0

21-day Pregnancy Rate = 0 / 2 = 0%

An average pregnancy rate for a group or herd of animals is simply calculated by counting all pregnancies and dividing by the sum of all eligible heat cycles across all cows in the group and multiplying by 100. Notice this is NOT the same as estimating a pregnancy rate for each cow and then averaging pregnancy rates across cows. This would cause an under estimate of the true pregnancy rate. Using cows A and B as an example, the correct average 21-day pregnancy rate is estimated as follows:

Total eligible heat cycles = 4 from Cow A + 2 from Cow B = 6

Total pregnancies = 1 (Cow A) + 0 (Cow B) = 1Average 21-day Pregnancy Rate = (1 / 6) *100 = 16.7%rounded to the nearest percent is 17%.Summary of Demonstration of POSILAC on California Dairy Herds Project Results

Across the seven herds in the Demonstration of POSILAC on California Dairy Herds project, pregnancy rates varied. In some herds, pregnancy rates for POSILAC supplemented cows appear to be greater than for cows not supplemented. In other herds the reverse appears to be true, and in other herds there is no apparent difference. Pregnancy rate is affected by heat detection and breeding efficiency. Any differences that may occur in herds using POSILAC are small and manageable. The key to sound reproduction is good heat detection and skillful breeding technique regardless of whether POSILAC is used or not.

DAYS OPEN:

Average Days Open is a more traditional measure of reproductive efficiency. It is often considered as a measure of how fast cows get pregnant. There are several inherent weaknesses in using only days open to monitor reproductive performance.
One issue is inconsistency in the definition of which animals should be included in the average. Should open cows be included? What about cows that have not yet made it through the VWP? If open cows are included, there is always the question of how to count days open for cows that are not yet pregnant. Is it the days from calving to current days in milk, or from the end of the VWP to current days in milk? No matter how it is counted, it changes every day.

Another issue with using days open as a sole monitor of reproductive efficiency is that no matter what definition is used; it is subject to being counter-indicative of what is occurring in the herd. For example, if only pregnant cows are included in the average days open estimation, there are times when success occurs, only to make the average days open to look worse. This happens when a long days open cow, say 250 days, gets pregnant. If average days open was 120, now including this cow in the average will cause it to increase despite a successful event – an additional pregnancy.

Another issue is that management decisions in other realms of the dairy operation can affect days open. One way to make days open look better is to cull open cows. This is a drastic decision indicative of poor reproductive management, yet the culling decision makes the reproductive monitor look better. There are other issues such as momentum, lag, and issues inherent in how dairy records may be managed that also may negatively impact the usefulness of average days open as an effective monitoring tool for a reproductive management program.

Average days open for the purpose of the demonstration project includes days open for pregnant cows only. Days open is simply calculated for each pregnant cow by determining how many days in milk a cow is when she conceived. Average days open is the simple average of days open over all pregnant cows in a treatment group. Therefore it is only a measure of how fast pregnant cows conceived and not necessarily indicative of the effectiveness of the total reproductive management program.

Summary of Demonstration of POSILAC on California Dairy Herds Project Results

There is variability in overall days open from herd to herd in the seven herds of the Demonstration of POSILAC on California Dairy Herds project. However when comparing days open between cows supplemented with POSILAC and control cows within herds, any differences are very small and inconsistent. Overall there appears to be no difference in average days open for pregnant cows between cows supplemented with POSILAC as compared to control cows in the same herd under the same management. This suggest s again that the same sound reproductive management principles apply regardless of if cows receive POSILAC.

PERCENT PREGNANT:

Percent Pregnant is simply a measure of the proportion of eligible cows that become pregnant. Often this measure is called a pregnancy rate. However, percent pregnant is a more accurate name for the calculation. It is calculated as follows:

Percent Pregnant = (No. Pregnancies / No. Eligible Cows) x 100

Percent pregnant is a function of how fast cows get pregnant (pregnancy rate) and how long a period they are given to get pregnant. In this case how long they are given the opportunity to get pregnant is directly related to how long a period the demonstration project covered. In other words, for two herds with identical pregnancy rates, the herd with the longer demonstration period will have a larger percent of eligible cows become pregnant. For this reason, unless cows in herds being compared have the same opportunity to get pregnant, percent pregnant cannot be compared across herds. When cows in different herds or groups have the same opportunity to get pregnant, than differences in percent pregnant is simply a function of differences in pregnancy rate.

Summary of Demonstration of POSILAC on California Dairy Herds Project Results

Differences of percent cows pregnant between herds in the demonstration project are a function of both differences in pregnancy rate and various lengths in duration of each herd project. Therefore, no comparisons should be made across herds. Within herds comparing cows supplemented with POSILAC to control cows, the results are very similar to differences in pregnancy rate. The differences appear to be small and inconsequential. And again, the focus on factors, which influence sound reproduction, should be the same regardless of whether POSILAC is used.

Source: Monsanto

‘Each kilogram of mix contained 4,000,000 IU of vitamin A, 400,000 IU of vitamin D, 3000 IU of vitamin E. 12 mg of Mn. 12 mg of Zn, 4 mg of Fe, 240 mg of 12. 40 mg of CO, 100 mg of Se, 800 mg of Cu, 1.4 mg of (NH4)2SO4. 1 mg of MgS04. 180 mg of Ca. 90 mg of P, and 90 mg of NaCI.

mination of the day of calf intake detected no systematic difference with other days of the week (P > .05). Milk samples were collected at each milking 1 dwk for 18 wk PP. For cows on the S treatment, milk was sampled only at machine-milking during the first 6 wk PP. Milk composition was determined by the central laboratory of the Israel Cattle Breeders’ Association (Bitan Aharon), and fat content was used to determine 4% FCM. Total milk production for the lactation and composition data were available from the same source based on monthly recordings.

Cow BW was recorded weekly for 18 wk PP, starting 2 wk before calving. Calving BW and BW at 3 d PP were averaged and used as initial BW. The correlation coefficient between initial BW and precalving BW was .992 (P c .05). Body condition scores (BCS) were assessed weekly for 18 wk, starting 1 wk before calving. One person ranked cows for BCS on a five-point scale (1 = emaciated to 5 = obese).

Feed intake for the first 10 wk was determined daily for each individual cow. The DM content of the feed and orts was determined by weekly analysis. Nutrient content of ration components was determined by weekly sampling and ration analysis

An indwelling cannula was placed in the jugular vein 24 h prior to blood sampling. Samples of venous blood (10 ml) were drawn from the cannula into heparinized syringes and immediately processed (centrifugation at 1000 x g for 10 min at 4°C) for collection of plasma, which was then stored at -20°C until analysis. Samples were collected at intervals of 30 min, commencing at 0600 h and finishing at 1300 h. For practical reasons, samples could not be taken during milking, so pre- and postmilking (or pre- and postsuckling) samples were taken at approximately 5 min before and 10 min after milking or suckling. The procedure was performed at wk 1 PP (d 7 of lactation for each cow) and repeated at wk 6 and 10 PP

Hormone Analyses Hormones were measured by specific double-antibody radioimmunoassays: growth hormone (GH), prolactin, and insulin as described by Vernon et al. (32); IGF-I after acid-ethanol extraction as described by Daughaday et al. (10); and oxytocin after extraction as described by Stock and Uvans-Moberg (29).

Statlstlcal Analyses

All statistical analyses were carried out using the general linear models procedure of SAS (28). Weekly data for milk production, FCM, DMI, BW change, and BCS were compared over treatments, weeks PP, and initial BW by analysis of variance, using cows within treatment and BW as the error terms for comparisons among treatments. The models also included an interaction effect of treatment and week PP.

Significance was set at P c .05 unless noted otherwise, and individual comparisons of treatments were made by Tukey’s Studentized multiple comparison test. Each of these models was tested separately for wk 1 to 6 PP and wk 7 to 18 PP. For each of wk 1, 6, and 10 PP, hormone measurements over 7 h were aggregated by calculating the area under the curve; those values were compared over weeks and groups by two-way analysis of variance, using variance among cows within groups as the error term for group comparisons. When interaction was significant, oneway analysis of variance was performed for each week separately.

RESULTS

Milk production is shown in Figure 1, and mean values by period are shown in Table 2.

Figure 1. Milk production of cows milked three times daily (M3; m), six times daily (M6; A), or milked three times daily and suckled three times daily (S; 0, 0) during the fmt 6 wk of lactation. Production of cows in the S group for total lactation (0) and machine-milkng only (0). Values are means with representative standard errors of the mean. Other standard errors of the mean are omitted for clarity.

During the treatment period, differences among groups were significant; milk production of cows in the S group was highest, and that of cows in the M3 group was lowest. Milk production was still increasing at wk 6 for cows in the S and M6 groups, but peaked during wk 4 for cows in the M3 group. Figure 1 also shows the amount of milk obtained at machine-milking for cows in the S group. This amount increased for the first 2 wk PP but then decreased; at its peak, machine-milking represented 40.7% of total production and, by wk 6, had fallen to 23.5%.

Milk production decreased sharply in wk 7 (immediately posttreatment) for cows in group S and, to a lesser extent, for cows in group M6; decreases were 29.2 It 1.18 and 4.6 It .62 kg/d, respectively. Despite these results, cows in the M6 group continued to produce more milk than cows in the M3 group (13.6%). Values for milk production of cows in the S group increased between wk 7 and 8 and more slowly thereafter, remaining lower than those for cows in the M3 group until wk 10 and then stabilizing after wk 12 before converging with values for the milk production of cows in group M6 at wk 18. Overall, milk production during wk 7 to 18 PP was similar for cows in the S and M3 groups but significantly higher for cows in the M6 group

Milk fat and protein contents were similar for all groups during the treatment period except for a reduced fat content of milk produced by cows in the S group compared with that for milk produced by cows in the M3 group (Table 2). Consequently, fat and protein yields were higher for cows in the M6 group than for cows in the M3 group, and the calculated values for cows in the S group were higher still, although component yields were probably underestimated because they were based on composition measured at machine-milking only. Fat content was greater in milk obtained later in milking, and the calves removed milk more efficiently than did the milking-machines. No posttreatment differences were found for milk fat or milk protein percentages. The DMI was significantly higher for cows in the M6 group than for cows in either the M3 or S groups throughout treatment and for the first 3 wk

TABLE 2. Milk production (MP), milk composition, DMI, and BW loss of cows milked three times daily (M3). six times daily (M6). or milked three times daily and suckled three times daily (S) during the first 6 wk of lactation.’

a.b,cMeans within rows with different superscripts differ P < .05. ‘For M3 and S. n = 10; for M6, n = 9. 2P > .05. 3Mean DMI for wk 7 to 10. *P < .05. **P < .01.

(Figure 2. The DMI of cows milked three times daily (M3; B), six times daily (M6; A), or milked three times daily and suckled three times daily (S; 0) during the first 6 wk of lactation. Values are means with representative standard errors of the mean. Other standxd errors of the mean are omitted for clarity.)

posttreatment; by wk 10, values were similar for all groups Figure 2 and Table 2). The DMI of cows in the S group were similar to DMI for cows in the M3 group during treatment and somewhat lower during the first 3 wk posttreatment (Figure 2).

The mean initial BW were very similar for the three groups (overall mean, 563 kg). During the first 6 wk PP, the cumulative BW loss was -25.2, -31.5, and -58.8 kg, for cows in the M3, M6, and S groups, respectively, which was significantly greater for cows in the S group than for cows in either the M3 or M6 groups (Figure 3a). The cows in the M3 and M6 groups reached their lowest BW at wk 5 and 6 PP and recovered to reach calving BW in the 12th and 15th wk PP, respectively. However, cows in the S group continued to lose BW until wk 8 PP, 2 wk after removal of the calves, and calving BW was not attained until wk 18 PP (Figure 3a).

Initial BCS were also very similar for the three groups (overall mean, 2.67). Decreases for the first 6 wk PP for cows in the M3, M6, and S groups, respectively, were greater (P < .Ol) for both the M6 and S groups than in the M3 group (Figure 3b). The BCS of cows in the M3 and M6 groups stopped decreasing during the 7th wk PP. However, for cows in the S group, BCS continued to decrease until the 11th wk PP, and only then started to recover.

Hormone data are presented in Figure 4. For all hormones studied, profiles were very similar at wk 1 and 6, so data were plotted for wk 1 and 10 only. Calculated values for areas under the curves are presented in Table 3. During treatment, basal values for oxytocin (those samples taken between milkings or sucklings) were highest for cows in the S group, intermediate for cows in the M6 group, and lowest for cows in the M3 group. The greatest oxytocin release was observed for cows in the S group as a response to suckling; cows in all three groups demonstrated a smaller pulse release 10 min after the afternoon milking, and little difference existed among groups in this regard. Oxytocin area under the curve was significantly higher for

Figure 3. Change in BW (a) and body condition score (1 = emaciated and 5 = obese) (b) of cows milked three times daily (M3; B), six times daily (M6; A), or milked three times daily and suckled three times daily (S; 0) during the first 6 wk of lactation. Values are means with representative standard errors of the mean. Other standard errors of the mean are omitted for clarity.

VERY FREQUENT MILKING OR SUCKLING

Figure 4. Plasma hormone concentrations of cows milked three times daily (M3;-), six times daily (M6; _ _ _ _ _ ), or milked three times daily and suckled three times daily (S; . . . . .) during the first 6 wk of lactation. Values are means. Samples were taken at intervals of 30 min during 7 h and additionally at 5 min before and 10 min after milking or suckling. Cows in the M6 and S groups were milked or suckled at 0700 h, and all cows were milked at 1200 h.

cows in the S group than for cows in the M6 or M3 groups. Oxytocin did not change posttreatment for cows in the M3 group, but, in the S group, the basal values were lower than during treatment. The postmilking peak was similar to premilking values, but a morning peak no longer existed, because suckling was absent. Oxytocin area under the curve was significantly lower postmilking for cows in the S group than for cows in the M3 group (Table 3)

Prolactin varied during the day during all 3 wk. Cows in the S group exhibited a clear pulse of prolactin release at suckling (wk 1 and 6; data shown for wk 1 only), but there was no clear postmilking release at any time in any group. Area under the curve was highest for cows in the S group (P e .05). intermediate for cows in the M6 group, and lowest for cows in the M3 group during treatment.

Clear differences existed in GH concentrations among the groups during treatment. Area under the curve values confirmed that concentrations of GH were elevated in cows in the S group compared with cows in the M6 group (P < .OS); GH concentrations were lower (nonsignificantly) for cows in the M3 group than for cows in the M6 group. By wk 10, GH values were no longer significantly different among groups. Differences in IGF-I among groups reflected the differences in GH, but the higher IGF-I values of cows in the S group were significant for all 3 measurement wk (Table 3). Insulin concentrations demonstrated the reverse; insulin was highest in cows in the M3 group, intermediate in cows in the M6 group, and lowest in cows in the S group throughout (Table 3)

DISCUSSION

Increasing milking frequency from 3 to 6x raised milk production by 7.3 kg/d (21%) during the first 6 wk PP. Previous studies of increased milking frequency have mainly involved increases from 2 to 3x, and milk production increases of from 6 to 25% have been observed (3, 11, 23). The present data clearly indicate that milking 3x does not result in maximum production. To our knowledge, this experiment was the first detailed study of protracted, very frequent milking during early

(TABLE 3. Plasma hormone concentrations (ma under the curve) of cows milked three times daily w3), six times daily (M6). or milked three times daily and suckled three times daily (S) during the first 6 wk of lactation, determined from 30-min spaced samples taken over 7 h.

————–table page=7————a.b.cMeans within rows with different superscripts differ (P <.05) ‘Growth hormone. *P <.05.)

lactation. Other studies, which have been brief (31) or have been conducted using unmatched groups of cows at different stages of lactation (15), reported increases of 8 to 10%. Milking 4x for 4 wk increased milk production by 11% above milking 2x (14), but, once again, this response was submaximal; other cows milked 4x and additionally treated with GH (recombinant bST) increased production by 28% (18). The difference between cows in the M6 and M3 groups quite possibly would have increased further if treatment had continued; milk production was still increasing for cows in the M6 group at wk 6 PP, but for cows in the M3 group, production showed no real increase after wk 4.

Some effects of very frequent milk removal could be mediated by endocrine factors related to teat stimulation, particularly oxytocin, prolactin, and GH. Evidence exists that different forms of teat stimulation affect hormone release in distinctive ways (13) and that calf presence can affect the response of a cow to teat stimulation (2). Detailed mechanistic studies require very frequent sampling around milking, which we did not attempt; nevertheless, some endocrine differences were apparent. Oxytocin and prolactin values were higher in cows from the S group, intermediate in cows from the M6 group, and lowest in cows from the M3 group. Oxytocin differed largely as a consequence of additional postmilking and suckling release, but prolactin differences were mainly because its baseline was higher for the S and M6 groups than for the M3 group. The recognized action of oxytocin is in milk removal. Recent claims that oxytocin can stimulate mammary metabolism (5) have not been supported by analysis of data from half udders within cows, which demonstrated that oxytocin administration increased production in the half udder that was milked just after injection but not in the contralateral half, which was milked earlier (16). In the present experiment, we observed a posttreatment depression in basal oxytocin concentrations of cows in the S group, but no reduction in the postmilking surge. We suggest that this effect would have little biological consequence for milk production. Long-term treatment with oxytocin improved lactation persistency of dairy cows (21), but it is not known whether this was an effect of the hormone per se or a consequence of improved milk removal.

Although prolactin is essential for successful lactation in rodents, no evidence exists of any galactopoietic effect during established lactation in ruminants (24). An increase in mammary growth and differentiation during the early lactation treatment phase may explain the long-term effects on milk production. Once again, although prolactin was implicated in mammary growth control of nonruminants, the evidence for ruminants did not support a mammogenic role for prolactin (9).

One hormone that is clearly implicated in galactopoiesis 0 and also in mammogenesis (9) is GH. Differences in GH concentrations among groups corresponded to milk production: highest GH and milk production for cows in the S group and lowest GH and milk production for cows in the M3 group. Milk production might have responded to GH; however, the GH differences just as easily could have been a consequence of the energy status of the three groups. Our results do not rule out a subsequent effect of GH on milk production, but this experiment provided no evidence of a causative action. During wk 1, GH release was related to the afternoon milking. This release was not repeated in other weeks, and could have represented enhanced responsiveness of the GH axis early in lactation.

Because frequent milking of one half of the udder affects only that half (14), the main effect of milking frequency is not related to endocrine function, but is directly related to actual milk removal. This result is due to the presence of a protein in milk that inhibits milk secretion, the feedback inhibitor of lactation (FIL) (33). As milk accumulates in the udder between milkings, secretion rate gradually decreases because of the action of FIL. More frequent removal of milk thus enables a longer maximal secretion rate. The main effect of FIL is exerted during protein secretion (26), resulting in an immediate reduction in milk production. The FIL directly inhibits mammary differentiation in vitro (35), so the positive effects of frequent milking on mammary differentiation are probably also mediated in this way.

The data demonstrated a clear carry-over effect of very frequent milking early in lactation. Production did decrease when frequency was reduced from 6 to 3x, but, during 12 wk posttreatment, cows in the M6 group still produced 5.1 kg/d (13.6%) more than cows in the M3 group, a significant difference. The milk production for the entire 305-d lactation was significantly higher for cows in the M6 group (10,476 f 397 kg) and S (9897 f 47 1 kg) groups than for cows in the M3 group (8994 rt 260 kg). Milk composition was not different among groups, and lactation fat and protein yields increased. Although others (23, 25) have demonstrated carry-over after periods of milking 3x, the effects were small and not statistically significant. This difference in results might be related to the fact that our experiment was the first time that treatment had been applied so early in lactation. The presence of a carry-over effect implied that mammary development had been enhanced. Frequent milking has been shown to increase both mammary differentiation and proliferation of mammary cells of goats (36) and of cows (14). Because mammary proliferation continues for the first few weeks PP at least in goats (19), the mammary gland may well be exquisitely responsive to mammogenic stimuli during early PP (1).

A further novel finding of the present study was the higher total milk production of suckled and milked cows versus very frequently milked cows. The mechanism underlying this difference is unknown. Earlier studies (12, 30) investigating low frequency of udder emptying established that suckling stimulated higher milk production than did machine-milking. In our experiments, we used two heifer calves suckling 3x to ensure a maximum stimulation. Endocrine profiles were different for cows in the S group compared with cows in the M6 group, but perhaps the calves emptied the udder particularly well, thus further reducing the inhibitory action of FIL. However, machinemilking removed relatively little milk from cows in the S group; presumably milk ejection was voluntarily suppressed to ensure milk for the calves. Thus, three of the six milk removals were efficient (calf suckling), and the other three were inefficient (machine-milking). Inefficient milking reduced milk production of goats locally through FE action (M), and the reason that overall production was significantly higher for cows in the S group remains unknown.

The suckling stimulus was abruptly removed at the end of the 6-wk treatment period. As a consequence, milk production dropped very markedly for cows in the S group, and, during the 1st wk posttreatment, cows in the S group gave little more milk at machinemilking than they had when they were still feeding calves. This result was almost certainly due to psychological disturbance of milk ejection (i.e., poor milk removal) rather than to a direct inhibition of milk secretion per se. The FIL mechanism would thus have operated to restrict secretion to an amount appropriate to the reduced overall milk removal. As the cows became more accustomed to the absence of the calves, milk removal improved, and milk production increased, rising above the production of cows in the M3 group to a production very similar to that of cows in the M6 group. Suckling during early lactation apparently induced the same mammary developmental improvements as very frequent milking, but expression of the improved production was delayed following calf removal until the cow adjusted to the changed conditions. The period of inefficient milking immediately after calf removal had no long-term deleterious effect on milk production, which was in agreement with recent observations of short periods of once daily milking in cows (17).

Increased milk production has an energy cost. Thus, cows in the M6 group consumed more DM than did cows in the M3 group. In some studies (27), a measurable increase in DMI accompanied the rise in milk production from higher milking frequencies but, in other studies, the increase was too small to be measurable or nonexistent (3, 11). The increased DMI by cows in the M6 group did not compensate for the increased energy demands, and thus these cows lost more BW, had a lower BCS during the initial lactation period, and displayed a longer recovery period than did cows in the M3 group. Despite this occurrence, health parameters (mastitis or lameness) were not observably different among the groups.

The lower BW of cows in the S group was not initially reflected in a decreased BCS, which fell by similar amounts for cows in the S and M6 groups PP. Curiously, cows in the S group did not increase DMI over that of cows in the M3 group, and cows in the S group ate significantly less than did cows in the M6 group even though access to feed was unlimited for both groups. This result was unexpected and is a major area for further study. Why cows in the S group ate less is not known. The different endocrine profiles of cows in the S group allow for some speculation, particularly with regard to the possible role of elevated plasma oxytocin [oxytocin suppressed voluntary feed intake of rats (4, 22)]. However, it is not yet possible to draw any firm conclusions. Health status did not appear to be affected; cows in the S group had no greater incidence of mastitis or lameness than did cows in the M3 or M6 groups and had the best conception rates of the three groups, although reproductive activity of the cows in the S group was totally suppressed until after calf removal (U. Bar-Peled, 1994, unpublished data).

CONCLUSIONS

We have demonstrated that frequent udder emptying during early lactation has short and long-term effects on milk production. Suckling produced a greater short-term increase than milking did, but the carry-over effect was then delayed by the psychological disturbance of calf removal. The DMI was increased by frequent milking, but not by suckling, and, in both cases, DMI was insufficient to support the enhanced milk production, and the cows lost BW.

ACKNOWLEDGMENTS

The authors are grateful to U. Lavin and Y. Short and to the staff of the dairy herd of Kibbutz Kefar Menahem, who provided the facilities to house and care for cows and calves.

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Source: Agric. Research Org, Israel
Author: Bar-Peled, Maltz

ABSTRACT

The health of dairy cows given bovine somatotropin (bST) for one lactation was evaluated in 28 commercial herds located in four regions of the United States. At least six herds were in a region and at least one herd/ region contained fewer than 60 cows. Cows (n = 1213) were assigned randomly to control or bST groups and were treated beginning in wk 9 to 10 of lactation and every 14 d until dry-off or d 400 of lactation. Management was according to site practices. Cows were observed for health-related signs by farm personnel daily and by the herd veterinarian biweekly. Average 305-d test-day milk yields were 932 kg greater for bST-treated cows. Pregnancy rates, days open, twinning, cystic ovaries, or abortions were unaffected by treatments. Supplementation of cows with bST had no effect on total mastitis cases, total days of mastitis, duration of mastitis, or the odds ratio of a cow to develop mastitis. Cows supplemented with bST used more medications for health events other than mastitis. This usage was associated primarily with treatments for disorders of the foot and hock. Supplemented cows had a slight increase in foot disorders. There was no effect of supplementation with bST on culling from the herd or removal from study. Overall, the results confirm that label directions for bST are adequate for safe use under field conditions. All clinical signs observed in this study occur normally in dairy herds and were managed in cows supplemented with bST.

(Key words: somatotropin, animal health, mastitis, reproduction)

Abbreviation key: PAMP = postapproval monitoring program, RHA = rolling herd average.

INTRODUCTION

Sometribove (United States Adopted Name) is a sterile formulation of methionyl bST for use in lactating dairy cows to increase milk production (Posilac., Monsanto Co., St. Louis, MO). It was commercialized in the US dairy industry beginning February 4, 1994. Because bST was the first production drug approved for use in lactating dairy cattle and the first recombinant peptide approved for production use in domestic animals, there was concern about its safety under field conditions. Therefore, a postapproval monitoring program (PAMP) composed of three parts was established to determine whether mastitis incidence and antibiotic use were manageable under label-use conditions and whether label directions were adequate.

One component of the PAMP was a controlled study in commercial dairy herds located in the four major geographic regions of the United States and concentrated in primary dairy states. The objective of this study was to evaluate the impact of bST on cow health in commercial dairy herds when used according to label instructions for one lactation.

Effects of bST on human and animal safety have been thoroughly investigated (Bauman, 1992; Cole et al., 1991, 1992; Marcek et al., 1989; Stanisiewski et al., 1992; Vicini et al., 1990). The effects of bST on milk yield in short-term studies under field conditions have been published previously (Thomas et al., 1991). Additionally, the impact of chronic use of bST under field conditions on clinical lameness was evaluated and reported (Wells et al., 1995). The effects of acute and chronic treatment of cows with bST on animal health under clinical conditions have been reported (Adriaens et al., 1992, 1995; Eppard et al., 1991; Vicini et al., 1990). However, no study has evaluated the impact of bST on animal health under commercial conditions for a full lactation. Thus, this study was designed to examine the general health of dairy cattle given bST for a single lactation under commercial conditions. A total of 1128 cows from 28 herds were included in the analyses, making it the largest single study of bST and herd health ever conducted.

MATERIALS AND METHODS

Herd Selection

A total of 28 commercial dairy herds located in four geographic regions of the United States (Northeast, Southeast, Upper Midwest, and West) were selected. Herds were primarily from the top 21 dairy-producing states. In addition, the dairies were selected to provide a minimum of six herds per region, and at least one small dairy farm (fewer than 60 lactating cows) was located in each region. Two of the herds used Jersey cows and the remaining 26 herds used Holstein cows.

Criteria for herd selection included reliable health records; a regular herd health program; and a rolling herd average (RHA) greater than 6350 kg for 2? milking, 7700 kg for 3? milking, and 8600 kg for 4? milked herds. Herds were required to have sufficient cows available to enroll all cows within 6 mo of study start. This interval was extended to 12 mo for small herds due to limitations of available animals.

Herds also had to have culling rates below 40% and have an average bulk tank SCC average of less than 300,000 cells/ml. A total of 96 herds were evaluated to obtain the 28 herds used in this study. Information on herd location, size, and average milk production of the 28 herds chosen is shown in Table 1.

Animal Selection and Management

The study was conducted as a randomized block design. Cows (n = 1213) were blocked by parity and herd and were assigned randomly within blocks to one of two treatments. Treatments were bST (500 mg of sterile sometribove zinc oil formulation/14 d) or control (oil excipient).

Eligible animals from each herd were assigned to a pool from calving to approximately 6 wk of lactation. Before treatment initiation for each cow, at least two milk and SCC records (DHIA or equivalent) no less than 20 d apart were required. At 2-wk intervals, animals in the pool that remained eligible on the start date (9 to 10 wk of lactation) were assigned randomly to treatment (A or B) based on starting order and parity. Cows were eligible for first injection at d 57 of lactation and remained eligible to start first injection up to and including d 70 of lactation.

Treatment assignments of individual cows in each herd were not identified so that the veterinarian and farm personnel were blind to treatment assignment. Syringes used for injections were labeled only as ‘A’ or ‘B’ and did not specify whether syringes were test or control article. Treatments were administered on the same day of the week every 14 d and generally at the same approximate time of day. Each site identified an injection day of the week to minimize injection errors because all cows were treated on the same weekday. Injections were administered subcutaneously in the tailhead or postscapular region according to instructions listed on the product label. If a cow received a partial injection, an additional syringe was administered to ensure that cows were not underdosed. Records were kept of all injections.

General management, health care, milking, and feeding management of cows were in accordance with established site practice, unless specified otherwise in the protocol. Cows remained on study until they were dried off or reached d 400 of lactation.

The normal reproductive management practices were followed at each site without regard to treatment assignment. Two cows were not bred intentionally, and data for these cows were excluded from all reproductive analyses. Data for cows that conceived before initiation of treatment were not included in analyses of percent pregnant or days to first insemination. Also, in one herd, cows were bred exclusively to a bull and individual cows in other herds were housed with a bull after a specified number of days. Data for these animals were not included in analyses of reproductive variables that required a conception date.

Normal culling practices were followed by all herds on the study. Before any animal was removed from the program, the veterinarian or Clinical Investigator was contacted and the reason(s) for removal was documented. If the removal was due to health problems, the animal was examined by the veterinarian, and clinical conditions for removal were documented. Animals that died while on study or required euthanasia because they were moribund were necropsied by the attending veterinarian. All available practical means were employed to determine the cause of any illness, death, or injury.

Observations, Examinations, and Tests

Starting at least 2 wk before treatment and continuing through 2 wk past the last injection, cows were observed daily by designated individuals at each site. All health-related observations were recorded using the existing record keeping system for the site. Before the start of the study, farm record keeping was reviewed and adjusted as required to assure that all farms were recording the required data. Daily observations were comprehensive and captured health conditions even if a condition persisted from the previous day. When taken, other health parameters were recorded such as temperature, pulse, respiration, ruminal motility, or assessments of appetite or animal activity. On the day of treatment administration, the veterinarian was pres

Table 1. Herd information for the postapproval monitoring program for bST.

¹Not on test before study, value is 305-d mature equivalent from herd software.
²Jersey breed. All others Holstein.

ent to observe all cows and record any health observations. Each site maintained a record of all medications and therapies administered throughout the study and reason(s) for administration of medications and therapies were recorded.

Cows were observed at every milking for signs ofclinical mastitis. Clinical mastitis was defined as thepresence of abnormal milk, such as visible flakes, clots,strings, clumps, or discoloration from blood or serum.Further evidence of infection, such as swelling, heat,pain in the affected quarter(s), depression, off-feed, ordrop in milk production may also have been presentand were also recorded. All mastitis records were maintainedby individual quarter, and quarters were treatedseparately in analyses. For calculation of cases and caseduration, a quarter needed to be free of clinical signsfor at least 21 d to be considered a new case.

Milk production and SCC data were obtained from DHIA (or equivalent program) records. Reproduction records were maintained according to site practices.

Data Analysis

Statistical analyses were conducted using SAS(1997). Separate analyses were conducted for each par-ity group (primiparous and multiparous). Treatmenteffects were examined using mixed model analyses employingREML algorithms. For normally distributed(continuous) variables, the MIXED procedure was used.Nonnormally distributed variables (counts, proportions)were examined using generalized mixed modelanalyses (% GLIMMIX macro; Littell et al., 1996).Treatment was the only fixed effect in the model. Randomeffects in the full model included location and theinteraction of treatment and location. Number of cowsaffected was fit as having a binomial error with a logitlink, while days affected rate was fit as having a Poissonerror with a log link and log of the period length as anoffset. In all cases, the extra-dispersion parameter wasallowed to vary, to accommodate possible over-dispersion.Results from these analyses are best linear unbiasedestimators and are referred to using the SAS designationas least squares means. When data were deemedsparse (fewer than five observations in any locationtreatmentcell) or when the macro failed to convergewithin 50 iterations, the exact analog of the Cochran-Armitage trend test was used, with location as a stratifyingvariable (Mehta and Patel, 1996). If fewer thanthree observations were in any location-treatment cell,no analysis was attempted. Survival analysis tech niques in the LIFETEST procedure were used to testfor associations between treatment and event-timevariables. For these latter analyses, raw means arereported. Treatment effects were considered significantat P < 0.05.

RESULTS

A total of 1213 cows were assigned and began the study and, of these, 85 cows were excluded due to protocol deviations such as initiation of treatment outside the 57 to 70 DIM range. Therefore, 1128 cows were included in the analyses. This included 419 primiparous and 709 multiparous animals. Cows within parity generally were distributed evenly between treated and control groups. Cows from the first to the eighth lactations were included in the study, with the majority (83.7%) in the first three lactations.

Milk Production

The mean RHA for the 27 of 28 herds with a RHA at study start was 10,100 kg (Table 1). Average test day-derived 305-d milk yield for control cows during the study was 10,247 kg, while average milk yield for cows treated with bST was 11,179 kg. Although this study was not designed to evaluate milk yield responses of cows treated with bST, the difference in milk yield for the two groups (932 kg) is similar to previous studies (Hartnell et al., 1991) in which milk yield responses to bST were measured directly.

Reproduction

The reproductive performance of primiparous and multiparous cows is presented in Table 2. Use of bST for either parity group did not affect (P > 0.05) days to first insemination, days open, percent pregnant, fetal loss, abortion, cystic ovaries, successful calving rate, multiple births, or gestation length.

Mastitis

Clinical mastitis results are presented in Table 3. The number of total cow-days during the treatment period for primiparous cows receiving bST was 55,704 d, which was greater than 53,961 d for controls. This increase in cow-days for the bST-treated cows is accounted for by the numerical increase in days open (Table 2) and concomitant slightly longer lactations in this group. Therefore, the number of days at risk for all health events including mastitis was increased in the group treated with bST. The health data are not corrected for this increase in days at risk or for the additional milk produced. Regardless, use of bST wasnot associated (P > 0.05) with increased mastitis incidencein numbers of cows affected, cases per 100 cowdays,days observed per 100 cow-days, or duration ofcases (Table 3).

Similar to data presented for primiparous cows, thenumber of total cow-days was greater for multiparouscows treated with bST. Average days were 87,075 and88,590 for control and bST-treated groups, respectively.The increased number of days at risk (1515) in thisgroup was also associated with a numerical increase indays open and subsequently longer lactations (Table2). Use of bST in multiparous cows did not affect (P >0.05) numbers of cows affected, cases per 100 cow-days,days observed per 100 cow-days, or duration of cases(Table 3). Thus, under commercial conditions in thefirst year of continuous use, there was no effect of bSTuse on mastitis incidence in primiparous or multiparouscows.

The odds ratios for mastitis and expected cases of mastitis in cows treated with bST are presented in Table 4. Odds ratios were not significantly different from 1.00 for either parity during the pretreatment or treatment periods. The odds ratios calculated for the treatment period for both primiparous (1.31) and multiparous cows (1.39) indicate no differences in the incidence of mastitis between control and bST-treated cows. The expected cases per cow for mastitis during the 252 d standardized treatment period were 0.23 and 0.28 for control and bST-treated primiparous cows and 0.38 and 0.50 for multiparous cows, respectively, and were unaffected by treatments.

Sampling of milk for components varied considerably between herds, but milk SCC were analyzed from samples taken from each cow at 154 ± 45 d following treatment initiation. The SCC were not affected by the administration of bST. Least squares means of linear scores ± SEM for control and bST-treated primiparous cows were 2.9 ± 0.23 and 3.1 ± 0.22, respectively. Values for multiparous cows were 3.9 ± 0.21 and 3.6 ± 0.21.

Medications

The results of the analyses of medication use in control and bST-treated cattle are shown in Table 5. As mentioned previously, there was an increase in total cow treatment days in both primiparous and multiparous cows treated with bST associated with slightly extended lactations (Table 2). Results are presented as the proportion of cows ever receiving medications or the proportion of total days that cows were medicated. All medications administered were recorded, and these were divided into preventive and therapeutic medica

Table 2. The effect of bST on reproductive performance during treatment period in primiparous and multiparouscows in the postapproval monitoring program.

¹NS = nonsignificant (P > 0.05). NA = Not analyzed because <3 fetal losses, or <3 unsuccessful calvings, for each site ? treatment subclass. Results for NA are raw means.
²Calculated for animals with accurate breeding/conception information (i.e., excludes cows bred to a bull).
³Lost pregnancies as a percentage of all conceptions.
⁴Successful calving defined as cows that gave birth, lived at least seven days and calf(s) lived at least 24 hr as a percent of cows that conceived and stayed in herd until parturition.
⁵Survival analysis:log rank test. Results are reported as raw means (± SE of raw means).
⁶Linear mixed model analysis: results are reported as least squares means (± SE of least squares means).
⁷Generalized linear mixed model analyses: results are reported as least squares means (± SE of least squares means).
tions. Therapeutic medications were further subdivided into mastitis and nonmastitis medications.

In primiparous cows treated with bST, the proportion of days medicated was greater, even though days with medication were small for each group. Average percentages of days medicated were 0.59% for controls and 1.01% for bST-treated cows (P < 0.05). This was not associated with preventive treatments but was associated with use of therapeutics. Both the proportion of cows medicated at least once with therapeutics and proportion of days were increased in primiparous cowstreated with bST compared with controls. Average percentagesof cows given therapeutics at least once were36.0 and 46.8% (P < 0.05) for control and bST-treatedprimiparous cows, and these medications accounted foronly 0.54 and 0.95% (P < 0.05) of days, respectively.When subdivided into mastitis and nonmastitis medications,administration of mastitis medications was notaffected by treatments for cows or days medicated. Similarly,nonmastitis medications were unaffected for

Table 3. The effect of bST administered on clinical mastitis in primiparous and multiparous cows in thepostapproval monitoring program.

¹NS: nonsignficant (P > 0.05).
²Generalized linear mixed analyses: results are reported as least squares means.
³Linear mixed model analysis: results are reported as least squares means.

Table 4. The effect of bST on the odds ratio of an animal having mastitis and expected mastitis cases duringthe pretreatment and treatment periods of the post-approval monitoring program.

¹Odds ratio is the antilog of the difference between least square means from Linear Mixed Model Analysis of logits. 95% CI = 95% Confidence Interval of the odds ratio.
²Expressed as percentage of cows that contracted mastitis.
³14-d pretreatment period.
⁴Assumes a 252-d standardized treatment period.
⁵Probability of a significance from generalized mixed model analysis. NS: Nonsignificant (P > 0.05).cows; however, the proportion of days medicated was small but was greater for primiparous cows treated with bST. These medications were given 0.33% of days for control primiparous cows and 0.65% of days for bSTtreated cows. These therapies were associated primarily with feet and hock medications (see section on musculoskeletal system).

The percentage of multiparous cows that were given at least one medication was greater for those treated with bST compared with controls, but the percentage of days cows were treated was not affected (Table 5).Average percentages of cows and days treated were 48.2 and 59.6% (P < 0.05) and 1.14 and 1.15% for control and bST-treated cows, respectively. This increase was associated with therapeutic medications, which was further associated with nonmastitis therapies (Table 5). There were 31.5% of control cows and 40.1% of cows treated with bST that received at least one nonmastitis therapy during the entire treatment period (P < 0.05); however, the proportions of days medicated during this period were 0.55 and 0.48%, respectively, which were not significantly different. These treatments were asso-

Table 5. Effect of bST on proportions of cows and days medicated in primiparous and multiparous cows.

¹NS = Nonsignificant (P > 0.05).²Estimates are proportion of total cow treatment days - generalized linear mixed model analysis unless otherwise noted.
³Includes vaccinations or any medication administered for prevention of a condition that was not observed.
⁴Medication administered for a condition that was observed.
⁵Exact test. Values are raw means.
*P = 0.05.

Table 6. Effect of bST on digestive disorders in primiparous and multiparous cows in the postapproval monitoring program.

¹NS = Non significant (P > 0.05). NA = Not analyzed because <3 recorded for each site ?? treatment subclass.
²Generalized linear mixed model analysis. Values are least squares means.
³Exact test. Values presented are raw means.
*P ?? 0.05.
>**P ?? 0.01.ciated primarily with medications for feet and hocks, which was similar to primiparous cows.

The average number of days with at least one milking discarded due to medication withdrawals was calculated using appropriate withdrawal times for every time a medication was administered. There was no effect of bST administration on the average days of discarded milk for primiparous cows, but there were more (P < 0.05) days with discarded milk for multiparous cows. Mean days with discarded milk during the entire treatment period for primiparous cows were 2.1 ± 0.50 and 2.9 ± 0.50 d for control and bST groups, respectively. Mean days with discarded milk for multiparous cows were 2.4 ± 0.54 and 3.7 ± 0.54 d, respectively.

Body Temperature

The incidences of elevated rectal temperatures were analyzed as the numbers of cows or numbers of days during which a temperature of ??39.4??C was recorded and were not affected by administration of bST.

Feed Intake and Digestive Disorders

Episodes of high feed refusal or reduced feed intake were part of the daily observation dataset and are shown in Table 6. Notations of off-feed were rare and were based on observations, not on actual measurements of feed consumption as cows in these herds were group-fed. In multiparous cows, the percentage of control cows with reduced feed intake was 0.3% and bSTtreated cows were 2.8%, which were different (P < 0.05). Similarly, days affected were very low but occurred only 1 d (< 0.01% of d) in controls and 22 d (0.01% of d) inbST-treated multiparous cows, which was different (P< 0.05). There was no association (P > 0.05) betweenuse of bST and diarrhea or digestive disorders in multiparouscows. In primiparous cows, neither number ofcows affected nor days observed for episodes of reducedfeed intake was affected by use of bST. Similar to multiparouscows, the incidences of diarrhea and digestivedisorders were not different between primiparous controlcows and cows treated with bST.

Musculoskeletal System

The effect of bST on musculoskeletal disorders is presented in Table 7. In primiparous cows, there were no significant effects of treatment with bST on musculoskeletal observations or the categories that comprise this system, except for observations of the foot. Percentages of days with foot observations were 0.08% for controls and 0.17% for bST-treated primiparous cows (P < 0.05). These foot observations did not result in an increase in cows or days affected for altered gait or lameness.

For multiparous cows (Table 7), musculoskeletal disorders were observed at least 1 d in 50 control cows and 88 bST-treated cows, which was different (P < 0.01). However, total days observed were only 0.25 and 0.31% of total treatment period days and these values were not affected by treatment. Although significant, days with disorders of the hock occurred less than 0.01% of the total cow-days for both treatment groups (P < 0.05). Percentages of cows with foot observations were 5.6 and 14.3% (P < 0.001) for the control and bST groups, and this accounted for 0.11 and 0.22% of days (P < 0.05). There were more cows treated with bST that had at least 1 d with an altered gait observation during the treatment period, but numerically there were fewer total days in which altered gait was observed for cows treated with bST. These were observed in 5.4 and 9.2% (P < 0.05) of control and bST-treated cows, which accounted for 0.09 and 0.07% of total days, respectively, and cases were of short duration.

Culling

Cows remained on study until dry-off for pregnant cows and 400 d of lactation for open cows. Cows removed before these times were classified as removed from study, and these data are summarized in Table 8. There was no effect of bST use on numbers of animals that died or were removed from the study due to mastitis, lameness, foot problems, digestive problems, other health problems, or low body condition. No control multiparous animals were removed from study due to poor body condition, and four bST-treated multiparous cows were removed for this reason, which accounted for 1.1% of cows. These cows were removed from study but remained in the herd to hasten body condition repletion at the herd owners’ discretion. Three of these animals were removed within the first 100 d of treatment and had other clinical signs, suggesting that body condition was only a secondary reason for removal.

DISCUSSION

An axiom of production animal agriculture is that the health and well being of domestic animals have direct and indirect relationships to their productive ef- ficiency (Collier et al., 1992; Comens-Keller et al., 1995). High-producing dairy cows must be healthy to achieve sustained levels of above-average performance. Herds utilized in this study were all above average in levels of milk yield, management, and performance. Overall, cows in these herds treated with bST remained as healthy as their herd mates despite greater levels of milk production.

Table 7. Effect of bST on musculoskeletal observations in primiparous and multiparous cows in the postapproval monitoring program.

¹NS = nonsignificant (P > 0.05). NA = Not analyzed because <3 recorded for each site ?? treatment subclass.
²Generalized linear mixed model analysis. Values are least squares means.
³Exact test. Values are actual means.
*P ?? 0.05.
***P ?? 0.001.Table 8. Effect of bST treatment for a full lactation on removal from study for primiparous and multiparouscows in the postapproval monitoring program.

¹NS = nonsignificant (P > 0.05). NA = Not analyzed because <3 recorded for each site ? treatment subclass.
²Individual cows can be represented in more than one removal category if multiple reasons given at time of removal.
³Exact test.In a previous study, the use of bST was associated with increased days open for primiparous cows and reduced pregnancy rate for multiparous cows (Cole et al., 1991). In this study, days open and percent pregnant for primiparous and multiparous cows treated with bST were similar to control cows. Also, there were no changes in incidences of abortion, fetal loss, cystic ovaries, or twinning in primiparous or multiparous cows treated with bST. Cole et al. (1991) reported on reproductive performance of 814 cows treated with bST in preclinical trials, where doses and routes of injection varied considerably. They indicated that length of the breeding period and level of milk production had a greater influence on reproductive performance than bST.

The ovary is a target organ for somatotropin (Lucy et al., 1993, 1994), and somatotropin may have beneficial effects on reproductive performance (Lucy et al., 1994; Stanisiewski et al., 1992). Moreira et al. (2000) demonstrated that when estrus detection is eliminated by use of a timed AI program, bST-treated cows had improved reproductive performance compared with control cows. Lucy et al. (1994) found that treatment with 25 mg/d of bST extended the life of normal corpus luteal function. Additionally, the initiation of the second follicular wave was earlier. Kirby et al. (1997) found that bST (500 mg/ 14 d) increased the incidence of undetected estrus. They suggested that while differences in steroid concentrations were not a causative factor in lack of estrus, changes in energy dynamics with increased milk production may have been involved. In support of this concept, low doses of bST, with concomitantly lowered milk production responses, improved reproductive performance (Stanisiewski et al., 1992). Taken together, these findings suggest that nutritional management to minimize shifts in energy balance and improved methods of estrus detection are important management practices that can result in no effects of increased milk production due to bST on reproductive performance.

Use of bST was associated with a greater incidence of twinning (Cole et al., 1991) in a previous clinical study in which bST was administered intramuscularly. But, in a second clinical trial, where bST was administered SC, there was no effect of bST treatment on twinning (Cole et al., 1991). In the current study, twinning was also unaffected by bST use. Data from these studies indicate that when bST was used according to the product label, there was no affect of bST treatment on the incidence of twinning. Whether the increased incidence of twinning observed in the first study was due specifi- cally to intramuscular administration of bST cannot be determined conclusively.

Although not significantly different, the days open obtained in this study would result in a calving interval of 420 d or 14.0 mo compared with an average of 410 d or 13.7 mo in control cows. The additional 10 d of lactation for bST-treated cows was more than compensated for by an average of 932 kg of additional milk per cow per lactation across the 28 herds.

Mastitis incidence was unaffected in either parity group treated with bST in this study. Overall, the odds ratio for mastitis (controlled for parity) in bST-treated animals was 1.23. This ratio is lower than the odds ratios estimated from previous studies (Collier, 1993). In those studies, the risk of mastitis was estimated to be approximately one additional case per cow every 10 lactations. Thus, under actual conditions of use, the incidence of mastitis was lower than had been predicted from the preclinical studies in university herds. There was no significant effect of bST use on the incidence of mastitis. Even though mastitis incidence in cows treated with bST was not corrected for greater days at risk or increased milk yields compared with control cows (White et al., 1994), these data are in agreement with results from a study conducted at four commercial farms where mastitis incidence was unaffected by bST (Judge et al., 1997).

Increased use of medications for nonmastitis-associated treatments was detected in cows treated with bST. As indicated earlier, mastitis medications were associated with therapeutics and not preventive medications. Further examination of these data indicated that the majority of medications used for therapies were not associated with mastitis. These medications included both nonmicrobial (foot baths) as well as microbial (antibiotic) treatments of acute foot disorders.

Digestive disorders were minimal in cows treated with bST. Days bST-treated multiparous cows were recorded as off-feed slightly increased, but days for primiparous cows were not affected. These days were not associated with major digestive problems such as displaced abomasum or metabolic diseases.

An analysis of daily observations and veterinary observations for the musculoskeletal system were in agreement and indicated an increase in foot and hock problems for cows treated with bST (Table 7). Foot and hock disorders included abrasions, ulcers, abscesses, and sores. Although the incidence of these events was increased in both primiparous and multiparous cows, there was no associated increase in laminitis for either parity group.

Analysis of data on removal of cows from the study and from the herd indicated that bST had no effect on reasons for removal of animals from the herd or from the study. Since adoption of bST for commercial use in the United States, analyses of DHIA data for 340 commercial dairy herds in the northeastern United States indicate that herds that adopted bST for 4 yr of continuous use did not differ in culling compared with herds that never used bST (Bauman et al., 1999). Similarly, in a study of 32 Midwest dairy herds, culling was not affected by use of bST (Ruegg et al., 1998).

In summary, health problems detected in cows treated with bST under commercial conditions were typical health events that normally occur in dairy herds. All of the conditions noted are managed routinely by accepted management practices within high-producing herds. Mastitis incidence was less than estimated from preclinical studies (Collier, 1993) and reproductive performance was improved compared with preclinical studies (Cole et al., 1991). Supplemented cows had a slight increase in foot disorders, resulting in more medications, but these disorders were minor and not associated with lameness. Thus, there was no indication that health problems were exacerbated in cows treated with bST under commercial conditions.

ACKNOWLEDGMENTS

We wish to thank the following people for their invaluable assistance in data collection and analysis: R. Hoffman, P. Olsson, M. Aubuchon, S. Piazza, S. Bettis, E. Plunkett, M. McCrate, T. Loesch, T. Curran and R. Sorbet. Additionally, appreciation is extended to the herd veterinarians that contributed to the health observations in this study.

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Source: Journal of Dairy Science
Author: Monsanto Dairy Group

Milking Frequency Effects In Early Lactation

Geoff Dahl, Extension Dairy Specialist, University of Illinois

Take home messages:

Introduction

Increasing the frequency of milk removal increases milk production in cattle as it does in many species (6). Indeed, this is a common management approach to maximize production per cow and fully optimize capital investment in machinery and facilities. One obvious drawback is the increase in variable costs, mainly labor, required to reap the higher yield of milk. Traditionally, this technique has been employed throughout lactation, but recent evidence suggests that frequent milking appropriately timed within the lactation cycle can have persistent effects, and thus eliminate some of the higher costs while maintaining higher yields. This paper reviews the physiology behind the response, expected outcomes from increased milking frequency, and proposes easily adopted strategies to exploit frequent milking during early lactation to improve overall yields.

Increasing the number of milkings from 2 (2X) to 3 (3X) each day increases production in cattle across a range of production levels (4). It is of interest that this appears to be a fixed response. That is, cows producing 40 pounds/day when milked 2X will increase production about 8 pounds/day when shifted to 3X; cows producing 80 pounds/day would also increase production by 8 pounds/day. So management decisions based on percentages can be deceiving, as the absolute response is not very different across production levels yet the percentage response actually decreases as average milk yield increases!

Research on Milking Frequency in Early Lactation

Israeli workers (1) observed higher production in cows milked 6X relative to 3X during the time that milking frequency was increased (Table 1). However, there was a striking persistency of the production response following a return to 3X from 6X. Cows milked 6X for the first 42 days of lactation continued to yield more milk even after milking frequency was reduced to 3X. Milk composition, though somewhat low, was not different between groups. Relative to those milked 3X, dry matter intake was increased in 6X cows. Cows milked 6X experienced a longer delay in return to positive energy balance and a longer time at a body condition score below 2.5 than those cows milked 3X. Collectively, cows milked 6X for only the first 6 weeks in milk had greater milk yield and feed efficiency for the entire lactation when compared with those milked 3X.

Table 1. Daily milk, components and lactation yield of cows milked 3X or 6X for the first 42 days of lactation and then 3X for the remainder of 305 day lactation. Daily yields were recorded during treatment (week 1-6) and after treatment for 12 weeks (week 7-18). Complete lactation records were from DHI testing (305 d). Data from Bar-Peled et al., 1995 (1).

aSignificantly greater than 3X controls, P<.05

A recent experiment in Maryland (5) confirmed under field conditions that milking cows 6X in early lactation produced persistent improvements in milk yield even after cows returned to 3X. For the first 42 days of lactation, cows were milked 3X at 8 hr intervals or 6X at approximately 4-5 hr intervals. After d 42 all cows were milked 3X for the rest of the study which lasted through 38 weeks of lactation. Relative to those milked 3X, multiparous cows milked 6X produced more milk throughout the study. On a percentage basis, milkfat was unaffected by treatment whereas milk protein was lower; protein and fat yield, however, were improved overall by 6X treatment. In addition, there was no adverse effect on reproduction as conception rate to the first synchronized ovulation was not different between groups.

Table 2. Milk, components and conception rate of cows milked 6X or 3X for the first 42 days of lactation. Data from Henshaw et al., 2000 (5).

aResults from synchronized breeding at 69 to 76 days in milk.
bSignificantly greater than 3X controls, P<.01.
cSignificantly lower than 3X controls, P<.05.
Physiology Behind the Response

There are two physiologic explanations for the impact of frequent milk removal on production. The first is the potential physical effect of increasing intramammary (IM) pressure to reduce the rate of milk synthesis within mammary epithelial cells. The IM pressure hypothesis suggests that physical forces of milk accumulating within the alveoli causes a compression of the secretory cell and this in turn reduces cellular metabolism and milk component synthesis. Indeed, the milk synthesis rates are fastest immediately after milking and decline with time to about 36 hours when secretion essentially stops. More recently a hormone-like factor, secreted by mammary epithelial cells, has been implicated as a suppressor of milk synthesis. This feedback inhibitor of lactation (FIL) acts in a self-limiting fashion to reduce milk synthesis. As milk accumulates in the gland between milkings, so does FIL accumulate, and thus it increasingly suppresses milk component production by the very cells that secrete it. Both IM pressure and FIL would be reduced by more frequent milking, and increases in milk yield would result relative to less frequent milking. However, these mechanisms may not be responsible for the impact of frequent milking during early lactation, as those responses persist in the absence of continued high frequency milk removal.

A more general response to milking frequency is the effect on secretion of prolactin. Circulating concentrations of prolactin increase acutely after each milking. Evidence from our work with photoperiod, another factor that can be used to manipulate prolactin, suggests that an increase in prolactin early in lactation may increase the number of secretory cells within the mammary gland for that lactation (3). It appears that in mammary cell growth reaches a peak in late pregnancy but continues into the first few weeks of lactation. Because milk production is a function of the number of mammary secretory cells (2), starting lactation with a greater number of secretory cells should increase yield. More importantly, this increase would be expected to persist because cell loss is a constant throughout lactation. Prolactin is thought to have a stimulatory effect on mammary cell development, and the higher prolactin in response to more frequent milking early in lactation may thus explain the persistent effect of this practice on yield.

Table 3. Predicted milk response and potential economic benefit from derived from milking all cows 4X for the first 21 days of lactation in a 120 cow herd.

aLabor cost of $20/hour; 4 hours/cow/lactation.
bDry matter at $.06/lb; 0.5 lb DM for each lb of milk increase.
cCost for supplies for an extra 42 milkings distributed over entire 305 day lactation.
dMilk at $11.00/cwt.
eEstimate is for each day of a typical 305 day lactation.
fCalculated from profit/cow for 305 day lactation for 120 cow herd.

Management suggestions

Increasing the frequency of milking early in lactation is simple to implement. In a 2X or 3X scheme, fresh cows can be milked first and last at each milking to achieve either a 4X or 6X frequency. While this may not yield exact 6 or 4 hour intervals between each milking, it is likely to provide appropriate stimulation such the persistent increases in milk production are observed. The question then becomes one of duration – that is, how long should the producer milk at increased frequency? Evidence from recent experiments suggests that the increased frequency need only be imposed for the first 21 days of lactation. For example, if typically cows are milked 2X at 12 hr intervals, then fresh cows only could be milked at the beginning and end of each milking. In a herd of 120 milking cows, estimate that 10 cows would calve each month, so at any time 7-8 cows would be milked 4X. This would not require any additional labor to be hired, yet the research indicates that an amount of production close to continuos 3X milking can be achieved. Table 3 presents expected returns on adopting early lactation frequent milking in a typical 120 cow herd. Assuming a 6 pound/cow/day response yields an additional potential profit of $97.60/cow with a milk price of $11.00.

References

1. Bar-Peled U., Maltz E., Bruckental I., Folman Y., Kali Y., Gacitua H., Lehrer A. R., Knight C. H., Robinzon B., Voet H., Tagari H. 1995. Relationship between frequent milking or suckling in early lactation and milk production of high producing dairy cows. J Dairy Sci. 78:2726-2736.

2. Capuco A. V., Wood D. L., Baldwin R., Mcleod K., Paape M. J. 2001. Mammary cell number, proliferation, and apoptosis during a bovine lactation: relation to milk production and Effect of bST. J Dairy Sci. 84:2177-2187.

3. Dahl G. E., Auchtung T. L., Kendall P. E. 2001. Environmental effects on endocrine and immune function in cattle. Reproduction Suppl. 59:In Press.

4. Erdman R. A., Varner M. 1995. Fixed yield responses to increased milking frequency. J. Dairy Sci. 78:1199-1203.

5. Henshaw A. H., Varner M, Erdman R. A. 2000. The effects of six times a day milking in early lactation on milk yield, milk composition, body condition and reproduction. J. Dairy Sci. 83(Suppl. 1):242. Abstract #1020.

6. Pearson R. E., Fulton L. A., Thompson P. D., Smith J. W. 1979. Three times a day milking during the first half of lactation. J. Dairy Sci. 62:1941-1950.

Source: University of Illinois
Author: Geoff Dahl

Herd Management Opportunities for Decreasing the Nitrogen Load on the Dairy Farm
Charles G. Schwab, University of New Hampshire, Durham, and Rick A. Kohn,University of Maryland, College Park

INTRODUCTION

Dairy farming in the United States faces two major challenges, an economic challenge and an environmental challenge. The solution to the economic challenge continues to be one of becoming more efficient. Two ways of becoming more efficient has been to increase milk production per cow (i.e., rolling herd average) and to increase cow numbers.

Unfortunately, increasing cow numbers on the farm has contributed to the environmental challenge. From an environmental point of view, in regard to nitrogen, there are two major areas of increasing concern. The first is the pollution of surface water (e.g., streams, lakes, wetlands and estuaries) and ground water from excessive land application of nitrogen. Some nitrogen may be lost with runoff water after a rainfall (Baker and Senft, 1993). Nitrogen incorporated into the soil in excess of crop needs is eventually lost to ground water (Joshi et al., 1994).

The second environmental concern is the volatilization of manure nitrogen into ammonia and its emission into the air. Ammonia contributes to acid rain that endangers forests and lakes (Luebs et al., 1973). Also, some nitrogen may be lost from the farm by conversion to atmospheric N2 in a process known as denitrification (Thompson et al., 1987). Studies indicate that up to 50% of manure nitrogen can be lost to the atmosphere during handling, storage, and land application (Borton et al., 1995; Hutson et al., 1998). The problem is that 60 to 80% of the nitrogen imported onto most dairy farms in the form of feed and commercial fertilizers stays on the farm. The reason for this is that only about 30% of the nitrogen consumed by lactating cows in high producing herds is transferred to the milk, the remainder is excreted in feces and urine (Wilkerson et al., 1997).

It is becoming increasingly clear that how we handle nitrogen and other nutrients (particularly phosphorus) on the dairy farm will affect both farm profitability and the number of animals per unit of cropland that will be allowed. The challenge is to find the appropriate balance between environmental stewardship and an efficient,economically viable dairy production system.Thus, the goal is to increase dairy farm efficiency and profitability while maintaining or reducing nutrient losses to the environment.

The purpose of this presentation is to compare the potential impact of some of the newer technologies in dairy cattle feeding and management on reducing nitrogen losses per unit of milk produced from typical dairy farms.

These technologies are grouped into those aimed at improving biological efficiency through increased production and those aimed at providing a better match of protein sources with the animal’s needs. The reader is referred to other publications that focus on manure, soil, and crop management practices as strategies for reducing nitrogen losses to the environment (e.g., Borton et al., 1997; Joshi et al., 1994; Van Horn et al., 1994).

Source: Monsanto Dairy Group
Author: Schwab,  Durham, Cohn