Can beef cattle breeding satisfy customer demands in the 21st century?

Abstract

Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 CAN BEEF CATTLE BREEDING SATISFY CUSTOMER DEMANDS iN THE 21ST CENTURY? R. D. Green, T. G. Field, N. S. Hammett, B. M. Ripley, and S. P. Doyle Department of Animal Sciences, Colorado State University INTRODUCTION As animal breeders, we are engaged in the noble pursuit of developing science-based technologies which will result in genetic improvement of livestock production. In the recent past, it has become apparent that in many cases the amount of information available is `much greater than the true practicing breeder can ably apply. There is a detectable sense of information overload amongst industry breeders, with no end in sight'. While the perspective of this presentation will come from the experience of the United States beef cattle industry, one could easily substitute the other livestock commodities, in a global perspective, and retain many of the same conclusions. It is the hope of the authors that it will stimulate the scientific community to feel some sense of urgency tigarding the need for engagement in not only research, but policy making and industry educational endeavors as well. The objectives of this presentation are to: 1) Provide an overview of how to match a producer and production system to a specific industry target: 2) Discuss current and future tools ,needed for proper genetic decision-making, and 3) Provide some perspective on how the beef cattle indusw can go about increasing 'quality and consistency' while maintaining bahmces in efficiency and profitability. WHERE SHOULD WE BE PLACING EMPHASIS IN GENETK IMPROVEMENT? All changes in a commercial cow-calf operation must be evaluated in terms of their effect on profitability of the whole enterprise. Given the problem that profitability is &en, in the short-term, very affected by external market conditions, Dickerson (1970) advocated that these changes be evaluated on the basis of economic efficiency measured as the ratio of input costs per unit of output product value. When one operates under this philosophy, cost of production becomes very important relative to desired increases in product value mentioned above as industry gods. Purtbermore, it is imperative to remember that many of these desired ends are often antagonistically `related, meaning that we must be careful to keep the 'big picture' in perspective. For example, traditionally we have thought that in relative economic terms, reproductive efficiency is roughly twice as important as growth performance which is approximatelyfive timesas important as carcass merit (Melton et al. 1979). A few years ago, a reanalysis of the importance of these three types of traits under a more current, value-based type of marketing system was completed. Under this more current marketing system, the former 10 reproduction: 5 growth:. I pro&Cr ratio was now closer to 2 reproduction: 1 growth: 1 product (Melton, 1995). A more recent evaluation of these economic weights has been presented from the American Gelbvieh Association's GeBvieh Alliance marketing program (Figure 1). After some 110,000 feedlot cattle had gone through their program, the estimated relative importance of these three trait categories was approximately 4:2:1 (Schiefelbein, 1998). There are several things about these relative economic values that are very important. First, under the general assumptions used in their, derivation, these results indicate that 17 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 while we have paid a lot of attention to growth of calves in the past, that will not suffice in the future. In most cases, the problm are in the. other two categories: repredtiw effldan~ bes~~se .it has been so difficult to genetically change, and care&s merit because we simply have not paid much attention to this area. Figure 1. Relative Importance of Trait Categories (Schiefetbeia, 1998). Secondly, one should not fall prone to the common error of assuming that these economic weights are universally true. They are applicable to one particular system and environment but may bequite different if the system is changed. One of the universal strengths that makes ,the beef influ$ry unique is that it uses God-given resources .from the land which cannot be more efficientlyuttlr~ by other production systems. Cattle harvest energy from sunlight, soil, and water that is then converted to a higher quality form of protein. They do this from a set of natural resources that cannot be 'farmed' any other way. The p ig tht those resouqx73s&: under such,a wide .array ofBci9systems. that, we are challenged to come up with one management system that will work, fg all ~vironrnents (Hohenboken, 1988). Herein also ties our .genetic. dilemma when we try to b&d the best beast to harvest and harness that energy from the environment. Thirdly, we also a&n tend to over-generaliae in the beef industry when @king about 'THE TARGET'. As Dell Allen of Excel, Inc. has stated, there a several different target markets in the beef industry (Allen, 1987). The fi question that a commercial breeder must ask bef@re.addressing anything else genetically, is 'Which target am I going maim my production resources toward?'. As marketing of cattle in alliance and grid programs has escalated over the past 24 months in the U.S., it has become clear that there are major targets in'lean beef', 'high-qua&y beef', and 'export beef' trade. There are certainly other smaller specialty markets as well. The market may change over time in relation to premiums and discounts for 'leanness' versus 'quality'. However,, B given producer must decide Qefare the gwetic decisi~ are made OQ a well-defined target .that.`is comfortable. Given the current plethora of alliance marketing programs, one must become. educated on where he/she fits and then set their target based on that ~m&etii program. O&Y then can one truly go about determinkg the relative importance of these traits, 18 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 WHAT SHOULD BE IN A COMMERCIAL BREEDER'S WANT AD? In 1987, the beef cattle symposium program at the annual meeting of the American Society of In that program, Rick Bourdon and Bill Animal Science was entitled 'Bovine Nirvana'. Hohenboken discussed different perspectives on how one might describe the 'ideal' cow (Bourdon 1988; Hohenboken 1988). As they both stated in their remarks, this beast does not really exist, primarily due to the reasons already described earlier in this paper. However, we do know that it is possible to provide some general guidelines for the specifications we wouId iook for `in performance criteria in the beef cattle production system. Bob Taylor, a recently deceased colleague and friend in the beef cattle management systems area, had great foresight in realizing the need to look at 'balanced' performance of cattle long before it was popular. A number of years ago, he developed a simple analogy to illustrate the importance of this philosophy to his beef production students. He said that what commercial producers should do is develop a 'want ad' for the type of bulls and females they use in their system. This want ad should then be what is used by the seedstock industry to develop 'specification seahock' to address the needs of the commercial production sector of the industry. While this is a very simple approach, in concept, one is left to wonder just how often it has been applied. Taylor's general&d want ad, shown in table 1, provides an excellent overview of the challenge a breeder has to mount in order to 'hit the overall' target. Table 1. Production and marketing specifications for beef cattle Trait Reproduction Age at Puberty (mos) Scrotal Circumference Reproductive Weight at Puberty (kg) Heifers Bulls Age at First Calving (mos) Birth Weight Calves from Cows (kg) Calves from Heifers (kg) Body Condition Score (BCS, 1-9) Postparhw Interval (d) 35-45 27-36 4-6 55-95 365-390 45-90 80-95 9-15 39 32 5 75 365 65 85 12 , ,, 2701360 400-500 23-25 320 `450 24 (cm) 12-16 32-40 4-5 14 36 5 Optimum Range' Industry Tag& Tract Score (14 mos) Calving Interval (d) Calving Season (d) Calf Crop Weaned (% cows exposed) Cow Longevity Growth Mature Cow Weight (kg at BCS 5) Weaning Weight (kg; steer @ 7 mos) (yr of age) 400-600 200-275 ,500 240 19 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 Yearling Weight (kg; steer @ 365 d) Grazed and I or backgrounded Weaning to Feedlot 275-365 400-500 320 450 Feedlot Gain(kg I d) 1.1-1.6 S-7' 60-120 1.4 6' 90 Feedlot Feed Efficiency (steer) Days on feed (high energy ration) Carcass Carcass Weight (kg) Quality Grade USDA Yield Grade Fat Thickness (mm) Ribeye Area (cm') Palatabihty (W fat in retail cuts) f&ear Force (kg) muscle to kg bone) 275-365 Select' to Choice' ` 320 Choice` 2.5 7.5 84 5 Below 3.65 4.0 1s-3.5 2.5-15.2 71-97 3-l Below 3.65 3.5-4.5 Warner-Brat&x Mu&e to Bone(kg Lean Yieid / Day Age (kg) Weaned Steer to Feedlot Grazed Yearling Steer to Lot Frame Score Steers cows Bulls - Maternal Terminal 4-6 4-6 4-6 5-7 5 5 5 6 0.35-0.4s 0.20-0.30 0.40 0.25 (Adapted from Taylor and Field, 1999). 'Range will include most commercial beef operations where an optimum combination of productivity and profitability is desired. yarget gives central focus applicable to many commercial beef operations. Deviation from this target and optimum range is dependent on market, economic, and environmental conditions in specific commercial beef operations. `High-energy ration, kg feed per kg gain. IS IT POSSIBLE TO GENETICALLY IMPROVE COW ADAPTABI`tI'f'Y AND CARCASS ACCEPTABILITY? Within Population Selection. Fortunately, collective research results over the past 50 years have clearly shown that genetic variation exists both between and within breeds for many of the important measures of perfomance in beef cattle production. Table 2 provides a summary of the average levels of heritability for a variety of reproductive, growth and carcass traits as provided in an exhaustive analysis of the research literature by Koots et al (1994a). In general, selection within breed populations is quite effective for carcass traits, moderately effective for growth related traits, and much slower for reproductive efficiency related traits. 20 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 Table 2. Levels of Heritability (h*) of Beef Cattle Performance Traits Trait Number of Studies' 7 wei&tal Mean ta2 b 6 19 8 1 6 to 9 17 48 5 2 17 2 31 14 24 13 33 6 `5-o 32 34 22 44 42 41 23 39 47 63 38 29 13 61 Reprodoction Age at First Calving (Direct) Age at First Calving (Maternal) Calving Date Calving Interval (Cows) Calving Interval (Heifers) Calving Ease (Direct) Calving Ease. (Maternal) Calving Rate Scrotal Circumference Heifer Conception Rate (Direct) Heifer Conception Rate (Maternal) Cow Conception Rate (Direct) Cow Conception Rate (Maternal) Growth Birth Weight (Direct) Birth Weight (Maternal) Weaning Weight (Direct) Weaning Weight (Maternal) Yearling Weight (Direct) Yearling Weight (Maternal) Mature Cow Weight Feed Efftciency Feed Intake Relative Growth Rate Carcass Backfat Thickness Ribeye Area Slaughter Weight Carcass Weight Dressing Percentage Cutability Lean:Bone Ratio Marbling Score' Warner-Bratzler Shear Force Sensory Panel Tenderness Yearling Frame Score 1 7 3 7 19 11 9 25 9 1 21 1 167 34 234 38 147 6 24 25 21 12 26 16 52 19 13 12 4 12 12 3 27 (Adapted fromKoots ef al., 1994a and Green, 1999). 'Number of research studies represented. bAverage heritability of trait, weighted by number of observations in studies. Expressed as a percentage. `Recent review of Marston et al (1999) reported average of 43% heritability for marbling. dAll traits are expressed on an age constant basis where applicable. Until recently, we have believed that there was limited opportunity'& via direct selection within breeds. While indicator traits of fertility 21 genetiially improve fertility and age at puberty, such as Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 scrotal circumference, have proven to be quite useful and heritable (Brinks et nl. 19%), they have not been shown to be highly genetically correlated to fertility measured as pregnancy success. Because fertility measures are binary traits (ie they are observed as either pregnant or not pregnant), it is quite difficult to use phenotypic information to determine genetic differences (eg. two fen&l& may both get pregnant but `may differ widely in their true genetic potential for fertility). This results in traditional analytical methods not being adequate to separate these genetic differences and thus, we have always stated that the heritability of these traits is quite low (see table 2). ,More appropriate statistical methodology called 'threshold modelling' allows appropriate analysis of these types of traits on an underlying continuous probability scale. One of the first applications this approach was to define a new trait called 'stayability' that has been adopted by the Red Angus Association of America and is now in the process of being implemented by several other breeds (&telling et al. 1995). This estimated breeding value is a genetic prediction of the probability of femaIes still being in the herd at a breakeven age of six years-given that they were selected as re&acements. This measure combines performance differences in fertility, growth, and survivability/adaptability of these females. In the direct fertility area, an analysis of heifer pregnancy records from the Iierefti herd at the Bell Ranch in New Mexico has recently been completed (Evans et al. 1996). In that study, the researchers determined that heifer pregnancy was indeed more heritable than previously thought (14%). Furthermore, when the relationship of heifer pregnancy with `yearling bull scrotal circumference was estimated, a non-linear relationship (ie the bulls with low.SC E&V had low HP EBV, moderate SC EBV had the highest HP EBV and highest SC EBV had lower HP EBV) was revealed. A second study conducted a similar analysis using historical data from the Colorado State University Beef Improvement Center Angus population at Saratoga, WY (Doyle eral. 1996). These researchers reported a heritability level for heifer pregnancy of 19%, corroborating the result of Evans et al (1996). These two studies indicate that it is feasible to produce genetic predictions to enable direct genetic improvement in reproductive rate. The only obstacle is getting breed association national cattle evaluation performance databases to adopt a 'whole-herd reporting' format that is necessary to allow computation of these types of EBV (Golden et. al. 1996). While this is only a start on the whole reproductive efficiency complex, it is a 200% improvement over current genetic capabilities in this important area. Population Selection. Larry Cundiff and co-workers at the U.S. Meat Animal Research Center have conducted the most extensive genetic evaluation of breeds in the world over the past 30 years in the Germ Plasm Evaluation (GPE) program at the U. S. Meat Animal Research Center. The design for this project (table 3) has allowed for the evaluation of a widely diverse set of breeds, as shown grouped by biological type in table 4 (Cundiff and Gregory 1999). Fromthe collective results of this effort, they have reported that the magnitude of genetic variability between breeds is roughly equivalent to that within breeds (table 5) for most performance traits. While this infers that genetic improvement is possible through proper breed selection implemented in designed crossbreeding programs (ie breed complementarity), it also points out that no one breed excels in all characteristics simultaneously, along with a great degree of overlap between various breeds. Between z2 . Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 Table 3. Sire brteds used in the germ plasm evaluation program (Cundiff and Gregory 1999) Cycle I Cycle II Cycle 111 (1970-72) (1973-74) (1975-76) F, crosses from Hereford or Angus dams (Phase 2)' Hereford Hereford Hereford Angus Angus Angus Jersey Red Poll Brahman S. Devon Braunvieh Sahiwal Limousin Pinzgauer Gelbvieh Simmental Maine Anjou Tarentaise Charolais Chianina Cycle IV (1986-90) Hereford Angus Longhorn Salers Galloway Nellore Shorthorn Piedmontese Charolais Gelbvieh Pinzgauer Cycle V (1992-94) Hereford Angus Tuli BdtW Belgian Blue Brahman Piedmontese 3-way crosses out of F 1 dams (Phase 3) Hereford Hereford Angus Angus B&man Brangus Devon Santa Gertrudis Holstein 'In Cycle V, composite MARC 111(l/4 Angus, l/4 Hereford, l/4 Pinzgauer and _ Red Poll) cows are also included. bHereford and Angus sires used in Cycle IV included 10 Hereford sires born from 1963 to 1969 and 14 Angus sires born from 1968 to 1970 used as reference sires in Cycles I, II, 111and IV to produce reciprocal cross Hereford X Angus (HA.) progeny, and 32 Hereford sires born from 1982 to 1985 and 28 Angus sires born from 1983 to 1985 used to produce reciprocal cross Hereford x Angus by a current sample of sires (HA,) in Cycles IV and as reference sires in Cycle V. . 23 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 Table 4. Breeds evaluated in USDA-ARS germ plasm evaluation biological type (Cundiff and Gregory 1999) Breed Group Jersey (J) Longhorn (Lh) >Hereford-Angus (HAx) Red Poll (R) Devon (D) Shorthorn (Sh) Galloway (Gw) South Devon (Sd) Tarentaise (T) Pinzgauer (P) Brangus (Bg) Santa Gert. (Sg) Sahiwal (SW) Brahman (Bm) Nellore (N) Braunvieh (B) Gelbvieh (G) Holstein (Ho) Simmental (S) Maine Anjou (M) Salers (Sa) Growth Rate I Mature size X X Lean to fat ratio X program grouped into Age at puberty X Milk Production xxxxx xxx xx xx xx xx xxx xxx xxx xxx xx xx xxx xxx xxx xxxx xxxx xxxx xxxx xxx xxx xx xxx xxx xxx xx xx xx xxxx xxxx xxxxx xxxxx xxxxx xx xx xx xx xx xxx xx xxx xx xx XXX xx XXX xxx xx xxx xxx xxx xx xx xxx xxx xxx xxxx xxxx xxxxx xxx xxx xxx xxx xx xxxx xxxx xxxx xxxx xxxx xxxxx xxxxx xxxxx xxxx xxxx xxx xxx xxx xx xxxx xxxx xxxx xxxx xxx xx X X X xxx xxxxxx Piedmontese (Pm) xxx xxxxx Limousin (L) xxx Charolais (C) xxxxx xxxxx Chianina (Ci) xxxxx xxxxx 'Increasing number of X's indicate relatively higher values. Table 5. Relativity of variation within and between breeds Trait for various performance criteria Number of Additive Genetic Standard Deviations 8.5 8.0 8.2 6.6 6.1 Age at Puberty (d) Slaughter Weight (450 d) Retail Product Weight (450 d) Retail Product % (450 d) Marbling Score (450 d) Warner-Bratzler Shear Force (kg) 5.1 Adapted from Cundiff and Gregory (1999). `Assumption is made here that within a breed approximately genetic standard deviations of variation exist in any trait. six 24 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol I3 The GPE program, along with other studies, has also,shown that many genetic antagonisms exist in beef production systems. Koots et al (1994b) summarized published estimates of genetic and phenotypic correlations between a number of traits of interest (table 6). These estimates clearly reveal general genetic antagonisms between growth rate and calving ease, growth rate and mature cow size, maternal characteristics and cutability, and carcass quality and cutability. Additionally, the review of these authors pointed out how many genetic relationships between traits of economic importance are poorly understood. A prime example of the sparseness of information'is the h&k of any understanding of the relationship between measures of tenderness and other perfomance~eriteria. Table 6. Weighted mean literature performance traits' Traitsb estimates of genetic correlations between various Phenotypic Correlation Gk!iI&iC correlatlo* Calving Ease / Birth Weight -0.28 Birth Wt / Feed Efficiency -0.12 Yearling Wt / Feed Efftciency -0.46 I_ Feed Intake / Feed Efftciency ___ Wean Maternal / Feed Intake Scrotal Circumference I Feed Efficiency 0.12 Birth Wt / Weaning Wt 0.46 Birth Wt / Yearling Wt 0.38 Weaning Wt I Yearling Wt 0.71 Weaning Wt I Mature Wt 0.45 Weaning Wt I Slaughter Wt 0.65 Yearling Wt / Slaughter Wt 0.65 Yearling Wt I Scrotal Circumference 0.36 Backfat / Feed Intake 0.29 Backfat / Scrotal Circumference 0.27 Carcass Wt / Birth Wt 0.41 Carcass Wt / Yearling Wt 0.85 Cutability / Yearling Wt 0.85 Marbling I Yearling Wt 0.14 Marbling / Feed Intake 0.24 Marbling / Cutability -0.25 Ribeye Area / Weaning Wt 0.23 Ribeye Area I Yearling Wt 0.35 Ribeye Area / Slaughter Weight 0.33 Ribeye Area / Cutability 0.33 Ribeye Area / Marbling 0.06 Tenderness I Marbling ??7? Tenderness / Cutability ???? 'Estimates shown are taken from Koots ef al (1994b) and mpreaent the weighted mean of estimates. %aits represented are expressed on an age constant basis where appropriate and represent -0.74 -8.46 -0.60 0.71 0.80 0.61 050 0.55 Q.8 I 0.57 0.79 0.56 0.39 0.44 0.78 0.60 0.9 I 0.87 -0.33 0.90 0.35 0.49 0.51 0.43 0.45 -0.21 7777 1177 available literature direct genetic effects. The most troubling genetic antagonism we must consider when attempting to genetically improve product quality and consistency concerns the relationship between carcass attributes and measures of reproductive efficiency. There is generally a lack of this type of information in the research literature. The best existing data relating actual carcass measures to reproductive traits comes from a study by MacNeil et al (1984) at the U. S. Meat Animal Research Center. Table 7 provides a 25 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 summary of that information and indicates antagonistic relationships between selection to increase retail product weight and age at puberty, services required to settle a cow and mature size. When one considers these estimates in concert with the experiences of the swine industry with pale, soft, and exudative pork (PSE), a definite red flag is raised. Table 7. Genetic Correlations Efnciency (MacNeil et al. 1984) Female Trait Age at Puberty (d) Wt at Pube&(kg) Services/conception Gestation Lepgtb (d) Calving pifficulty Birth Weight (kg) Mature Weight (kg) Between Measures of .Carcass Merit &WI Reproductive Postweanine Gain (kg) .I6 .07 1.33 -.iO -.60 .34 .07 Carcass Weight (kg) .i7 .07 .61 .03 -.3 1 .37 .21 Fat `frim (kg) 429 -.3 1 .21 -.07 -.31 -.07 -.09 Retail Product (kp), 33 .O% .28 .I3 -.02 .30 .25 `.' j Unfortunately, even though there have been numerous attempts to make one b&eve otherwise, these antagonisms leave no doubt that no one breed allows breeders to have their cake`and eat it, too! Bourdon (1994) used the analogy of 'sensible beef stew' to describe the effectiveness of utilizing designed mating systems to 'mix and match' strengths and weaknesses of breeds to meet specifications for balanced performance. This fact has been further supported in the analysis of the American Gelbvieh Alliance results where a ratio of 50% British to 50% Cbntiriental European breeding appears optimal to hit market targets (Schiefelbein 1998). Cundiff,gr al (1,9W)`additionally pointed out the need for alteration of breed inputs in sub-tropical environments to in&de either some Bos indicus or heat tolerant Bos taurus germ plasm. HETEROSIS... THE FINAL PIECE IF THE PUZZLE Fortunately, nature has provided a significant amount of heterosis observed in the reproductive efficiency and maternal trait complex to allow breeders to overcome the obstacles of divot selection for fertility and cow adaptability mentioned earlier. Heterosis levels of 20 to`25% are achievable in pounds of calf weaned per cow exposed to breeding using systems which exploit a terminal sire breed mated to crossbred females of unrelated breeds (table 8; Cundiff and Gregory 1999). This amount varies according to the ,breeds used in the crossing system beoauee heterosis is ,directly proportional to the difference in gene frequencies affecting the traits between,the breeds used in the cross. This is the basis for the success of the Bos indicus x Bos taurus crosses in the sub-tropical zones where these females express phenomenal heterosis in maternal and reprodutiive performance. Unfortunately, in the chase to utilize this 'free-lunch' heterosis gift, as has animal breeding, there'has been too much emphasis on 'maximize' and 'optimize'. When we recall what was mentioned before about evaluating cost per unit of output product value, there is an optimum amount of reproductive perfom&ce. Beyond that optimum it costs more to achieve return. This is an important concept to keep in check. 26 too often been the case in not enough emphasis on the &f&t8 ofchange ,on everything tie do, even than'be&fits received in Proc. Assoc. Advmt. Anim. Breed. Genet, Vol13 In&us Table 8. Heterosis effects in crosses of Bos Taurus x Bos Z'aurus breeds and in crosses of Bos x Bos Taurus breeds from diallel crossing experiments' Bos taurus x Bos taurus N Bos in&us x Bos taurus Units 3.2 1.4 0.8 1.4 .034 13.2 3 .-;2 3.5 .8 0.7 8.2 1.36 .97 272 Trait Calving rate, % Survival to weaning, % Birth weight, kg Weaning weight, kg Postweaning ADG, kg/d Yearling weight, kg Cutability, % Quality grade, l/3 grade Calving rate, % Survival to weaning sirth weight, kg Weaning weight, kg Longevity, yrs Lifetime production No. Calves 11 16 16 16 19 27 24 24 13 13 13 13 3 3 3 N % % Units Crossbred ches (itdviaala hktetmis) 4.4 1.9 11.1 4 3.3 2.4 12.6 10 21.7 3.9 i6.2 6 .116 2.6 3.8 6 ___ .3 ::_ 9 Crossbred cows (npaternrl heterois) 13.4 7 9.9 3.7 5.1 7 4.7 1.5 5.8 6 1.9 1.8 16.0 12 31.1 3.9 16.2 17.0 25.3 Cumulptive wming weight 'Estimates are from experiments contributing to North Central Regioaal Pmjact NC-l&own, Indiana, Missouri, Ohio, USDA-ARS and Nebraska), Southern Regional Project S-10 (Virginia, Florida, Louisiana, Texas, SD& ARS and Louisiana, USDA-ARS and Florida) as reported by Cundiff and Gregory (1999). SO, HOW DO WE GENETICALLY MANAGE TO SIMULTANEOUSLY IMPROVE ENDPRODUCT PERFORMANCE AND LOWER COS'r OF PRODUCtiON? Given that there are IiteraIly hundreds (thousands may be even more appropriate) of feed resource and climatic environments used in cattle production,- yet end-product performance must fit within specification targets, what do we do? Animal breedeti have unanimously stated over the past several generations of cattle production that we must'achieve this balance by using bieed complementarity and heterosis in very carefully designed crossbreeding programs. This must be a sevemllstep process to work successfully. First, the proper breeds must be chosen for niatching maternal performance of the cow herd to a given production environment. `Secondly, the proper ii&s from within those breeds must be selected to properly hit those environmental targets while also meeting minimum acceptable Then a terminal sire breed musi be selected to bring performance in end-product characteristics. necessary performance for growth and end-product performance to the system. Furthermore, the sires selected from within the terminal breed (or breeds) chosen, must have documented performance for growth and carcass traits (ie EBV ) in addition to the sires selected for maternal replacements having documented EBV for reproductive and functional soundness. There are several different types of crossbreeding programs available to producers. These have been discussed in detail in the past (Bourdon 1994; Kress 1994; Cundiff and Gregory 1999). There are certainly advantages and disadvantages to each of them. Unfortunately, a number of the product inconsistency problems our industry is experiencing today are from misuse and abuse of these systems. It has not usually been the choice of the particular crossbreeding program that has gotten 27 Proc. Assoc. Advmt, Anim. Breed. Genet. Vol13 breeders into trouble as much as the inability to properly .design,impkement and then stay,the course in a crossbreeding program. Many progmms have been doomed-from the Wrt$ecause they :we~e nti properly thought out, while yet others have failed because a new breed,has come along that tempts the curiosity too much. Furthermore, there are sti!l many breed and tradition loyalties which run rampant which often get in the way of breeding program objectivity. These fticts, coupled, with the wild chase for extra growth and extra heterosis have resulted in what some have called the 'mongrelization' of the U.S. beef cow herd. IS THERE ANY WAY TO REDUCE CROSSBWEDING VARIATION? Cundiff and Gregory (1999) presented an excellent summary of the effectiveness of various crossbreeding systems in terms of heterosis utilization, use of breed complementarity, and consistency of production in 1994. In that presentation, the most effective system at doing all three things simultaneously, along with being the easiest to manage effectively, was composite breeding. The theory behind composites has been amply proven by the Germ Plasm Utilization Project at the U.S. Meat Animal Research Center under the Ieadership and guidance of Keith Gregory. The published summary (Gregory et al. 1995) of that work proves that composite breeding offers a usable solution to many of the problems we are discussing here. Heterosis utilization is high, breed percentages are fixed and do not vary between generations, and breed differences can be utilized to match breed strengths and weaknesses to the production and marketing environment. The ability to overcome genetic antagonisms and still retain high levels heterosis in maternal performance is unmatched by any of the other designed systems. Furthermore, once the composite is formed, the breeding system is much simpler to manage than any of the others. Detractors of the composite approach have argued that composite mating sjrsteins will i&ease rather than decrease variability of production due td increased` lkvels of heter&j$&y. USbA-AI& work has shown that there is not a significant iricrease in tht? variability observtid in the composite lines as compared to the purebreds (table 9). Furthermore, compared to other mating systems such as rotational.crosses and rota-terminal systems, the inter-generational variation is eliminated (figure 2). These same detractors of composites have argued thai we cannot afford to give up the consistency that purebreeds have worked so hard to devllop through their history. They do foiget, however, that those purebreeds with their consistency have to be the foundation for the composite Iines. Just like there is no one breed that offers everything, the beef cattle industry will not be able to deveIop only one maternal line compdsite. While that may work better for the ioultry and &vine industries, it will not work for the beef industry. Therefore, the challenge is for the purebred breeds to, f&d where they will fit into various composite lines as they develop. 28 Proc. Assoc. Advmt. Anim. Breed. Genet. Vol13 Figure 2. Variation Resulting From Various Mating Systems (Cmdiff and Gregory 1994). Table 9. Genetic Standard Deviations (sg) and Phenotypic Coefficients of Variation (CV) for Purebwds and Conposites (Castrate Males) Purebreds Trait 200-d weight, kg Slaughter weight, kg Carcass weight, kg Compasites SE 14.2 28.7 17.9 2.0 2.3 10.7 6.3 2.1 I.0 0.59 % 13.3 21.7 12.4 1.3 2.2 8.1 8.6 2.8 .6 .I8 Cv .I0 .08 .OS .48 .04 .08 .I8 .08 .27 .22 cv .I1 .08 .09 .44 .06 .09 .I9 .I0 .29 .2l I 21hrib fat, mm Retail product, % Carcass lean weight, kg Carcass fat weight, kg Carcass bone weight, kg Longissimus muscle fat. % Shear force, kg (Cundiff and Gregory 1999 and Gregory er al. 1995) Reactions to the idea of composite breeding have been very interesting to watch. There have been some purebred breeds which have realized that they need to find where they can provide useful germ plasm for the formation of these composit