禁漫天堂

J.W. Smith¹
A.M. Chapa¹
W.D. Gilson¹
L.O. Ely¹

• Introduction
• Methods and Procedures
• Regional Distribution of Sire Usage by Milk Production Level
• Evaluation Using Mature Equivalents
• Evaluation of Predominately AI Herds
• Conclusion
• References
• Tables

Introduction

The Dairy Records Management Systems (DRMS), Raleigh, North Carolina, provides information and resources for use in dairy herd management analysis. The Dairy Herd Improvement (DHI)-202 Herd Summary Report is a valuable source of information when evaluating milk production. Many herd management strengths and weaknesses including genetic evaluation of the herd can be revealed by using herd summary data.

The level of milk production is affected by both genetic and environmental (non-genetic) factors. Genetics accounts for about 25 percent of the variation in milk production with environmental factors making up the remaining 75 percent. Environmental factors include weather conditions, feed quantity and quality, herd health, reproductive efficiency and other management factors. Whereas the genetic potential of a herd of milking cows is fixed, environmental factors often can be changed or modified. For example, the quality of feed might be increased or the effects of heat stress might be reduced by using fans. Both of these environmental changes should result in more milk production. However, if cows are producing at their maximum genetic potential, management changes will not result in higher production.

The genetic makeup of an individual cow will affect her ability to consume feed and efficiently convert that feed into milk. The upper limit on a herd's production is set by the genetic makeup of the herd. In some instances, this may severely restrict productivity regardless of the level of management. Genetic ability of the herd may restrict productivity in some herds if genetics rather than management or feeding is limited. Evaluation of a herd's genetic information can help ensure that genetic ability is not the factor that limits production.

A thorough herd evaluation requires knowledge of management practices and herd genetic potential. The Dairy Records Management Systems DHI 202 Herd Summary Report provides information on herd genetic values that can aid in the evaluation of a herd's milk production potential. A complete evaluation should also include other production and management information. Georgia Extension Service Bulletins 1193 and 1194 provide benchmark values for production and somatic cell count evaluations respectively. (1, 2)

The purpose of this bulletin is to provide genetic benchmarks for Holstein herds processed by DRMS. Examples for using and applying benchmark values are provided. However, this bulletin should be viewed primarily as a comprehensive resource of genetic benchmark values. These values will be useful to dairy producers, dairy managers, consultants, veterinarians and agri-business representatives as a first step in the evaluation of the genetic program of a herd.

Methods and Procedures

Herd Summary information was obtained from DRMS, Raleigh, North Carolina, for Holstein herds last tested in November and December, 2000. Data analysis was performed using the Statistical Analysis System (3). Since research has shown that management variables differ by region of the country, herd size and milk production level, values are analyzed for Northeast, Midsouth, Midwest and South regions (Figure 1). Within regions, genetic variables were listed by herd size or by rolling herd averages for milk production with values listed, limited to herds with a minimum of 25 cows and a minimum milk production for herds included in percentile tables of 12,000 pounds. Percentile rankings were restricted to herds using the milk, fat and protein (MFP) predicted transmitting ability (PTA) option and less than 30 percent non-AI sires. Previous analysis had indicated that the MFP PTA option was selected by over 96 percent of the herds.

Figure 1. U.S. Map Showing Four Regions

Regional Distribution of Sire Usage by Milk Production Level

Tables 1 through 4 show the distribution of sire usage by region and level of herd milk production. The overall trend across regions is an increase in use of AI sires (% Proven Sires plus % Young Sires) and a decrease in herd sire usage as rolling herd average increases. This demonstrates the importance of AI usage in relation to herd production. These tables also provide a means of evaluating the relative use of proven sires compared to young sires. Young sires are normally considered an inexpensive means of improving the genetics of a herd if used judiciously. Their use also guarantees a steady supply of new proven sires from which to select. For most herds, a distribution of 75-80 percent proven sires and 20-25 percent young sires is recommended. This distribution helps insure the availability of genetically superior sires.

Evaluation Using Mature Equivalents

Herds using a high percentage of natural service herd sires are difficult to evaluate genetically since no measure of sire genetic merit is usually available. One method of evaluating natural service herds as well as herds using AI sires is to examine the mature equivalent (ME) production of cows by lactation group. Mature equivalent records are lactation records that have been adjusted for age at freshening, frequency of milking and season of the year at calving. These records do not predict how much a cow or group of cows will produce in the future. Mature equivalent records simply estimate how much a cow or group of cows would have produced if she (they) were of mature age, calved during an average month, and were milked twice a day.

Mature equivalent production values by lactation groups and by region and level of milk production are shown in Tables 5 through 8. The ME lactation ratios provide the opportunity to compare average ME production between lactation groups. One might expect the highest ME production for first lactation cows since they should posses the highest genetic merit. When comparing lactation groups, however, second lactation cows tend to have higher MEs since they have been selected for production more intensively compared to first lactation cows.

The ME production ratios between lactation groups provide a convenient method of comparing the relative difference between groups. Herds with ratios which differ significantly from those in the tables should be evaluated further regarding the reasons for the deviations. Factors to consider are variations in culling rates, genetic merit and management among the three lactation groups. Health problems affecting a specific lactation group can also contribute to differences.

As an example, Mr. I.M. Producer in New York is concerned with the production of his first lactation cows although his rolling herd average is 24,321 pounds. The average MEs for his cows are 25,224, 27,826 and 26,327 pounds for first, second and third or more lactation cows. The ratio for the first lactation cows' ME to second lactation cows' ME production is 0.91 (25,224/27,826). The ratio of his first lactation cows' ME to third lactation cows' ME is 0.96 (25,224/ 26,327). Based on his production level, the average ME production of his first lactation cows is lower than expected (25,224 pounds vs 27,033 pounds) (Table 5, page 8).

Furthermore, when comparing second lactation and third and more lactation cows, both ratios were lower than expected (Table 5). This indicates that first lactation cows are not producing at expected levels relative to older cows. Determining the specific reasons for these differences will require further evaluation as noted previously.

Evaluation of Predominately AI Herds

The most accurate genetic evaluation is possible only when predicted transmitting ability (PTA) values are available for a high percentage of the cows in a herd. A PTA is an estimate of the genetic superiority or inferiority of an animal that is transmitted by a sire or dam to its offspring. PTA values are calculated by the USDA using production information obtained from Dairy Record Processing Centers.

PTA values for production, longevity and somatic cell score are combined into an index called Net Merit$. The Net Merit$ index combines genetic evaluation for somatic cell score, productive life, udder composite, feet and legs, body size, and product value adjusted for feed costs. This combination of traits and economic values makes selection of this index a good choice for most herds.

Not all cows in a herd necessarily have a PTA calculated. In order to obtain a PTA calculation, cows must be properly identified by sire and dam and cows must have at least one test completed by 40 days of the lactation.

The first step in evaluation is to determine the percentage of cows with a calculated PTA for Net Merit$. Tables 9 through 12 show the percentage of cows with a PTA calculated by region, herd size, and lactation group. An individual dairy producer's DHI-202 Herd Summary Report lists only the actual number of cows in the herd with PTA values. These numbers must be converted to a percentage for comparison purposes. To convert to a percentage, divide the number of cows in a specific lactation group that have a PTA by the total number of cows in that group and multiply by 100.

There is no specific number or percentage of cows with a PTA required to perform a genetic evaluation of a herd. However, if the percentage of cows with a calculated PTA is below about 50 percent, an analysis is probably less meaningful. Herds with more than 50 percent of the cows with a calculated PTA should continue to the next step.

PTA values for each lactation group are shown by region and herd size in Tables 9 through 12. Accurate identification of an animal's parentage (sire and dam) is essential for a PTA calculation. The percent cows identified by sire and dam also are also listed in Table 9 through 12 by region and herd size. If the percentage of cows identified is low, the percentage with a PTA calculated will also be low. The level of identification of replacement heifers can be similarly evaluated. This provides the opportunity to evaluate identification when animals are young. If proper identification is not available when heifers are young, it is unlikely to be available when they calve. The percent proven sires in a herd and the percentile rank of proven sires are shown in Tables 9 through 12. This information can help evaluate the genetic merit of sires used in a herd.

For example, Mr. I.M. Producer has a herd of 282 cows in New York and calculates that 75 percent of his first lactation cows have a PTA. He refers to Table 9 (250 to 349 cows). The 75 percent for his first lactation cows is above the 70 percent in the table, which places his herd in the 90^th percentile.

Mr. I. M. Producer continues the PTA evaluation for the first lactation cows in his herd. The average PTA (Net Merit$) for his first lactation cows is 97. Referring again to Table 9, he notes this value is at the 50^th percentile. His first lactation cows are in the top 50 percent of all herds of similar size in the Northeast region. A similar procedure would be followed to analyze percent proven AI sires and the percentile rank of AI sires.

Table 13 shows the percentage of cows with a PTA calculated by region and by production level. The average PTA for cows by lactation group and by region and production level are in Table 14. Values in both tables show the relationship between PTA level and average herd production. High producing herds tend to have a higher percentage with a PTA calculated. These herds also have cows with a higher average PTA. The average PTA values increase as average herd production increases and as the lactation number decreases.

An analysis of the genetic benchmarks can help determine if productivity may be limited by genetic ability. Herds below the 50^th percentile in numerous categories may be limited by genetic ability and managers should consider improving the quality of the sires being used. Moreover, levels below the 50^th percentile in specific lactation groups indicates that genetic ability may be limiting the productivity of those groups. However, many herds even in the upper 50^th percentile may have opportunities for significant genetic improvement.

Conclusion

The genetic makeup of a herd dictates the upper limit for production and performance of a herd. Actual production is determined by genetics and environmental (non-genetic) factors. Evaluating a herd's genetic benchmarks indicates whether a herd is performing at its genetic potential. If herd genetic values are lower than expected, more detailed analysis must be performed to determine whether genetic or environmental factors are limiting performance.

References

• Dairy Production and Management Benchmarks, Cooperative Extension Service, 禁漫天堂 College of Agricultural and Environmental Sciences, Bulletin 1193, February, 2001.
• Somatic Cell Count Benchmarks, Cooperative Extension Service, 禁漫天堂 College of Agricultural and Environmental Sciences, Bulletin 1194, January, 2001.
• SAS/STAT User's Guide: Statistics, Version 6.12. 1996. SAS Inst., Inc., Cary, NC.
• DHI-202 Herd Summary Fact Sheet A-1. 1997. Dairy Records Management Systems, Raleigh, NC.

See the PDF version of this publication for tables 9 through 14.

• Table 9. Genetic Measures in the Northeast Region by Herd Size
• Table 10. Genetic Measures in the Midwest Region by Herd Size.
• Table 11. Genetic Measures in the Midsouth Region by Herd Size.
• Table 12. Genetic Measures in the South Region by Herd Size.
• Table 13. Percent of Cows with a Net Merit$ Calculated by the Animal Improvement Programs Laboratory by Region by Production Level.
• Table 14. Average Net Merit$ for Cows by Region and Production Level.

Status and Revision History
Published on Feb 01, 2002
Published on Feb 03, 2009
Published with Full Review on Mar 13, 2012