usda logo
NM$2 (7-03)

Net merit as a measure of lifetime profit: 2003 revision

P.M. VanRaden1 and A.J. Seykora2
1Animal Improvement Programs Laboratory, ARS-USDA, Beltsville, MD 20705-2350
301-504-8334 (voice) ~ 301-504-8092 (fax) ~ ~

2Department of Animal Science, University of Minnesota, St. Paul 55108-6118
612-624-3448 (voice) ~ 612-625-1283 (fax) ~ ~

Superceded by 2006 Revision

Updated economic values || Net merit calculation || Genetic parameters || Expected genetic progress || Calving ease || Daughter pregnancy rate || Yield traits || Productive life || Somatic cell score || Conformation composites || Lifetime profit || History of net merit || Acknowledgments

Important new traits have been added since the previous revision of net merit (NM$) in August 2000. The maternal grandsire (MGS) effect for calving ease, which is called daughter calving ease (DCE), became available in August 2002 and allows breeders to improve maternal effects in addition to service sire effects for ease of calving (SCE). Daughter pregnancy rate (DPR) evaluations, which became available in February 2003, allow producers to select directly for fertility in addition to selection for overall health using productive life (PL). Economic values of other traits also have been updated. Milk component prices were revised to make cheese merit (CM$) and fluid merit (FM$) useful for more producers. Those indexes each estimate lifetime profit based on incomes and expenses obtained in cooperation with Project S-1008, Genetic Selection and Crossbreeding to Enhance Reproduction and Survival of Dairy Cattle, collaborative research efforts of the Southern Association of Agricultural Experiment Station Directors.

Updated economic values

New economic values for each unit of predicted transmitting ability (PTA) and relative economic values of traits will be implemented with August 2003 evaluations:

Trait Units Standard
Value ($/PTA unit) Relative value (%)
Protein Pounds 25 4.81 6.68 1.33 33 36 9
Fat Pounds 32 2.54 2.54 2.54 22 18 22
Milk Pounds 832 0 -.056 .104 0 -10 24
Productive life Months 1.5 26 26 26 11 9 11
Somatic cell score Log .20 -166 -166 -166 -9 -7 -9
Udder Composite .78 33 33 33 7 6 7
Feet/legs Composite .88 15 15 15 4 3 4
Body size Composite .94 -12 -12 -12 -3 -2 -3
Daughter pregnancy rate Percent 1.4 17 17 17 7 5 7
Service sire calving difficulty Percent 1.7 -5 -5 -5 -2 -2 -2
Daughter calving difficulty Percent 1.4 -5 -5 -5 -2 -2 -2

The SD listed above are for true transmitting abilities (TA) in a hypothetical unselected population. The SD of TA for NM$, CM$, and FM$ are all estimated to be $191. An economic value is the added profit caused when a given trait changes by one unit and all other traits in the index remain constant. For example, an economic value for protein is determined by holding pounds of milk and fat constant and examining the increase in price when milk contains an extra pound of protein. The genetic merit for each trait of economic value can be predicted from both direct and indirect measurements (multitrait methods). The economic value of a trait may change when other correlated traits are added into the index. Selection of animals to be parents of the next generation should be more accurate if all traits of economic value are included in NM$.

Relative values for each trait are obtained by multiplying the economic value by the SD for true transmitting ability, and then each individual value is divided by the sum of the absolute values to express each relative value as a percentage of total selection emphasis. The only breed with calving ease evaluations was Holstein until Brown Swiss evaluations began in February 2005. For the remaining breeds, relative values of other traits each increase by a factor of 1.04 when the 4% of emphasis on SCE and DCE is excluded. Due to rounding, relative values change to 35% for protein, 23% for fat, and -10% for SCS in NM$ for the other breeds.

Net merit calculation

Calculation of NM$ and reliability (REL) of NM$ can be demonstrated using the following example Holstein:

Trait PTA REL (%)
Protein +70 90
Fat +80 90
Milk +2,000 90
Productive life +2.5 60
Somatic cell score 3.00 (- 3.10) 75
Udder +1.5 80
Feet/legs +.5 75
Size -1.0 85
Daughter pregnancy rate +.3 55
Service sire calving difficulty 6 (- 8) 90
Daughter calving difficulty 7 (- 8) 60

The PTA's for each trait are multiplied by the corresponding economic value and then summed. A mean of 8% must be subtracted from both SCE and DCE PTA's for Holsteins (5% for Brown Swiss) and a mean of 3 must be subtracted from PTA for somatic cell score (SCS) for all breeds. After subtracting 3 from PTA SCS and 8% from SCE and DCE, the NM$ for this example animal is +$711, CM$ is $730, and FM$ is $675. Calculation of NM$ also can be expressed in matrix form:

NM$ = a'u,

where a contains the economic values for the 11 PTA traits and u contains the trait evaluation. Means for SCS and for calving difficulty are removed from the corresponding elements of u. Calculations are the same for males and females with one exception: calving ease PTA are not available for cows because of the sire-MGS model, and pedigree indexes are substituted, calculated as .5 sire + .25 MGS + .125 maternal great grandsire, etc., for all generations of the maternal line, with breed average replacing any unknown ancestors.

The REL of NM$ can be approximated as the REL of yield multiplied by .85 plus the REL of PL multiplied by .15, or 90% (.85) + 60% (.15) = 86%. Actual REL of NM$ is computed using matrix algebra from REL of the eleven traits and genetic correlations among those traits. The REL of NM$ is the variance of predicted NM$ divided by the variance of true NM$:

REL NM$ = r'Gr/v'Gv.

where r contains the relative economic values multiplied by the square root of each PTA trait's REL, G contains the genetic correlations between the 11 PTA traits, and v contains the relative economic values for the traits.

Genetic parameters

Genetic correlations were calculated among the 11 PTA traits:

PTA trait PTA trait
Milk Fat Protein PL SCS Size Udder Feet/
Milk .30* .45 .81 .13 .20 .01 -.20 -.02 -.35 -.05 -.03
Fat   .30 .60 .12 .15 .01 -.20 -.02 -.32 -.08 -.02
Protein     .30 .15 .20 .01 -.20 -.02 -.34 -.07 -.01
PL       .085 -.35 -.04 .30 .19 .59 -.19 -.24
SCS         .12 -.11 -.33 -.02 -.30 .04 .09
Size           .40 .26 .22 -.08 .22 .09
Udder             .27 .10 .03 .06 -.05
Feet/legs               .15 -.04 .04 .03
DPR                 .04 -.16 -.20
SCE                   .09 .47
DCE                     .06
*Holstein heritabilities in blue on diagonal; heritabilities for other breeds are the same except for size (.35), udder (.20), and, for Jerseys and Brown Swiss, yield traits (.35).

For all breeds, genetic correlations of the linear type composites with yield, PL, and SCS were computed from literature values for Holstein linear type traits (Short and Lawlor, 1992, Journal of Dairy Science 75:1987; Schutz et al., 1993, Journal of Dairy Science 76:658; Weigel, 1993, Ph.D. thesis). Genetic correlations among the type composites were calculated from official Holstein genetic correlations for linear type traits (Misztal et al., 1992, Journal of Dairy Science 75:544). Correlations of DPR and PL with several other traits were obtained through REML, and the remaining correlations were obtained from correlations among PTA of bulls with high REL.

Expected genetic progress

Correlations of PTA's for each trait with NM$, FM$, or CM$ were obtained from progeny-tested Holstein bulls born from 1994 through 1997. Bulls were required to have a REL of at least 80% for milk yield and an evaluation for each trait in the index. Correlations with the previous NM$ formula used since August 2000 are shown for comparison:

PTA trait Correlation of PTA with index Expected PTA
Expected genetic trend/decade
Previous NM$ NM$ CM$ FM$ NM$ NM$
Protein .81 .74 .74 .71 3.9 78
Fat .68 .67 .67 .64 4.8 96
Milk .68 .58 .49 .72 119 2380
Productive life .51 .58 .56 .58 .24 4.8
Somatic cell score -.35 -.38 -.37 -.39 -.022 -.44
Udder .19 .22 .21 .22 .07 1.40
Feet/legs .17 .16 .16 .16 .05 1.00
Size -.10 -.10 -.10 -.09 -.03 -.60
Daughter pregnancy rate .00 .15 .17 .12 .05 1.0
Service sire calving difficulty -.13 -.23 -.23 -.22 -.13 -1.3
Daughter calving difficulty -.11 -.21 -.20 -.22 -.08 -1.6

The new indexes have higher correlations with several fitness traits, especially fertility and calving ease, but give somewhat reduced progress for protein and milk yields. Expected PTA progress was obtained as the correlation of PTA with NM$ multiplied by the SD of PTA multiplied by .34, which is the annual trend in SD of NM$. The SD of PTA (not shown) are generally lower than the SD of true TA given in the first table because of selection and because REL are < 1. Genetic trend, or change in breeding value, equals twice the expected progress for PTA. Thus, multiplication of annual PTA gain by 20 gives expected genetic progress per decade. One exception is that SCE and DCE jointly affect calving ease progress. The annual SCE gain multiplied by 10 plus the annual DCE gain multiplied by 20 gives the total gain per decade of (-1.3 - 1.6) = -2.9% difficulty. This rapid progress will be acheived only if Holstein breeders stop selecting for large size, which has contributed to the poor SCE of that breed.

Economic values for each trait are derived in the following sections, beginning with the new traits added to the merit indexes in this 2003 revision.

Calving ease

Each lactation begins with a birth, and a difficult birth reduces production, delays reproduction, and in some cases kills the calf or the cow. For U.S. Holsteins, service sire rankings for calving ease have been available since 1978 (Berger, 1994, Journal of Dairy Science 77:1146). Selection for easy calving was not widely practiced because most benefits occur from mate assignment rather than breed improvement and because MGS effects differ from sire effects. Direct and maternal (or MGS) evaluations are now available in the United States (Wiggans et al., 2002, Proceedings of the 7th World Congress on Genetics Applied to Livestock Production 32:561) and for most major Holstein populations around the world. Routine international rankings are expected soon (Pasman et al., 2003, International Bull Evaluation Service Bulletin 30:59). Thus, calving ease seems easy to include in both selection and mating programs.

Values of calving ease traits were derived by many researchers for use in selection indexes, beginning perhaps with Philipsson et al. (1979, Livestock Production Science 6:111). Dekkers (1994, Journal of Dairy Science 77:3441) examined selection and mating programs in detail and provided an excellent summary of previous literature. Indexes for U.S. producers were proposed by Balcerzak et al. (1989, Journal of Dairy Science 72:1273) and by Dematawewa and Berger (1995, Iowa State University Dairy Report DSL-27). As of August 2003, national selection indexes include calving ease and stillbirth traits for 5 of the 12 largest Holstein populations that participate in the International Bull Evaluation Service (2003, National GES Information). Proportion of total emphasis is 3% for Germany, 4% for United States, 6% for Denmark, 10% for The Netherlands, and 12% for Sweden.

Most research studies concluded that although selection for just sire effects provides some benefit, selection for both direct and maternal effects provides greater benefits; in addition, direct effects have higher relative values than maternal effects because of the larger heritability of direct effects. Effects for MGS include maternal effects as well as half of direct effects and thus have higher value than maternal effects alone as studied previously. Dekkers (1994, Journal of Dairy Science 77:3441) obtained a total value for the two calving ease traits of about .10 relative to yield if the index also contained fertility and longevity and a value of .16 if it did not. Studies differed as to whether yield losses in the next lactation should be included in the value of calving ease.

Each calf receives half of its sire's and dam's genes and a maternal effect of the dam (or surrogate dam for an embryo-transfer calf). Evaluations of yield, PL, and cow fertility already account for calving difficulty losses due to the combined maternal effect and genetic contribution of the dam to the calf but not for a bull's contributions to those traits of his mates. In fact, his PTA is corrected for merit of mates, and any damage to the mates would make his own offspring appear better by comparison. Thus, the sire's direct effect should include losses for all traits, whereas the MGS effect should only include calf death, veterinary, and farmer labor expenses. Unfortunately, some cow deaths are not recorded if the cow does not survive to the first test day and thus are not included in the sire's PL evaluation.

Estimates from Dematawewa and Berger (1995, Iowa State University Dairy Report DSL-27; 1997, Journal of Dairy Science 80:754) and from Dekkers (1994, Journal of Dairy Science 77:3441) were combined to obtain the following expenses for a "difficult" calving (codes 4 and 5). Daughter calving difficulty includes $50 for veterinary and labor costs, $25 for calf death (probability of 20%), and $15 for cow deaths before first test day (probability of 1%). Service sire calving difficulty also includes $40 for yield losses during the next lactation and $30 for fertility and longevity losses.

Calving ease scores 2 and 3 each have lesser cost but occur more frequently than scores 4 or 5 (Dematawewa and Berger, 1997, Journal of Dairy Science 80:754). Cost of difficult births must be multiplied by about 2 to include both clinical and subclinical difficulty and also multiplied by 1.6 to account for births from two later lactations with about one-third the difficulty (1.6 = 1 + .3 + .3). The MGS effect accounts for only half of the daughter's contribution and must be doubled to account for the contribution of maternal granddam to genetic trend. Calving ease values then are

Daughter calving ease value/PTA unit = $90(2)(1.6)2/100 = $5.76;
Service sire calving ease value/PTA unit = $160(2)1.6/100 = $5.12.

With values rounded down to $5 for each calving ease trait, SCE and DCE receive 2.3% and 1.9% of total emphasis, which results in about 4% of the relative weight in NM$ on calving ease traits.

Mating programs should continue to assign bulls with low and high PTA for service sire calving difficulty to heifers and to cows, respectively. Breeders can now select the best bulls for their herds based on NM$ without using an independent culling level for calving ease. The value of $5 used in NM$ is a weighted average of losses for cows and heifers. Thus, when ranking sires for heifer use, another $4 should be subtracted from NM$ for each percentage of SCE, and $2 for each percentage of SCE should be added back to NM$ when ranking service sires for cows. These minor adjustments for the differing value of 5 + 4 = $9 for heifers vs 5 - 2 = $3 for cows can be easily handled with computerized mating programs.

Daughter pregnancy rate

Cow fertility is a major component of PL and is important in that sense. Additional costs associated with DPR that are not included in PL are increased units of semen needed per pregnancy, increased labor and supplies for heat detection, inseminations, and pregnancy checks, and yield losses because ideal lactation length cannot be achieved. Semen price ($15/unit) and insemination labor costs ($5/unit) were multiplied by .025 units/day open to estimate a cost of $.50/day open. Heat detection labor and supplies ($20/lactation) multiplied by .5% increase/day open resulted in a cost of $.10/day open. Labor costs for pregnancy checks ($10/exam) were multiplied by .012 exams/day open for a cost of $.12/day open. The initial estimate of reduced profit from lactations longer or shorter than optimum was $.75/day open.

The loss of about $1.50/day open per lactation is converted to a lifetime value by multiplying by 2.8, which assumes that cows have three lactations, no breedings are attempted for half of the cows during their final lactation, and heifer fertility is also included with a correlation of .3 to cow fertility (2.8 = 3.0 - .5 + .3). This economic loss for 1 day open is then converted to DPR by multiplying by -4, which results in a DPR value of $17/PTA unit. With an SD of 1.4 for true transmitting ability, DPR will receive 7% of the relative emphasis in NM$.

The assumed costs may differ greatly across farms or countries. Hansen et al. (1983, Journal of Dairy Science 66:306) obtained expected responses to index selection for a wide range of economic values. McAllister (2000, Proceedings of the Conference on Managing Reproduction in Southeastern Dairy Herds) provided a more recent summary of selection for fertility. Research from Australia (Morton, 2002) indicates that fertility may be 3 times more important in herds with seasonal calving than those that calve year-round. As of August 2003, 8 of the 12 largest Holstein populations internationally include cow fertility in their national indexes with the proportion of emphasis on fertility equal to 1% for Germany, 7% for United States and Netherlands, 8% for Australia, 9% for Denmark, 10% for New Zealand and Sweden, and 13% for France (International Bull Evaluation Service, 2003, National GES Information). A few countries, such as Sweden, have selected for fertility since 1975.

Yield trait data are adjusted by the Animal Improvement Programs Laboratory (AIPL) for days open during the previous lactation but not the current lactation. Adjustments for current days open were developed as part of a test-day model [Wiggans et al., 2002, Journal of Dairy Science 85:(Jan.)] but have not been implemented. Inclusion of PL in NM$ since 1994 and adjustment of yield traits for previous days open since 1995 already have prevented much of the correlated decline in cow fertility that would have resulted from selecting for increased yield. Actual selection decisions of breeders may not have emphasized PL as much as recommended in previous NM$ formulas. The Holstein genetic trend for DPR has stopped declining since 1995, but the environmental trend continues downward.

Further details regarding the calculation of DPR are provided by "Daughter pregnancy rate evaluation of cow fertility" [VanRaden et al, 2003, AIPL Research Report DPR1(11-02)].

Yield traits

Milk prices continue to vary widely across time and by use of milk. Expected prices for milk, fat, and protein were obtained from average U.S. prices over recent years (available from the USDA Agricultural Marketing Service). A base milk price of $12.70 was assumed after hauling and promotion charges were deducted. Component prices per pound follow:

Index Milk Fat Protein
NM$ .012 1.30 2.30
CM$ -.009 1.30 3.00
FM$ .051 1.30 1.00
Feed cost .012 .35 .50

Correlations of merit indexes based on recent, progeny tested bulls were .99 for NM$ with CM$, .96 for NM$ with FM$, and .91 for FM$ with CM$. The FM$ index previously included a protein price of 0, but many producers receive a blend price for milk or at least hope to receive some protein premium within 5 years. Inclusion of a small protein premium makes FM$ relevant to more producers and results in selection for protein instead of against it when the premium is higher than the feed cost. Producers that expect future premiums of <$.17/.1% protein should select on FM$; those that expect premiums of >$.26/.1% protein should select on CM$. Most producers are likely to expect protein premiums between $.17 and $.26 and should select on NM$.

Feed costs in the past were assumed to equal 30% of component values in NM$. The feed cost for milk volume must be higher to account for the $.20 required to produce a pound of lactose in each 20 pounds of milk. Feed costs also include $.002 for bulk tank, equipment, and electricity costs to cool and store each pound of milk. Feed cost for protein was decreased to that estimated by Dado et al. (1994, Journal of Dairy Science 77:598), but other researchers obtained still lower values. The value of milk, fat, and protein is converted from a lactation basis to a net lifetime basis by subtracting feed costs and then multiplying by the number of lactations and the ratio of actual yield to mature-equivalent yield. For example, the lifetime value of PTA protein in NM$ is (2.30 - .50) (3) (.89) = $4.81. Yield traits together account for only 55% of total selection emphasis in NM$.

Productive life

Many traits affect PL and also the incomes and expenses within lactations. Evaluations for PL are enhanced with correlated information from type, yield, and SCS evaluations. Further information on calculation of multitrait PL can be found in "Multitrait Productive Life" [VanRaden and Wiggans, 2000, AIPL Research Report PL1(11-00)].

Because multiple lactations are needed to cover the cost of raising the cow, PL has a large economic value. The profit function requires that PL be expressed in lactations instead of months. The variable #Lact is defined as the average number of lactations (3.0) plus a regression on PL (.12). The regression is >.1 (1 lactation = 10 months) to allow for PL beyond 84 months and lactations longer than 10 months:

#Lact = 3.0 + .12(PTA PL).

The economic value of PL depends mainly on the price difference between replacements and cull cows, which has been increasing. Instead of increasing the emphasis on PL, the new value of 11% is lower than the 14% in the previous NM$ index because more emphasis is now assigned to the individual traits such as DPR that contribute to PL instead of assigning this emphasis to PL. With the new NM$ formula, increased genetic progress is expected for PL because the total emphasis on fitness traits is much greater than in the past.

Somatic cell score

Selection for lower SCS reduces the labor, discarded milk, antibiotic, and other health costs associated with clinical mastitis. Lower PTA SCS also leads to higher milk prices in markets where quality premiums are paid. Fetrow et. al (2000, Proceedings of the 39th Annual Meeting of the National Mastitis Council, p. 3-47) surveyed price premiums and penalties across the nation and found an average price decrease of $.20 for each unit of PTA SCS (a doubling of somatic cell count). The value of PTA SCS per lactation was set at -$51, which includes a premium of $41 plus $14 for labor, drugs, discarded milk, and milk shipments lost due to antibiotic residue. Larger economic losses caused by reduced milk yield are not included in the SCS value because these already are accounted for in PTA milk. The economic value results in assigning 9% of emphasis in NM$ to lower SCS. PTA SCS includes a mean of 3 which is subtracted when including PTA SCS in the merit indexes.

Conformation composites

Linear type traits provide additional information about incomes and expenses. Instead of directly using PTA's for all 17 type traits, composites are used in NM$. For Holsteins, the Udder Composite, Feet and Legs Composite, and Body Size Composite Indexes are calculated by Holstein Association USA (2000, Holstein Type-Production Sire Summaries, August, p. 12). For other breeds, published PTA's for linear traits are converted to standardized transmitting abilities (STA's) by dividing by SD of true transmitting ability and then are combined into composites that are not published. Because rear legs (rear view) and feet-and-legs score in the Holstein Feet and Legs Composite are traits that are not available for other breeds, STA for foot angle and rear legs (side view) are included in the feet/legs composite for those breeds. Relative values of udder and feet/leg traits for Jerseys and Brown Swiss were obtained from the official Functional Trait Indexes (FTI) and Functional Udder Index (FUI) of these two breed associations. The Jersey values equal 3 FTI + FUI and the resulting values are applied to Ayrshires, Guernseys, and Milking Shorthorns instead of the Holstein values used previously. Relative values were negative for fore udder, rear udder height, and teat placement in the official Guernsey FTI and thus that index was not used here. Breed association FTI formulas were obtained from correlations with productive life, but partial regressions are difficult to estimate in small populations with many traits. Relative values of body size traits are the same for all breeds except Jersey, where body depth is no longer evaluated and its value was assigned to strength instead.

Relative values of each trait in the composites and SD used for obtaining STA's follow. SD are 1.0 for Holsteins because their linear trait evaluations are published as STA's. SD for other breeds are similar to those given for Jerseys.

Udder trait Relative value (%)     SD
Holstein Brown Swiss Jersey and other breeds Holstein Jersey
Fore udder 16 21 20 1.0 1.1
Rear udder height 16 6 18 1.0 1.2
Rear udder width 12 1 8 1.0 1.1
Udder cleft 10 2 3 1.0 .8
Udder depth 30 35 26 1.0 1.5
Teat placement 16 11 7 1.0 1.1
Teat length -24 -18 1.0 1.3
Udder composite 100 100 100 .78 .65

Relative values of traits in the feet/legs composite follow:

Foot or leg trait Relative value (%) SD
Holstein Brown Swiss Jersey and other breeds Holstein Jersey
Rear legs (side view) -8 -32 -30 1.0 .7
Rear legs (rear view) 18 . . . . . . 1.0 . . .
Foot angle 24 68 70 1.0 .7
Feet and legs score 50 . . . . . . 1.0 . . .
Feet and legs composite 100 100 100 .88 .90

Relative values of traits in the size composite follow:

Size trait Relative value (%)
Holstein and other breeds Jersey Holstein Jersey
Stature 50 50 1.0 1.3
Strength 25 40 1.0 .8
Body depth 15 . . . 1.0 1.0
Rump width 10 10 1.0 1.1
Size composite 100 100 .94 .92

The emphasis placed on udder composite in NM$ is similar to that proposed by Rogers (1993, Journal of Dairy Science 76:664; 1998, Proceedings of the 1998 U.S. National Dairy Genetics Workshop, Orlando, FL, p. 5-11). Selection for higher udders is important when also selecting against large body size. Positive selection for PTA feet/legs and negative selection for PTA size also are included. Compared with a value of $11 per lactation for udder traits, the value of PTA feet/legs is set at $5 per lactation based on research by Rogers (1993, Journal of Dairy Science 76:664).

Large cows and bulls were favored by dairy cattle breeders for many years. Research studies (VanRaden, 1988, Journal of Dairy Science 71:Suppl. 1:238; Metzger et al., 1991, Journal of Dairy Science 74:Suppl. 1:262) that were funded by Holstein Association USA at the Universities of Wisconsin and Minnesota concluded that cow size should have negative value in an index because milk income already was accounted for but feed costs were not. Within each breed, the larger cows tend to eat more feed and are less efficient (Dickinson et al., 1969, Journal of Dairy Science 52:489).

Body size expenses include the increased cost of feed per lactation that is eaten by heavier cows for body maintenance [$.18/pound of cow weight based on findings by the National Research Council (2001, Nutrient Requirements of Dairy Cattle, 7th rev. ed.), Yerex et al. (1983, Journal of Dairy Science 66:Suppl. 1:115), and Metzger et al. (1991, Journal of Dairy Science 74:Suppl. 1:262) plus increased housing costs [$.03/pound of cow weight based on Bath et al. (1985, Dairy Cattle: Principles, Practices, Problems, Profits, 3rd ed.) and Etgen et al. (1987, Dairy Cattle Feeding and Management, 7th ed.)] minus income from heavier calf weights ($.06/pound of cow weight). Mature cow weight in pounds is obtained by multiplying PTA size by 24 based on Holstein data from the University of Minnesota size-selection herd. The net lactation expense equals $.15/pound of cow weight, and the beef price for cull cows is much lower than the cost of growing replacements. The calculated value of body size was then reduced slightly as compared to 2000 NM$ because inclusion of calving ease in the index places additional emphasis on small size. The direct selection emphasis in NM$ is now 3% against large body size.

Lifetime profit

The NM$ index is defined as the expected lifetime profit as compared with the breed base cows born in 1995. Incomes and expenses that repeat for each lactation are multiplied by the cow's expected number of lactations. This multiplication makes the economic function a nonlinear function of the original traits. For official NM$, a linear approximation of this nonlinear function is used as recommended by Goddard (1983, Theoretical and Applied Genetics 64:339). The linear function is much simpler to use and was correlated with the nonlinear function by .999.

Index selection based on computer calculation is efficient, and computer mating programs that account for inbreeding using complete pedigrees can be very useful. Selection and mating programs both can have large, nearly additive effects on future profit. Gains from mating programs do not accumulate across generations, whereas gains from selection do. Cows and bulls within each breed are ranked using the same NM$ index even though the timing of gene expression differs for the two sexes. Although NM$ measures additional lifetime profit that is expected to be transmitted to an average daughter, it does not include additional profit that will be expressed in granddaughters and more remote descendants. Gene flow methods and discounting of future profits could provide a more complete summary of the total profit from all descendants.

The profit function approach used in deriving NM$ lets breeders select for many traits by combining the incomes and expenses for each trait into an accurate measure of overall profit. Averages and SD's of the various traits in the profit function may differ by breed, but official NM$ is calculated by using Holstein values instead of having a slightly different NM$ formula for each breed. Producers should use the lifetime merit index (NM$, CM$, or FM$) that corresponds to the market pricing that they expect a few years in the future when buying breeding stock and 5 years in the future when buying semen.

History of Net Merit

The enhanced NM$ index, which will be implemented in August 2003, includes cow fertility and calving ease and is correlated by .98 with the previous NM$ formula for recent progeny-tested bulls. Because the enhanced NM$ includes more of the traits that affect profit, the resulting change in genetic progress is expected to be worth $5 million per year on a national basis. However, some of this extra progress resulted from revised relative values for existing traits rather than the addition of new traits.

In August 2000, type traits were included along with yield and health traits using a lifetime profit function described in "Net Merit as a measure of lifetime profit -2000 version" [VanRaden, 2000, AIPL Research Report NM$1(11-00)] based on research of scientists in the S-284 Health Traits Research Group. In 1994, PL and SCS were combined with yield traits into NM$ using economic values that were obtained as averages of independent literature estimates (VanRaden and Wiggans, 1995 Journal of Dairy Science 78:631). In the 1980's as part of Project NC-2 of the North Central Regional Association of Agricultural Research Experiment Station Directors, researchers developed a profit function to compare genetic lines in their experimental herds:

lifetime profit = milk value + salvage value + value of calves
- rearing cost - feed energy - feed protein - health cost - breeding cost.

The main difference between NM$ and the 1980's profit function is that PTA is calculated for each evaluated trait and then combined instead of combining each cow's phenotypic data directly. The PTA approach is more accurate because heritabilities of traits differ, genetic correlations are not the same as phenotypic correlations, and all phenotypes are not available at the same time.

In 1984 and 1977, economic index formulas based on cheese yield price (CY$) and protein price (MFP$), respectively, were introduced. In 1971, AIPL introduced its first economic index called Predicted Difference Dollars (PD$), which combined only milk and fat yield. The three different milk pricing formulas continued to be published until 1999 when these were replaced by the more complete merit indexes CM$, NM$, and FM$, respectively.

A history of the main changes in AIPL indexes and the percentage of relative emphasis on traits included in indexes follows:

Traits included USDA economic index (and year introduced)

Milk 52 27 -2 6 5 0
Fat 48 46 45 25 21 22
Protein . . . 27 53 43 36 33
Productive life . . . . . . . . . 20 14 11
Somatic cell score . . . . . . . . . -6 -9 -9
Udder composite . . . . . . . . . . . . 7 7
Feet/leg composite . . . . . . . . . . . . 4 4
Size composite . . . . . . . . . . . . -4 -3
Daughter pregnancy rate . . . . . . . . . . . . . . . 7
Service sire calving difficulty . . . . . . . . . . . . . . . -2
Daughter calving difficulty . . . . . . . . . . . . . . . -2

Emphasis on yield traits has declined as other fitness traits were introduced. As protein yield became more important, milk volume became less important because of the high correlation of these two traits. In recent years, some of the emphasis on PL has shifted to the individual traits that contribute to PL. A recent survey of selection indexes used by other countries with large Holstein populations is available for comparison (VanRaden, 2002, Proceedings of the 7th World Congress on Genetics Applied to Livestock Production 29:127).

Acknowledgments: The authors thank the many university scientists, artificial-insemination industry specialists, and breed association staff that provided input on economic values, Bob Miller for help in estimating fertility expenses, George Wiggans and Gary Fok for computational assistance, and Mel Tooker, Suzanne Hubbard, and Melvin Kuhn for review and revision of this research report.