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Genetic improvement of animals plays an important role in improving the economic and environmental sustainability of livestock production systems. This paper proposes a method to incorporate mitigation of environmental impacts and risk preferences of producers into a breeding objective via economic values (EVs). The paper assesses the effects of using these alternative EVs of breeding goal traits on discounted economic response to selection and on environmental impacts at commercial farm level. The application focuses on a Brazilian pig production system. Separate dam- and sire-line breeding programs that supply parents in a 3-tier production system for producing crossbreds (fattening pigs) at commercial level were assumed. Using EVs that are derived from utility functions by incorporating risk aversion increases the cumulative discounted economic response to selection in sire-line selection (6%) while reducing response in dam-line selection (12%) compared with the use of traditional EVs. The use of EVs that include environmental costs increases the cumulative discounted social response to selection in both dam-line (5%) and sire-line (10%) selections. Emission of greenhouse gases, and excretion of nitrogen and phosphorus can be reduced more with genetic improvements of production traits than reproduction traits for the typical Brazilian farrow-to-finish pig farm. Reductions in environmental impacts do not, however, depend on the use of the different EVs (i.e., with and without taking into account environmental costs and risk). Both environmental costs and risk preferences of producers need to be considered in sire-line selection, and only environmental costs in dam-line selection to improve, at the same time, the economic and environmental sustainability of the Brazilian pig production system.

A combined matrix that exploits genealogy together with marker-based information could improve the selection of elite individuals in breeding programs. We present genetic parameters for adaptive and growth traits in beef cattle by exploring linear combinations of pedigree-based (A) and marker-based (G) relationship matrices. We use a data set with 2,111 Brahman (BB) and 2,550 Tropical Composite (TC) cattle with genotypes for 729,068 SNP, and phenotypes for five traits. A weighted relationship matrix (WRM) combining G and A was constructed as WRM = λG + (1 - λ)A. The weight (λ) was explored at values from 0.0 to 1.0, at 0.1 intervals. Additionally, four alternative G matrices, in the WRM, were evaluated according to the selection of SNP used to generate them: 1) Gw: all autosomal SNP with minor allele frequency (MAF) > 1%; 2) Gg: autosomal SNP with MAF > 1% and mapped inside to gene coding regions; 3) Gp: autosomal SNP with MAF > 1% and previously reported to have significant pleiotropic effect in these two populations; and 4) Gc: autosomal SNP with MAF > 1% and with significant correlated effects previously reported in both BB and TC populations. In addition, two A matrices were evaluated: 1) A: all relationships between animals were considered after tracing back known ancestors; and 2) Ad: a distorted A matrix where a random 1% of the off-diagonal nonzero values were set to zero to simulate relationship errors. Five independent Ad matrices were explored each with a different random 1% of relationships masked. Criteria for comparing the resulting WRM included estimates of heritability (h2) and cross-validation accuracy (ACC) of genomic estimated breeding values. The choice of WRM had a greater impact on h2 than on ACC estimates. The 1% errors introduced in pedigree relationships generated large distortion in genetic parameters and ACC estimates. However, employing a λ > 0.7 was an efficient mechanism to compensate for the errors in A. Additionally, although significant (P-value < 0.0001), we found no consistent relationship between the type of SNP used to compute G and h2 or ACC estimates. We devised the optimal value of λ for maximum h2 and ACC at λ = 0.7 suggesting a 70% and 30% weighting to genomic and genealogical information, respectively, as an optimal strategy to compensate for pedigree errors, to improve genetic parameters estimates and lead to more accurate selection decisions.

Economic selection indexes (EI) are considered the best way to select the most profitable animals for specific production systems. Nevertheless, in Brazil, few genetic evaluation programs deliver such indexes to their breeders. The aims of this study were to determine the breeding goals (BG) and economic values (EV, in US$) for typical beef cattle production systems in southern Brazil, to propose EI aimed to maximize profitability, and to compare the proposed EI with the currently used empirical index. Bioeconomic models were developed to characterize 3 typical production systems, identifying traits of economic impact and their respective EV. The first was called the calf-crop system and included the birth rate (BR), direct weaning weight (WWd), and mature cow weight (MCW) as selection goals. The second system was called the full-cycle system, and its breeding goals were BR, WWd, MCW, and carcass weight (CW). Finally, the third was called the stocking and finishing system, which had WWd and CW as breeding goals. To generate the EI, we adopted the selection criteria currently measured and used in the empirical index of PampaPlus, which is the genetic evaluation program of the Brazilian Hereford and Braford Association. The comparison between the EI and the current PampaPlus index was made by the aggregated genetic-economic gain per generation (Δ). Therefore, for each production system an index was developed using the derived economic weights, and it was compared with the current empirical index. The relative importance (RI) for BR, WWd, and MCW for the calf-crop system was 68.03%, 19.35%, and 12.62%, respectively. For the full-cycle system, the RI for BR, WWd, MCW, and CW were 69.63%, 7.31%, 5.01%, and 18.06%, respectively. For the stocking and finishing production system, the RI for WWd and CW was 34.20% and 65.80%, respectively. The Δ for the calf-crop system were US$6.12 and US$4.36, using the proposed economic and empirical indexes, respectively. Respective values were US$19.87 and US$18.22 for the full-cycle system and US$20.52 and US$18.52 in the stocking and finishing system. The efficiency of the proposed EI had low sensitivity to changes in the values of the economic and genetic parameters. The 3 EI generated higher Δ when using the proposed economic weight compared to the Δ provided by a PampaPlus index, suggesting the use of proposed EI to obtain greater economic profitability in relation to the current empirical PampaPlus index.

An economic selection index was developed for Beefmaster cattle in a general-purpose production system in which bulls are mated to a combination of heifers and mature cows, with resulting progeny retained as replacements or sold at weaning. National average prices from 2010 to 2014 were used to establish income and expenses for the system. Genetic parameters were obtained from the literature. Economic values were estimated by simulating 100,000 animals and approximating the partial derivatives of the profit function by perturbing traits 1 at a time, by 1 unit, while holding the other traits constant at their respective means. Relative economic values for the objective traits calving difficultly direct (CDd), calving difficulty maternal (CDm), weaning weight direct (WWd), weaning weight maternal (WWm), mature cow weight (MW), and heifer pregnancy (HP) were -2.11, -1.53, 18.49, 11.28, -33.46, and 1.19, respectively. Consequently, under the scenario assumed herein, the greatest improvements in profitability could be made by decreasing maintenance energy costs associated with MW followed by improvements in weaning weight. The accuracy of the index lies between 0.218 (phenotypic-based index selection) and 0.428 (breeding values known without error). Implementation of this index would facilitate genetic improvement and increase profitability of Beefmaster cattle operations with a general-purpose breeding objective when replacement females are retained and with weaned calves as the sale end point.

The aim of our study was to compare different validation methods with respect to their impact on validation results and to evaluate the feasibility of genomic selection in the German Landrace population of the Bavarian herdbook. For this purpose, a sample of 337 boars and 1,676 sows was genotyped with the Illumina PorcineSNP60 BeadChip. Conventional BLUP breeding values for fertility, growth, carcass, and quality traits were deregressed and used as phenotypes in genomic BLUP. The resulting genomic breeding values were also blended with information from the full conventional breeding value estimation to include information from nongenotyped parents. Subsequent validation used forward prediction, realized reliabilities, and theoretical reliabilities. The results indicate that the validation methods showed a relatively large effect on in the displayed reliability levels in our study: forward prediction reliabilities were found to be much lower than the conventional parent-average reliabilities whereas corresponding realized and theoretical reliabilities were found substantially greater. Theoretical reliabilities appear to be the most consistent validation approach tested in our study, because they avoid the use of proxy variables. Generally, our results suggest a substantial potential for a genomic selection implementation for the Bavarian herdbook by using both sows and boars. Theoretical genomic reliabilities of direct genomic values of selection candidates were, on average, 31 to 36% greater than the conventional parent average reliabilities. However, the inclusion of residual information from conventional breeding values had only a marginal effect on reliabilities.

Most breeding companies evaluate economically important traits in males and females as a single trait, assuming genetic correlation of 1 between phenotypes measured in both sexes. This assumption may not be true because genes may be differently expressed in males and females. We estimated genetic correlations between males and females for growth and efficiency traits in broiler chickens, growth traits in American Angus beef cattle, and birth weight and preweaning mortality in purebred pigs; therefore, each trait was treated differently in males and females. Variance components were estimated in single- and multiple-trait models, jointly or separated into both sexes. Furthermore, we calculated traditional and genomic evaluations, and we correlated EBV or genomic EBV (GEBV) from joint and separate evaluations for males and females. For broiler chickens, genetic correlations ranged from 0.86 to 0.94. For Angus cattle, genetic correlations ranged from 0.86 to 0.98 for early growth traits and were less, ranging from 0.68 to 0.84, for postweaning gain. In pigs, genetic correlations ranged from 0.98 to 0.99 for birth weight and from 0.71 to 0.73 for preweaning mortality. For some models in all 3 animal species, the joint and separate analyses had different heritabilities. Despite differences in heritability, the correlations within the sex-specific trait EBV and between the sex-specific and the joint trait EBV were very strong, regardless of the model or inclusion of genomic information. Males and females differed for traits measured late in the animal's life; however, strong traditional EBV correlations and also GEBV correlations indicate that considering the traits equal in males and females may have no negative impact on selection.

The objective of this study was to develop a transparent, comprehensive, and flexible model for each trait for the formulation of breeding objectives for sow traits in swine breeding programs. Economic values were derived from submodels considering a typical Australian pig production system. Differences in timing and expressions of traits were accounted for to derive economic weights that were compared on the basis of their relative size after multiplication by their corresponding genetic standard deviation to account for differences in scale and genetic variability present for each trait. The number of piglets born alive had the greatest contribution (27.1%) to a subindex containing only maternal traits, followed by daily gain (maternal; 22.0%) and sow mature weight (15.0%). Other traits considered in the maternal breeding objective were preweaning survival (11.8%), sow longevity (12.5%), gilt age at puberty (8.7%), and piglet survival at birth (3.1%). The economic weights for number of piglets born alive and preweaning piglet survival were found to be highly dependent on the definition of scale of enterprise, with each economic value increasing by approximately 100% when it was assumed that the value of extra output per sow could be captured, rather than assuming a consequent reduction in the number of sows to maintain a constant level of output from a farm enterprise. In the context of a full maternal line index that must account also for the expression of direct genetic traits by the growing piglet progeny of sows, the maternal traits contributed approximately half of the variation in the overall breeding objective. Deployment of more comprehensive maternal line indexes incorporating the new maternal traits described would lead to more balanced selection outcomes and improved survival of pigs. Future work could facilitate evaluation of the economic impacts of desired-gains indexes, which could further improve animal welfare through improved sow and piglet survival. The results justify further development of selection criteria and breeding value prediction systems for a wider range of maternal traits relevant to pig production systems.

Genomic selection can be implemented in pig breeding at a reduced cost using genotype imputation. Accuracy of imputation and the impact on resulting genomic breeding values (gEBV) was investigated. High-density genotype data was available for 4,763 animals from a single pig line. Three low-density genotype panels were constructed with SNP densities of 450 (L450), 3,071 (L3k) and 5,963 (L6k). Accuracy of imputation was determined using 184 test individuals with no genotyped descendants in the data but with parents and grandparents genotyped using the Illumina PorcineSNP60 Beadchip. Alternative genotyping scenarios were created in which parents, grandparents, and individuals that were not direct ancestors of test animals (Other) were genotyped at high density (S1), grandparents were not genotyped (S2), dams and granddams were not genotyped (S3), and dams and granddams were genotyped at low density (S4). Four additional scenarios were created by excluding Other animal genotypes. Test individuals were always genotyped at low density. Imputation was performed with AlphaImpute. Genomic breeding values were calculated using the single-step genomic evaluation. Test animals were evaluated for the information retained in the gEBV, calculated as the correlation between gEBV using imputed genotypes and gEBV using true genotypes. Accuracy of imputation was high for all scenarios but decreased with fewer SNP on the low-density panel (0.995 to 0.965 for S1) and with reduced genotyping of ancestors, where the largest changes were for L450 (0.965 in S1 to 0.914 in S3). Exclusion of genotypes for Other animals resulted in only small accuracy decreases. Imputation accuracy was not consistent across the genome. Information retained in the gEBV was related to genotyping scenario and thus to imputation accuracy. Reducing the number of SNP on the low-density panel reduced the information retained in the gEBV, with the largest decrease observed from L3k to L450. Excluding Other animal genotypes had little impact on imputation accuracy but caused large decreases in the information retained in the gEBV. These results indicate that accuracy of gEBV from imputed genotypes depends on the level of genotyping in close relatives and the size of the genotyped dataset. Fewer high-density genotyped individuals are needed to obtain accurate imputation than are needed to obtain accurate gEBV. Strategies to optimize development of low-density panels can improve both imputation and gEBV accuracy.

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.

Two selection methods, 1-stage selection (OSS) and 2-stage selection (TSS), for improving efficiency and profitability of selective breeding of yellow perch were evaluated, through examining the genetic and phenotypic parameters for BW of F(1) fish using microsatellite parentage assignment in this study. Approximately 94% of the sampled yellow perch progeny were assigned to single parental pairs using 8 microsatellite markers, which confirmed the applicability of the communal rearing technique in yellow perch breeding. Within OSS, the genetic correlation between 1-yr-BW and 2-yr-BW was high (0.98), indicating that the growth of yellow perch recorded at yr 1 could predict their growth for yr 2. Also mean family BW and family EBV for BW between yr 1 and 2 were found to be significantly correlated, suggesting yr 1 fast-growing yellow perch families continued to be the fast growing families in yr 2. Two-year random fish undergoing TSS were significantly heavier (P < 0.01) than those undergoing OSS. In addition, top males and females with TSS were heavier (P < 0.01) than those with OSS. Based on these results we concluded that the TSS was more desirable and effective for yellow perch breeding compared with OSS in terms of improving selection efficiency and reducing costs.

The objective of this paper was to adapt gene-flow methodology for the calculation of economic weights (EW) for direct and maternal traits and trait components in sheep and to apply this methodology to the Suffolk breed in the Czech Republic. Computer programs were developed in which annual-lambing sheep production systems with purebreeding or partial terminal crossing were simulated. Using these programs, the EW for 12 production and functional traits were estimated for i) Suffolk sires whose sons were used both in purebreeding and in terminal crossing with the 4 dual-purpose breeds, Romanov, Sumavska, Romney, and Merinolandschaf; and ii) Suffolk sires used only for terminal crossing. For case (i), the EW were at first calculated separately for the purebreeding system and for the crossing systems with the 4 dual-purpose breeds in dam position. Compound EW for the general breeding goal for Suffolk were then estimated as weighted averages from the EW in the 5 subsystems. Standardized EW were calculated by multiplying the marginal EW with the genetic SD of the trait, and relative EW were defined as absolute values of the standardized EW expressed as percentage of the sum of the absolute values of the standardized EW over all traits. The 5 most important trait components for Suffolk sires whose sons were used both in purebreeding and in terminal crossing were (relative EW given in parentheses): the direct components of survival rate until weaning (21.0%), daily BW gain until weaning (14.1%), survival rate at birth (14.0%), the maternal component of survival rate until weaning (10.7%), and litter size at lambing (7.6%). There were only small differences between the relative EW calculated for the whole system with pure- and crossbreeding and the relative EW for the purebred system within the Suffolk breed. Therefore, selection of Suffolk rams using a selection index based on the compound EW is expected to be of high efficiency in all of the simulated breeding systems. Only direct traits were relevant for Suffolk sires used only for terminal crossing; the most important (range of relative EW calculated for the 4 crossing systems given in parentheses) were survival rate until weaning (35.2 to 36.5%), daily BW gain until weaning (24.2 to 26.3%), and survival rate at birth (23.7 to 24.8%).

The objective of this study was to estimate the value derived from using DNA information to increase the accuracy of beef sire selection in a closed seedstock herd. Breeding objectives for commercial production systems targeting 2 diverse markets were examined using multiple-trait selection indexes developed for the Australian cattle industry. Indexes included those for both maternal (self-replacing) and terminal herds targeting either a domestic market, where steers are finished on pasture, or the export market, where steers are finished on concentrate rations in feedlots and marbling has a large value. Selection index theory was used to predict the response to conventional selection based on phenotypic performance records, and this was compared with including information from 2 hypothetical marker panels. In 1 case the marker panel explained a percentage of additive genetic variance equal to the heritability for all traits in the breeding objective and selection criteria, and in the other case to one-half of this amount. Discounted gene flow methodology was used to calculate the value derived from the use of superior bulls selected using DNA test information and performance recording over that derived from conventional selection using performance recording alone. Results were ultimately calculated as discounted returns per DNA test purchased by the seedstock operator. The DNA testing using these hypothetical marker panels increased the selection response between 29 to 158%. The value of this improvement above that obtained using traditional performance recording ranged from $89 to 565 per commercial bull, and $5,332 to 27,910 per stud bull. Assuming that the entire bull calf crop was tested to achieve these gains, the value of the genetic gain derived from DNA testing ranged from $204 to 1,119 per test. All values assumed that the benefits derived from using superior bulls were efficiently transferred along the production chain to the seedstock producer incurring the costs of genotyping. These results suggest that the development of greater-accuracy DNA tests for beef cattle selection could be beneficial from an industry-wide perspective, but the commercial viability will strongly depend on price signaling throughout the production chain.

A study was conducted to evaluate the efficacy of selection for intramuscular fat (IMF) in a population of purebred Duroc swine using real-time ultrasound. Forty gilts were purchased from US breeders and randomly mated for 2 generations to boars available in regional boar studs, resulting in a base population of 56 litters. Littermate pairs of gilts from this population were randomly assigned to a select line (SL) or control line (CL) and mated to the same sire to establish genetic ties between lines. At an average BW of 114 kg, a minimum of 4 longitudinal ultrasound images were collected 7 cm off-midline across the 10th to 13th ribs of all pigs for the prediction of IMF (UIMF). At least 1 barrow or gilt was slaughtered from each litter, and carcass data were collected. A sample of the LM from the 10th to 11th rib interface was analyzed for carcass IMF (CIMF). Breeding values for IMF were estimated by fitting a 2-trait (UIMF and CIMF) animal model in MATVEC. In the SL, selection in each subsequent generation was based on EBV for IMF with the top 10 boars and top 75 gilts used to produce the next generation. One boar from each sire family and 50 to 60 gilts representing all sire families were randomly selected to maintain the CL. Through 6 generations of selection, an 88% improvement in IMF has been realized (4.53% in SL vs. 2.41% in CL). Results of this study revealed no significant correlated responses in measures of growth performance. However, 6 generations of selection for IMF have yielded correlated effects of decreased loin muscle area and increased backfat. Additionally, the SL obtained more desirable objective measures of tenderness and sensory evaluations of flavor and off-flavor. Meat quality characteristics of pH, water holding capacity, and percent cooking loss were not significantly affected by selection for IMF. Selection for IMF using real-time ultrasound is effective but may be associated with genetic ramifications for carcass composition traits. Intramuscular fat may be used in purebred Duroc swine breeding programs as an indicator trait for sensory traits that influence consumer acceptance; however, rapid improvement should not be expected when simultaneous improvement in other trait categories is also pursued.

The objective of this study was to evaluate and quantify the genetic progress achieved in a New Zealand Angus nucleus herd through long-term selection for an economically based, multi-trait breeding objective. A 4-trait breeding objective was implemented in 1976 and selected on through 1993 with traits consisting of slaughter weight and dressing percentage of harvest progeny and cull cows, and the number of calves weaned in the lifetime of each cow. These traits were related to gross income with none related to costs of production. To overcome this, economic weights were adjusted down for increased feed requirements of faster growing (and generally larger) animals. Performance and pedigree information was recorded on 16,189 animals from 1976 through 1993 and included weaning, yearling, and mature cow weights along with the lifetime number of calves weaned by each cow. These traits were used in the phenotypic selection indexes developed to predict the defined breeding objective. Individual performance was adjusted by least squares for major environmental fixed effects and deviated from contemporaneous means. Genetic and residual (co)variances were re-estimated for each of the traits using REML techniques and used to calculate EBV for each trait. These EBV were in turn used to calculate annual genetic changes. The average annual genetic changes for weaning weight direct and maternal breeding value were 0.43 +/- 0.05 and 0.03 +/- 0.22 kg/yr, respectively. Corresponding annual genetic changes for postweaning BW gain, yearling weight, harvest weight, and mature BW were 0.29 +/- 0.03, 0.72 +/- 0.06, 1.7 +/- 0.13, and 0.13 +/- 0.09 kg, respectively. The annual change in number of calves weaned per cow lifetime was 0.006 +/- 0.001 calves/cow and the change in dressing percentage was estimated to be -0.035 +/- 0.003 %/yr. At the end of the program, 3.21 generations of selection had occurred with a mean accumulated selection differential of 3.87 SD. Change in objective traits due to selection was similar to or exceeded change predicted at the onset of the program with the exception of mature BW and dressing percentage. Genetic change in mature BW was not different from zero, whereas the predicted change was 29.3 kg. The overall genetic trend in the breeding objective exceeded that predicted at the onset of the program. Results of this study showed that selection on indexes developed to predict an economically based, multi-trait breeding objective will produce genetic change.

The feasibility and economic value of DNA paternity identification were investigated and illustrated using Nevada beef cattle operations. A panel of 15 microsatellites was genotyped in 2,196 animals from 8 ranches with a total of 31,571 genotypes. Probabilities of exclusion for each marker within ranch and across ranches were computed. Joint probabilities of exclusion for the 15 microsatellites were also determined, resulting in values over 0.99 for any individual ranch and across ranches. Dropping 1 or 2 microsatellites with the lowest probabilities of exclusion resulted in joint probabilities greater than 0.99 and with marginal reduction compared with the probabilities with 15 microsatellites. Formulas for benefit-cost analysis for a DNA paternity identification program in beef cattle were derived. Genotyping 15 microsatellites with 20 calves per sire resulted in benefits of $1.71 and $2.44 per dollar invested at bull culling rates of 0.20 and 0.30, respectively. The breakpoints for the program to be profitable occurred when the ratio of the price of 1 kg of calf liveweight over the cost of genotyping 1 microsatellite was greater than 1.1 for a bull culling rate of 0.30. Benefit-cost analysis was also derived under incomplete DNA paternity identification using a lower number of DNA markers than necessary to achieve joint probabilities of exclusion of 0.99. Approximately a 20% increase in the benefit-cost ratio was achieved using 10 vs. 12 microsatellites with incomplete paternity identification. The greater the number of bulls in the operation, the lower the benefit-cost ratio of the paternity testing program. Low probabilities of exclusion and a high number of bulls in the beef operation reduced the benefit-cost ratio dramatically. The DNA paternity identification programs are feasible and may be profitable for free-range beef cattle operations.

Deterministic simulation was used to evaluate 10 breeding schemes for genetic gain and profitability and in the context of maximizing returns from investment in Japanese Black cattle breeding. A breeding objective that integrated the cow-calf and feedlot segments was considered. Ten breeding schemes that differed in the records available for use as selection criteria were defined. The schemes ranged from one that used carcass traits currently available to Japanese Black cattle breeders (Scheme 1) to one that also included linear measurements and male and female reproduction traits (Scheme 10). The latter scheme represented the highest level of performance recording. In all breeding schemes, sires were chosen from the proportion selected during the first selection stage (performance testing), modeling a two-stage selection process. The effect on genetic gain and profitability of varying test capacity and number of progeny per sire and of ultrasound scanning of live animals was examined for all breeding schemes. Breeding schemes that selected young bulls during performance testing based on additional individual traits and information on carcass traits from their relatives generated additional genetic gain and profitability. Increasing test capacity resulted in an increase in genetic gain in all schemes. Profitability was optimal in Scheme 2 (a scheme similar to Scheme 1, but selection of young bulls also was based on information on carcass traits from their relatives) to 10 when 900 to 1,000 places were available for performance testing. Similarly, as the number of progeny used in the selection of sires increased, genetic gain first increased sharply and then gradually in all schemes. Profit was optimal across all breeding schemes when sires were selected based on information from 150 to 200 progeny. Additional genetic gain and profitability were generated in each breeding scheme with ultrasound scanning of live animals for carcass traits. Ultrasound scanning of live animals was more important than the addition of any other traits in the selection criteria. These results may be used to provide guidance to Japanese Black cattle breeders.

The objectives of this study were 1) to propose a profit function for Italian Chianina beef cattle; 2) to derive economic values for some biological variables in beef cows, specifically, production expressed as the number of calves born alive per year (NACY), age at the insemination that resulted in the birth of the first calf (FI), and length of productive life (LPL); and 3) to investigate the relationship between the phenotypic profit function and type traits as early predictors of profitability in the Chianina beef cattle population. The average profit was 196 Euros/(cow.yr) for the length of productive life (LPL) and was obtained as the difference between the average income of 1,375 Euros/(cow.yr) for LPL and costs of 1,178 Euros/(cow.yr) of LPL. The mean LPL was equal to 5.97 yr, so the average total phenotypic profit per cow on a lifetime basis was 1,175 Euros. A normative approach was used to derive the economic weights for the biological variables. The most important trait was the number of calves born alive (+4.03.cow(-1).yr(-1) and +24.06 Euros/cow). An increase of 1 d in LPL was associated with an increase of +0.19 Euros/(cow.yr) and +1.65 Euros/cow on a lifetime basis. Increasing FI by 1 d decreased profit by 0.42 Euros/(cow.yr) and 2.51 Euros/cow. Phenotypic profit per cow had a heritability of 0.29. Heritabilities for eight muscularity traits ranged from 0.16 to 0.23, and for the seven body size traits between 0.21 and 0.30. The conformation trait final score can be used as an early predictor of profitability. The sale price of the animal and differences in the revenue and costs of offspring due to muscularity should be included in a future profit function.

Pig breeding programs traditionally focus on the genetic improvement of production and reproduction traits that have a clear economic value. Because citizens and consumers increasingly attach value to traits that have little or no direct relationship to production costs or to the price of a product, pig breeding organizations want to pay more attention to societally important traits, such as the welfare and health of pigs, the ecological effects of pork production, and the healthiness and sensory quality of pork. Most societally important traits have an economic and a noneconomic value and are sufficiently heritable for effective genetic selection, although many genetic and phenotypic (co)-variances still have to be estimated. However, it often is not clear to a pig breeding organization how it may deal with the noneconomic value of breeding-goal traits. In this study, a retrospective selection-index method is proposed to obtain the proper weights for societally important traits in the breeding goal. First, the genetic-progress space for each breeding-goal trait is explored by increasing the weights, in a stepwise manner, to each societally important trait in the breeding goal, starting from zero. Subsequently, a pig breeding organization can adopt the resulting genetic-progress scenario that it considers most sustainable or most acceptable. The weights underlying the adopted scenario are considered to be the proper breeding-goal weights. The noneconomic value of each societally important breeding-goal trait is found by deducting its economic value from its obtained weight and is thereby expressed in monetary units. In addition to obtaining weights for societally important breeding-goal traits, the proposed method offers the possibility to estimate the societal costs of selecting for economic traits only, as well as the societal benefits and the economic costs of selecting for traits with a noneconomic value. The method is therefore a useful tool for the development of sustainable breeding goals. An example has been worked out for a sow-line breeding program.

The results of genetic evaluation are predictions of breeding values for the selection candidates, and these involve uncertainty with regard to future returns from the use of those selected individuals. This uncertainty is due to differential variability in BLUP of breeding values and can be translated into risk: High fluctuations mean greater risk, which is not taken into account by just looking at expected return. In this research, the methodology of value at risk (VaR) and expected shortfall is introduced for animal breeding decisions as a means to adjust the expected return for the cost of uncertainty in prediction of breeding values. This methodology has recently received a great deal of attention from financial institutions. Given a specified probability alpha, VaR is the alpha-quantile of the distribution of economic returns. The conditional value at risk (CVaR), or expected shortfall, is the expectation of the economic returns, which are less or equal to the VaR. By subtracting the CVaR from the predicted aggregate genotype (muR), a risk-adjusted expected return (RAER) measure was obtained. The measures muR, VaR, and RAER were calculated for a data set with progeny of 161 Polled Hereford bulls belonging to a beef cattle company. The Pearson and Spearman correlations between muR and RAER were 0.89 (P < 0.001) and 0.90 (P < 0.001), respectively. Even though the latter correlation was high, some bulls ranked differently for muR compared with RAER. The Pearson correlation between muR and VaR was low (0.124) and nonsignificant (P > 0.05), whereas the correlation between VaR and RAER was -0.31 (P < 0.0001). The results indicate the need to take into account the adjustment for risk in expected return in order to alleviate the effects of possible losses when overrated animals are selected.

An optimum-sized dog guide weighs 18 to 32 kg and measures 53 to 64 cm in height at the withers when mature body size is attained. Effects of selection index with and without restrictions, independent trait selection, directional selection, stabilizing selection, and negative assortative mating were modeled using data from German shepherd dogs and Labrador retrievers raised by the Seeing Eye, Inc., Morristown, NJ from 1979 to 1997. The selection goals were to decrease mature weight and mature height in German shepherd dogs and to decrease mature weight and increase mature height in Labrador retrievers. Mature weights were recorded for 1,333 German shepherd dog offspring and their 69 dams and 17 sires, and 1,081 Labrador retriever offspring and their 51 dams and 13 sires. Mature heights also were recorded for offspring and parents, including 871 German shepherd dogs from 70 dams and 15 sires, and 793 Labrador retrievers from 40 dams and 13 sires. Selecting on mature weight alone produced the highest aggregate genetic-economic gain for German shepherd dogs compared with the selection indices with and without restrictions, generating a 2.10-kg decrease in mature weight and a correlated 0.36-cm decrease in mature height. In Labrador retrievers, selecting for mature height alone produced the highest aggregate genetic-economic gain but caused an increase in mature weight. Weighting the two traits equally but in the opposite direction without restrictions was the only index that produced the desired effect of decreasing mature weight and increasing mature height in Labrador retrievers. Response to selection for one generation of directional selection for a single trait included a 0.50-kg decrease in mature weight for German shepherd dogs, a 0.59-kg decrease in mature weight for Labrador retrievers, a 0.18-cm decrease in mature height for German shepherd dogs, and a 0.91-cm increase in mature height for Labrador retrievers. Increasing the percentage of dogs attaining optimum size may decrease the cost of production for the Seeing Eye, Inc., because fewer dogs would need to be raised and trained to provide assistance to the same number of blind individuals.

Sow production indicators, including litter size, litter weight, and the length of time that sows remained in the herd (sow longevity), were used to characterize sow performance and profitability. Sow longevity and production records from 148,568 sows in 32 commercial herds from Central Illinois from January 1995 to May 2001 were analyzed using survival and repeatability models, respectively. The factors studied included sow genetics (32 genetic lines), with eight major lines present in multiple herds, and the combination of herd and year of entry in the herd. The largest difference in longevity between the major genetic lines was approximately one parity. There were differences (P < 0.05) in the instantaneous sow removal rate or hazard from the major lines. These differences constitute evidence that sow longevity could be improved by using replacements from specific genetic lines. The net present value per sow (present value of future cash flows and the present value of the sow) was used to evaluate the effect of sow longevity and production traits on economic returns. Assuming a zero discount rate per parity, genetic lines with longer herd life resulted in greater profit than genetic lines with shorter herd life. This difference was reduced with increasing discount rates and was reversed with high discount rates and low net income per litter. These results suggest that the magnitude of the economic improvement attained through the use of sow genetic lines with longer longevity depends on the economic context under which the evaluation is made.

The objectives of this study were to estimate (co)variance components for growth and feed efficiency measures, and to compare selection strategies to improve economic efficiency of gain. Variance components for pre- and postweaning growth, body weight, and measures of feed efficiency were estimated from data collected on 1,047 Targhee lambs over 7 yr. Approximately 21 d after weaning, lambs were group-fed for 4 wk, with ad libitum access to a diet of 37% whole barley grain and 63% pelleted alfalfa hay. Lambs were then individually fed for 6 wk. Lambs were then returned to group feeding for another 4-wk period. The mean feed conversion ratio (gain/intake) for the individual feeding period was 0.11. Mean postweaning ADG for the total 14-wk feeding period was 0.26 kg. (Co)variance components were estimated from single- and two-trait animal models using REML. The selection strategies compared included direct selection, index selection, and restricted index selection. Estimates of (co)variances derived from single- and two-trait models were similar, except for mid-test body weight. Preweaning growth had a low heritability estimate (0.03 +/- 0.04) compared with postweaning growth measures (0.25 to 0.39), but all measures of growth were highly correlated (r2 > 0.98). Heritability estimates of measures of gain efficiency were variable (total feed intake = 0.39; feed conversion ratio = 0.26; residual feed intake = 0.26). Total feed intake was strongly correlated genetically with feed conversion ratio (0.79) and residual feed intake (0.77). The estimate of genetic correlation between feed conversion ratio and residual feed intake was low (0.23). Comparison of selection strategies showed the superiority of index selection (ADG, total feed, body weight) for economic improvement compared with other strategies. Economic response to direct selection for ADG was at least twice that for direct selection for feed conversion ratio or against total feed intake, and that for restricted indices (selecting against residual feed, while holding body weight and/or gain constant). Selection for ADG may be a practical approach for indirectly improving efficiency of gain in lambs.

The CGC population is a stabilized composite of 1/2 Red Angus, 1/4 Charolais, and 1/4 Tarentaise germplasm. The objectives of this research were to estimate genetic parameters for weight traits of CGC and to evaluate genetic responses resulting from selection based on the following index: I = 365-d weight 3.2(birth weight). Phenotypes evaluated were birth weight (n = 5,083), 200-d weight (n = 4,902), 365-d weight (n = 4,626), and the index. In addition, there were 1,433 cows with at least one recorded weight, and 4,375 total observations of cow weight collected at the time their calves were weaned. In 1989, a randomly selected control line and a line selected for greater values of the index were established. Average generation intervals were 3.16 +/- 0.04 and 3.90 +/- 0.08 yr in the index and control lines, respectively. The index selection line (n = 950) accumulated approximately 212 kg more selection differential than the control line over three generations (n = 912). Heritability estimates for direct effects were 0.32 +/- 0.04, 0.49 +/- 0.05, 0.49 +/- 0.05, 0.30 +/- 0.04, and 0.70 +/- 0.04 for the index, birth weight, 365-d weight, 200-d weight, and cow weight, respectively. Heritability estimates for maternal effects were 0.05 +/- 0.02, 0.11 +/- 0.03, 0.04 +/- 0.02, and 0.19 +/- 0.04 for the index, birth weight, 365-d weight, and 200-d weight, respectively. In the control line, direct genetic changes for the index and its components were small. For the index selection line, direct genetic changes for the index, birth weight, 365-d weight, 200-d weight, and cow weight were 6.0 +/- 0.3, 0.45 +/- 0.09, 7.74 +/- 0.55, 3.42 +/- 0.25, and 6.3 +/- 0.9 kg/generation, respectively. Maternal genetic changes were generally small for both the control and index selection lines. Thus, selection for the index produced positive correlated responses for direct genetic effects on BW traits at all ages, with only minor effects on maternal genetic effects. Results demonstrate that despite a genetic antagonism that compromises selection response for decreased birth weight and increased postnatal growth, favorable genetic responses can be achieved with the selection index used in this study.

A study was conducted to compare Brangus, Beefmaster, Gelbray, and Simbrah breed influences for economically important traits. Brangus (9), Beefmaster (12), Gelbray (10), and Simbrah (7) sires were used in purebred and crossbred (Brahman x Hereford F1 cows) matings to generate calves (326) in eight breed groups. Beefmaster cows were of similar size (448 kg), Brangus and Gelbray cows were 11% heavier (501 and 503 kg), and Simbrah cows were 21% heavier (548 kg) compared to Brahman x Hereford F1 cows (452 kg). Calves sired by Brangus and Beefmaster bulls had lower birth weights (35 vs 38 kg; P < 0.05), preweaning growth rates (0.87 vs 0.91 kg x d(-1); P < 0.01), and weaning weights (206 vs 219 kg; P < 0.01) than Gelbray- and Simbrah-sired calves. Birth weights, preweaning ADG, and weaning weight and hip heights were similar between Brangus- and Beefmaster-sired calves. Simbrah-sired calves had greater preweaning growth rates (0.94 vs 0.88 kg x d(-1); P < 0.05), weaning weights (227 vs 211 kg; P < 0.01), and adjusted 205-d hip heights (126 vs 122 cm; P < 0.05) than Gelbray-sired calves. Straightbred Angus steers were introduced in the postweaning portion of the study. Steer calves were placed on feed at an average age of 14.5 mo. Steers were removed from the feedlot upon attaining a targeted 10 mm of backfat. Feedlot ADG did not differ among sire breeds. Brahman-derivative sired steers required an additional 54 d on feed (P < 0.01) and were 86 kg heavier (P < 0.01) at harvest than Angus steers. Continental-Brahman steers spent an additional 25 d on feed (P < 0.05) and were 35 kg heavier (P < 0.01) at harvest than British-Brahman steers. Simbrah-sired steers were 52 kg heavier (P < 0.01) at harvest than Gelbray-sired steers when fed for a similar number of days (211 vs 203 d). However, straightbred Simbrah steers required an additional 12 d on feed (P < 0.01) and weighed 47 kg more (P < 0.01) than Simbrah-sired crossbred steers. The economic value of the heavier calf weaning weights may be offset by the attendant larger cow size of the Continental-Brahman compared to the British-Brahman breeds. Similarly, the heavier weights of Continental-Brahman compared to British-Brahman steers, when harvested at a prescribed level of fatness may be viewed as a benefit, but the increased number of requisite days in the feedlot is a disadvantage.

Inactive myostatin (one or two copies) results in increased muscularity, increased yield of closely trimmed retail product, reduced fat content, increased lean growth efficiency, reduced quality grade, increased birth weight, and increased dystocia. Even though one or two copies of inactive myostatin reduces quality grade or marbling compared to zero copies, there is no decrease in meat tenderness. It may be possible to use mating systems to make the most of the advantages of inactive myostatin while minimizing the disadvantages. The objective of this study was to develop a method to compare mating systems among genotypes at the myostatin locus. Economic variables that influence the profitability of alternative mating systems are prices per unit of retail product for USDA quality grades Standard, Select, and Choice; cost of an assisted calving; and cost of genotyping. Because of variation in both economic variables and biological parameters, a single mating system is not expected to universally maximize profit. We identified seven mating systems that each yield maximum profit for different combinations of values for biological parameters and economic variables. Use of inactive myostatin was profitable as long as the price for Select was at least 80% of the Choice price and the price for Standard at least 60%. As the price for Select and Standard increase up to the Choice price, mating systems that produce a higher proportion of inactive myostatin alleles become more profitable. Profitable use of inactive myostatin depends either on retaining ownership of beef until it is fabricated into retail product or the development of specialty markets that place greater value on lean yield and less on marbling, unlike conventional U. S. markets.

Objectives for this study were to estimate relative economic weights for performance traits for two native and two composite sheep breeds under two management systems in Egypt. Breeds studied were Rahmani (R), Ossimi (O), 3/4R-1/4Finnish Landrace (RFR), and 3/4O-1/4Finn (OFO); OFO and RFR were composite breeds. Management systems were one mating season per year (1M) and three mating seasons per 2 yr (3M). A dynamic computer model was used to simulate animal performance and enterprise efficiency and profit. Input parameters for the model were obtained from published results and analyses of data collected from experimental flocks of the same genetic stocks in Egypt. Responses for two measures of life-cycle feed conversion and one measure of enterprise profit were evaluated. Life-cycle feed conversion was calculated as kilograms of TDN input per kilogram of empty body weight output (TDN/EBW) and kilograms of TDN input per kilogram of carcass lean output (TDN/CLN). Profit was measured as annual gross margin/ewe (GM/EWE). Traits evaluated were conception rate (CR), lambing rate (LR), mortality rate (MR), mature weight (MW), and milk production (MK). Based on responses to percentage changes in trait means, CR was most important for TDN/EBW, followed by LR and MR. For TDN/CLN, LR, MR, and CR were most important. For GM/EWE, CR was most important, followed by LR, MW, and MR. In the systems studied, there was little response to changes in MK. Based on changes in GM/EWE per genetic standard deviation change, LR was most important, followed by CR, MR, MW, and MK in all systems. Relative economic weights for O and OFO were similar, as were weights for R and RFR. Differences in economic weights between management systems for the same breed were not large enough to justify separate selection lines within breeds.

Our objective was to evaluate life-cycle performance of flocks of two Egyptian breeds, Rahmani (R) and Ossimi (O), and their crosses with Finnish Landrace (F) in two management systems. Management systems were one mating season per year (1M) and three mating seasons per 2 yr (3M). Breeds and crosses studied included purebred R and O, F1 crosses 1/2F-1/2R (FR) and 1/2F-1/2O (FO), and inter se matings of 1/4 F-3/4 R (RFR) and 1/4 F-3/4 O (OFO). A dynamic computer model was used to simulate animal performance and enterprise efficiency and profit. Two measures of lifecycle feed conversion (biological efficiency) were computed: kilograms of TDN input per kilograms of empty body weight output (TDN/EBW) and kilograms of TDN input per kilogram of carcass lean output (TDN/CLN). Profit was measured as gross margin (income minus variable costs per ewe per year, GM/EWE). Input parameters for the model were obtained from published results and analyses of data collected from experimental flocks of the same genetic stocks in Egypt. Profit for FR and RFR was 42 and 6% higher in 1M than in 3M. However, profit for all other genetic types was 4 to 8% greater in 3M than in 1M. Breed rankings changed depending on the measure of evaluation (i.e., biological efficiency or profit). Maximization of system output did not necessarily improve efficiency. Under accelerated lambing systems, greater overhead costs associated with labor and feed offset gains in ewe productivity. Genetic stocks should be matched to resources and management systems.

Short- and long-term response to marker-assisted selection in two stages was studied using a stochastic simulation of a closed nucleus herd for beef production. First-stage selection was carried out within families based on information at a fully additive quantitative trait locus (QTL). Second-stage selection strategies were based on 1) individual phenotype, 2) individual phenotype precorrected for QTL, 3) a selection index incorporating phenotype and QTL information, 4) a standard animal model BLUP, and 5) a selection index incorporating marker-QTL information and standard animal model BLUP on records precorrected for QTL. All strategies were efficient in moving the favorable allele at the QTL to fixation, but they differed in the time to reach fixation. Mass selection was less efficient in changing allele frequencies than BLUP. Discounted accumulated response, accounting for the time response was realized and inflation rate, was proposed to rank strategies and to elude the conflict between short- and long-term response in marker-assisted selection. Discounted accumulated response at a time horizon of 20 yr for alternative two-stage selection strategies was compared with conventional BLUP carried out in second stage only. Within-family selection increased discounted accumulated response by more than 11% using Strategy 4 and by up to 12% using Strategy 5 at an inflation rate of 2%. The percentage increase in response was less for highly heritable traits and when the proportion of additive variance explained by the QTL was small. Strategy 5 gave larger response with reduced inbreeding. This strategy also resulted in the lowest cost-benefit ratio, requiring less genotyping per unit of response. Cost-benefit ratio for discounted genotyping and for discounted in vitro production of embryos for traits with low heritability was two to four times that for traits with high heritability. The use of first-stage selection slightly increased the level of inbreeding for both mass (Strategy 1) and BLUP selection (Strategies 4 and 5).

Economic values of growth and carcass traits in Japanese beef cattle for production systems with various types of integration of levels/ stages (cow-calf and feedlot segments and the integrated system) and production circumstances (including 20% higher genetic levels of the traits, management, and economic alternatives) were used to examine responses to selection. Discounted economic values with interest rates of 0, 4.2 (Japanese average), and 8.4% were obtained to investigate the effect of discounting on selection efficiency. Traits considered were daily gain in the feedlot, marbling score, birth weight, weaning weight, and mature weight. The effects of discounting were small. Correlated responses to selection were not always economically favorable for all situations. Selecting bulls for the base situation (i.e., the typical biological and economic conditions for the production of Japanese Black cattle) resulted in negative genetic changes in weaning weight and mature weight in the feedlot segment. Higher genetic levels of daily gain and weaning weight affected efficiency of selection. Although effects of management and economic alternatives on responses to selection were generally small, lighter market weight influenced responses to selection. The results indicate that predicted correlated responses to selection are sensitive to production systems and some production circumstances.

Genetic evaluation, as the term is used today in the beef cattle and sheep industries, refers to the calculation and dissemination of genetic predictions for individual traits. If genetic predictions are to be used wisely, however, genetic evaluation should be broadened to include multiple-trait selection technology, preferably technology that is customized for individual commercial and seedstock producers. Most of the recent research in the area of genetic prediction/multiple-trait selection has focused on the use of economic selection indexes that incorporate genetic predictions produced within breeds. This approach is complicated by genotype x genotype, genotype x environment, and more complex interactions, and the changing correlations they create. The use of a mechanistic technology, bioeconomic simulation, to calculate economic weights can avoid some of the problems caused by interactions, but to implement this technology, academic animal breeders must accept the mechanistic concept of genetic potential and devise ways to translate current within-breed genetic predictions to predictions of this new measure. Sire selection by simulation, a multiple-trait selection technology described in detail in this article, uses bioeconomic simulation in a way that offers advantages over traditional selection indexes in terms of both functionality and appeal. For any customized technology to be applied on a meaningful scale, research priorities must change, and the business relationships between research groups and animal breeding industries must be restructured.

Genetic improvement is inherently a long-term process in which progress in the future is built upon improvement in the past. Discounting of future returns is often used in deriving economic values of traits under selection, but this gives a short-term perspective that is in conflict with the long-term nature of genetic improvement. Changes in management, market environment, and genetic potential over time can negatively affect the attainment of breeding goals. Nonlinear optimization techniques can be used to find optimum economic weights each year over any time horizon. Nearly optimal solutions can be found by deriving economic weights for a single, specified future date. Uncertainty about future production and marketing environments creates risk that might be lessened by maintaining or selecting for diverse genetic stocks that could be used in the future. Such programs may need to be coordinated internationally because they may be too expensive for individual companies to undertake. Consideration of risk and careful analyses of future technical and environmental conditions are needed to define multiple trait objectives for long-term genetic change.

Genetic marker technologies, such as marker-assisted selection, parentage identification, and gene introgression can be applied to livestock selection programs. Highly saturated genetic maps are now available for cattle, swine, and sheep to provide the genetic framework for developing MAS programs. These programs rely on three phases for commercialization of the technology: the detection phase, in which quantitative trait loci are located and their effects on the phenotype measured; the evaluation phase, in which the markers are evaluated in commercial populations; and the implementation phase, in which markers are combined with phenotypic and pedigree information in genetic evaluation for predicting the genetic merit of individuals within the population. Predicting the economic impact of genetic technologies is a complex process that requires quantitative prediction and economic analysis. Evaluating the impact of these benefits across an industry can be achieved through a process in which gains from implementation of a genetic technology are assessed at the individual, enterprise, and industry levels. A pattern of annual benefits and costs can be predicted using gene flows that can be evaluated by conventional economic analysis.

A bioeconomic model was developed to predict slaughter end points of different genotypes of feeder cattle, where profit/rotation and profit/day were maximized. Growth, feed intake, and carcass weight and composition were simulated for 17 biological types of steers. Distribution of carcass weight and proportion in four USDA quality and five USDA yield grades were obtained from predicted carcass weights and composition. Average carcass value for each genotype was calculated from these distributions under four carcass pricing systems that varied from value determined on quality grade alone to value determined on yield grade alone. Under profitable market conditions, rotation length was shorter and carcass weights lighter when the producer's goal was maximum profit/day, compared with maximum profit/rotation. A carcass value system based on yield grade alone resulted in greater profit/rotation and in lighter and leaner carcasses than a system based on quality grade alone. High correlations ( > .97) were obtained between breed profits obtained with different sets of input/output prices and carcass price discount weight ranges. This suggests that breed rankings on the basis of breed profits may not be sensitive to changes in input/output market prices. Steers that were on a grower-stocker system had leaner carcasses, heavier optimum carcass weight, greater profits, and less variation in optimum carcass weights between genotypes than steers that were started on a high-energy finishing diet at weaning. Overall results suggest that breed choices may change with different carcass grading and value systems and postweaning production systems. This model has potential to provide decision support in marketing fed cattle.

Methodology for selection index updating was developed to allow multistage selection. The program determines truncation points for each stage of selection that will maximize either profit or the ratio of aggregate economic gain to cost (R = delta H/C). Either maximum profit or R may be attained by reducing the cost of performance testing in later stages of a multistage program. In order to eliminate the need for multiple integration and assure convergence, a piecewise algorithm was developed. Examples of beef bull selection compared single-stage selection at 1 yr of age, two-stage selection at birth and 1 yr, two-stage selection at 205 d and 1 yr, and three-stage selection at birth, 205 d, and 1 yr. Selection based on three traits (birth weight, gain birth to 205 d, and gain 205 to 365 d) was compared with selection based on four traits (the above three plus ultrasound fat depth) and selection based on five traits (the above four plus feed:gain ratio). Five scenarios were used that allowed variation in proportion of candidates selected for breeding, number of progeny per selected bull, and proportion of profit returned to the nucleus herd. General conclusions based on the examples were 1) multistage selection reduced aggregate economic gain relative to that attained by single-stage selection, 2) inclusion of feed conversion in the index of traits resulted in reduced profit and aggregate economic gain, 3) measurement of feed conversion could be justified when selected bulls produced a large number of progeny, and 4) three-trait selection produced greater profit in all five scenarios than did four- or five-trait selection. Use of the selection updating program described here provides a new source of information that can be used in developing economically sound performance testing and selection programs.

Fifty years of research in animal breeding and genetics are examined from four perspectives: 1) genetic prediction, 2) animal testing and selection schemes, 3) dissemination of genetic improvement, and 4) definition of breeding objectives in economic form. Breeding in all classes of livestock has moved from a purebred appearance orientation to a performance (either purebred or crossbred) orientation. Unfortunately, the evolution from a performance orientation to an economic orientation is incomplete, especially for some livestock classes. Placing breeding objectives into a mathematical form on a sound economic basis is key to integrating modern developments in animal breeding into more purposeful industry programs. Procedures used to develop such objectives are reviewed with attention to common approaches. Where consensus is reached about a breeding objective (in economic form) for a class of livestock, this objective can be used in conjunction with genetic predictions to rank animals within a breeding population. Ranking without undue attention to herd of origin facilitates a pyramid-shaped hierarchy of animals that can be fundamental to the functioning of breeding enterprises contributing improvements to operations concerned with production. Genetic improvements should flow from proven genetically superior animals to improved production systems. The tiers of the pyramid need to be organized relative to animals with differing levels of economic evaluation.

The purpose of this study was to find the economically optimal period of first conception in gilts, addressing the issues of lifetime reproductive performance and expected herd life. A profit equation was used to combine the effects into one economic parameter. The data were from 14,910 gilts on 54 farms throughout The Netherlands. The average number of pigs born alive in the first litter increased with older age at conception. In the second litter a similar, but much smaller, effect was observed. Age at first conception had no effect on number of pigs born alive in the third or greater litter. Gilts bred at an older age had a shorter expected herd life than gilts bred at a younger age. Evaluating the reasons for culling revealed that infertility became a more important reason with increasing age at first conception. The proportion culled for infertility increased linearly from 18% at conception on d 200 to 24.5% at conception on d 300. Combining the effect of litter size and herd life led to the conclusion that the profit per gilt (sow) was not significantly affected by her age at first conception. It is concluded that the optimal economic age at first conception was considered to be approximately 200 to 220 d of age when the cost of housing and feed of the gilt from entry to first conception were taken into account.

A bioeconomic model of a feedlot was developed for the comparison of beef cattle genotypes under specified management and marketing conditions. The optimization behavior of commercial feedlot managers is incorporated into the model using optimum economic rotation theory. The days spent in the feedlot (rotation) by a group of animals are derived using this theory so as to maximize an objective function. Differences among breeds in the present value of profits from a single rotation, expressed per animal, represent the expected price premium paid for a feeder animal of a particular breed. Feed requirements and growth rates for a genotype are predicted over time for a specified diet from estimated mature size. Estimates of carcass fatness over time as a function of the energy content of the diet and estimates of dressing percentage over time are used for each genotype. A base model is described that incorporates biological parameters estimated for 11 breeds from a major breed comparison experiment and uses prices of inputs and outputs for Ontario feedlots. Sensitivity of the model to these biological and economic assumptions is shown. When breeds are compared at constant days fed, weight, or fat depth slaughter points, rankings are inconsistent, relative to those when each breed is slaughtered at its optimal economic point. The model can be used to establish appropriate slaughter end points for comparing beef cattle breeds and crosses and to evaluate breeding objectives for feedlot traits in genetic improvement programs.

Sow replacement rates in a three-tiered breeding structure were investigated for a 10-yr planning horizon using a stochastic life-cycle swine production model. Market hogs were produced in a three-breed static crossing program and marketed on a liveweight basis. Growth and reproductive traits of individual pigs were simulated using genetic, environmental, and economic parameters. Sows were culled after a maximum of 1, 5, or 10 parities. Systems were defined by maximum sow age at culling and included combinations of 1- and 5-parity nucleus and 1-, 5-, and 10-parity multiplier and commercial tiers. Economic response to index selection was considerable for all culling alternatives with yearly increases in system profits ranging from $1.06 to 1.44 for each commercial hog marketed. When sows were culled after one parity in nucleus, multiplier, and commercial tiers, respectively (1,1,1), annual changes in net returns and all cost measures were 40 to 50% larger than responses in systems with lower sow replacement rates. Based on 10-yr averages for net returns, systems with low multiplier- and commercial-level replacement rates were more profitable than systems with higher replacement rates. The most profitable system (5,10,10) differed from the least profitable system (1,1,1) by more than $10 per pig, but when the (1,1,1) system was excluded, the range was only $3 per pig. The system with lowest replacement rates supported 3,388 more multiplier and 34,151 more commercial sows from a 750-sow nucleus level than the (1,1,1) system. Output from the two extremes differed by > 664,000 commercial market hogs sold.(ABSTRACT TRUNCATED AT 250 WORDS)

Commercial-level sow replacement rates were investigated for a 10-yr planning horizon using a stochastic life-cycle swine production model. A three-tiered breeding structure was modeled for the production of market hogs in a three-breed static crossing scheme. Growth and reproductive traits of individual pigs were simulated using genetic, environmental, and economic parameters. Culling was after a maximum of 1, 5, or 10 parities in commercial levels within 1- and 5-parity nucleus and 1-, 5-, and 10-parity multiplier combinations. Yearly changes and average phenotypic levels were computed for pig and sow performance and economic measures. For growth traits, greater commercial level response was for systems with higher sow replacement rates, 110 to 115% of lowest response. Phenotypic changes in net returns ranged from $.85 to 1.01 x pig-1 x yr-1. Average growth performances were highest for systems with greatest genetic trend. Highest kilograms.sow-1 x year-1 finished was for 10-parity commercial alternatives. System differences in total costs and returns per pig resulted primarily from differences in replacement costs. Removal of the gilt system from analyses often reduced ranges among systems for economic measures by more than 70%. Systems with the lowest commercial replacement rates were most profitable. Within these systems, those with higher genetic change had highest net returns. For high replacement rates, no more than 175% of market value could be paid for gilts, but with lower sow replacement rates commercial units could justify as much as 450%.

Computer models were used to simulate integrated cow-calf-feedlot production systems. Angus (A), Charolais (C), Hereford (H), Limousin (L), and Simmental (S) purebreds and two- and three-breed rotational crossbreds were included. Models were deterministic and based on data reported primarily from the 1970s. Variation in carcass weights were determined to predict distributions of carcass weights and values for 272- to 318-kg carcasses. Data were updated to a 1984 base by increasing birth, weaning, yearling, and mature weights to account for genetic trends within breeds. Two slaughter end points were considered: 288-kg carcass weight and low Choice grade. At low Choice grade, accounting for variation in carcass weights around the 272- to 318-kg target weight increased the estimated efficiency of A and AH crosses (input costs/carcass value), whereas at the 288-kg end point, efficiency rankings among other breed combinations were relatively unchanged. Including genetic trends resulted in increased estimated efficiencies among breed combinations with previously underweight carcasses at low Choice (A and AH), measured either as input costs/carcass weight or lean weight values. Within breeds, accounting for genetic trends and variation for weights caused breeds to be ranked differently when evaluated at low Choice.

In recent years animal breeders have increasingly made use of output:input ratios and simple measures of economic efficiency, such as annual profits, as a basis for comparisons and evaluations of the commercial applicability of alternative beef breeds. In many instances, however, output:input ratios may produce fallacious indications of economic efficiency that may, in turn, lead to erroneous conclusions regarding the true commercial applicability of the breeds evaluated. Errors potentially arising from the use of output:input ratios in breed evaluations may be attributed to a combination of 1) a narrow range of input use values under which most breeds are evaluated and 2) the inability of output:input ratios, including average annual profitability, to reflect consistently the economic objectives of commercial cow-calf producers. An alternative basis for breed comparison and evaluation is, therefore, developed from economic theories related to optimal investment and asset replacement. Comparison of the results obtained with this alternative to those obtained from output:input ratio evaluation, including annual profitability, indicate that potential value differences of as much as 33% may result from the use of output:input ratios as a primary basis of commercial breed evaluation.

The objectives of this study were to determine 1) the effect of bull:heifer ratio on reproductive performance and associated costs and return on heifers in synchronized estrus and 2) the effect of estrus synchronization on reproductive performance and economic variables, in a multiple-sire, pasture breeding situation. Eight hundred yearling beef heifers and 28 mature, sexually experienced beef bulls were allotted to four treatments (two replicates per treatment) at bull:heifer ratios of 2 per 100 (1:50; Treatment 1), 2 per 100 (1:50; Treatment 2), 4 per 100 (1:25; Treatment 3), and 6 per 100 (1:16; Treatment 4). Treatment 1 (control) used nonsynchronized heifers, whereas heifers in Treatments 2, 3, and 4 were synchronized using the 33-d melengestrol acetate (MGA)-prostaglandin F2 alpha (PGF2 alpha) program. Pregnancy results after a 28-d breeding season indicate that there may be a limit to how many estrus-synchronized heifers bulls can impregnate. Treatment 2 showed a 6% decrease (P < .10) in pregnancy rate (77%) compared with Treatment 3 (83%), indicating that the bulls probably were not able to service all the synchronized heifers. Treatments 3 and 4 had similar pregnancy rates (83 and 84%, respectively). Treatment 4 had a 3-d advantage (P < .01) over Treatment 3 in average day of conception. However, based on economic analysis, Treatment 3 exhibited greater returns. Estrus synchronization failed to provide any advantage in pregnancy rate or day of conception. For unknown reasons, the control, nonsynchronized heifers cycled and conceived as if they were synchronized.(ABSTRACT TRUNCATED AT 250 WORDS)

Experimental lifetime performance data obtained from 156 straightbred Hereford, Angus, and Shorthorn and 172 first-cross heifers were used to estimate heterosis for economic efficiency in a 100-cow herd at age equilibrium under three culling policies and at terminal ages from 6 to 12 yr. All nonpregnant heifers and cows greater than 9 yr of age were culled. The culling policy for removal of nonpregnant cows from second parity through 9 yr of age were 1) no culling, 2) after two consecutive years (actual), and 3) all (imposed). Efficiency was calculated as input cost per unit of output value. A 10-yr average was used for costs of replacement heifers, cow units, and the ratio of calf:cull cow prices (PR), plus higher and lower PR. Input included costs for both cow units and purchased replacements. Output value included both weaned calves and cull cows. Optimum terminal age was mainly a function of PR: 9 yr for average and high PR, but 6 through 9 yr when PR was low, regardless of culling policy or breed groups. Efficiency differences among culling policies were small for high or average PR, but more culling for infertility was beneficial when PR was low. Estimated reductions in unit costs of output value under any culling policy or terminal age were approximately 6% from crossbred cows plus another 6% from crossbred calves, or a total of 12% from specific three-breed crossing of these British breeds. Cost reductions would be somewhat less for rotation crossbreeding but greater for mating smaller crossbred cows with sires of superior growth-carcass breeds.

Two generations of selection on restricted BLUP breeding values were applied in an experiment with laying hens. Selection had been on phenotype of income minus feed cost (IFC) between 21 and 40 wk of age in the previous five generations. The restriction of no genetic change in egg weight was included in the EBV for power-transformed IFC (i.e., IFCt, with t-values of 3.7 and 3.6 in the two generations, respectively). The experiment consisted of two selection lines plus a randomly bred control of 20 male and 80 female breeders each. Observations on 8,844 survivors to 40 wk were available. Relative to the base population average, the restriction reduced genetic gain in IFC from 4.1 and 3.9% to 2.0 and 2.2% per generation in the two selection lines, respectively. Average EBV for egg weight remained nearly constant after a strong increase in the previous five generations. Rates of genetic gain for egg number, body weight, and feed conversion (feed/egg mass) were not affected significantly. In the seventh generation, a genetic gain in feed conversion of 10.3% relative to the phenotypic mean of the base population was obtained.

A stochastic life-cycle swine production model was used to study the effect of female replacement rates in the dam-daughter pathway for a tiered breeding structure on genetic change and returns to the breeder. Genetic, environmental, and economic parameters were used to simulate characteristics of individual pigs in a system producing F1 female replacements. Evaluated were maximum culling ages for nucleus and multiplier tier sows. System combinations included one- and five-parity alternatives for both levels and 10-parity options for the multiplier tier. Yearly changes and average phenotypic levels were computed for performance and economic measures. Generally, at the nucleus level, responses to 10 yr of selection for sow and pig performance in five-parity herds were 70 to 85% of response in one-parity herds. Similarly, the highest selection responses in multiplier herds were from systems with one-parity nucleus tiers. Responses in these were typically greater than 115% of the response for systems with the smallest yearly change, namely, the five-parity nucleus and five- and 10-parity multiplier levels. In contrast, the most profitable multiplier tiers (10-parity) had the lowest replacement costs. Within a multiplier culling strategy, rapid genetic change was desirable. Differences between systems that culled after five or 10 parities were smaller than differences between five- and one-parity multiplier options. To recover production costs, systems with the lowest returns required 140% of market hog value for gilts available to commercial tiers, whereas more economically efficient systems required no premium.

A stochastic computer model was developed to simulate individual pigs in a hierarchical breeding system. The bioeconomic model was designed as a tool to facilitate the evaluation of selection, culling, and management strategies for a three-tiered breeding structure. Events such as mating, farrowing, and selection occurred weekly. Variables included number of pigs born alive, survival rate from birth to weaning, average daily gain and backfat at 110 kg, number of pigs weaned, feed per gain, days from weaning to 110 kg, age at puberty, and growth rate and weight of sows and service boars. Also included were probabilities of conception, return to estrus by week, survival, involuntary culling, male infertility, and unacceptable conformation. Variables important for selection were determined by breeding value, individual and maternal heterosis, parity, size of birth litter, sex, age of dam, genetic and environmental relationships between variables, and common litter, permanent, and random environmental effects. Variables derived from selection variables were computed by regression using phenotypic relationships between all variables. Also, a random environmental effect was added to predicted performance. Means and variances of variables differed between genetic lines. Production costs included feed, non-feed operating, fixed, and replacement stock costs. Income included market animals, culls, and replacements sold to lower tiers. Effects of changes in backfat on market value and sow maintenance feed costs were not modeled. An example is given to illustrate model output.

Data from feeder cattle teleauction sales in Georgia from 1977 to 1988 were analyzed using least squares analysis of variance to detect significant (P less than .05) influential factors on price. The sample was divided into two periods, 1977 to 1982 and 1983 to 1988, to test whether the influence of factors had changed over the time periods. The test of equality was rejected (P less than .01) using a Chow test, thus suggesting a change had occurred. Hereford breeds were discounted in the latter period whereas Angus breeds generated a premium in the earlier period. Treatment for specific diseases resulted in premium prices, as did preconditioning, during the 1983 to 1988 period. The effect of seasonality on prices decreased over the two time periods. The optimal lot size increased from 228 to 280 cattle during the time periods.

A study was conducted to examine effects of mating systems composed of natural service (NS) and AI in swine on farrowing rate, litter size, and labor requirements. Sows and gilts were bred once per day via one of the following treatments (d 1/d 2): NS/NS, NS/AI, AI/AI, and NS/none. Gilts bred with NS/AI, AI/AI, and NS/NS had higher (P less than .05) farrowing rates than gilts bred with NS/none matings. Similarly, farrowing rates were higher (P less than .05) in NS/AI than in NS/NS gilts. Numbers of pigs born alive were greater (P less than .05) in NS/NS, NS/AI, and AI/AI than in NS/none gilts. In sows, a treatment x time interaction (P less than .01) was present for farrowing rate. In the AI/AI treatment, farrowing rate increased (P less than .01) from 70.0% (wk 1 through 3) to 88.5% (wk 4 through 10). Farrowing rates were 87.3, 93.2, and 76.0% in the NS/NS, NS/AI, and NS/none groups, respectively, and did not change (P = .72) over time. Sows bred via NS/NS and NS/AI had larger litters (P less than .05) than NS/none sows. In the present study, if four or more sows and gilts were bred, then AI required less (P less than .05) time per animal than NS. Furthermore, gilts required more (P less than .05) time for breeding than sows. Results from this study demonstrate that gilts and sows responded differently to combinations of NS and AI in terms of reproductive performance. In addition, differences in labor requirements per sow or gilt between NS and AI matings were dependent on parity and daily breeding demands.

A stochastic dynamic model of reproduction and a deterministic cow-herd economic simulation model were used to evaluate how management decisions and reproductive performance interact to influence net income in a cow-calf operation (1,000 cows) for 1 yr of production. The stochastic model was used to determine herd performance when length of breeding season (45, 70, or 120 d) interacted with three postpartum intervals of anestrus (48, 65, or 90 d) and three conception rates at first service (60, 70, or 80%). Short, moderate, and long postpartum intervals were used to reflect differences in reproductive performance. In addition, replacement heifers were bred beginning either 3 wk ahead of the cow herd or at the same time as the cow herd. Fifty-four simulations were generated. Inputs into the economic model were herd performance, livestock and feed prices, nonfeed costs, and feed requirements for 1 yr of production. Feed requirements were calculated separately for each postpartum interval to reflect three different body condition scores, thin, moderate, and good, to correspond with long, moderate, and short postpartum intervals. Net income was greatest with 70-d breeding seasons when the postpartum interval was short or moderate. When the postpartum interval was long, net income was greatest with 120-d breeding seasons because pregnancy rates, as a result of the long breeding season, were highest and feed costs were lowest for thin cows. Overall, net income was greatest when cows were managed to have postpartum intervals of moderate length. Breeding heifers 3 wk before the cows provided the most economic benefit with long postpartum intervals.

Feed intake, weaning weight and direct and maternal contributions to weaning weight were estimated for four breeding systems using data collected between 1979 and 1986 from 773 cow-calf pairs at the Elora Beef Research Centre. Breeding systems included purebred Hereford (HE), small rotational dual purpose (SR) (a four-way rotational crossing system utilizing Tarentaise, Angus, Gelbvieh and Pinzgauer breeds), large rotational beef (LR) (composed of Maine-Anjou, Simmental and Charolais) and Angus-sired large rotational beef (AL) utilizing Angus as the sire breed and LR as the maternal breed. Large rotational dams had the highest feed intakes for both dry (8.9 kg DM/d) and lactation (11.5 kg DM/d) periods. Conversely, HE calves consumed the greatest amounts of creep feed (309 kg DM), followed by AL, SR and LR. The large rotational system had the highest weaning weights (265 kg) and direct (12.3 kg greater than average of observations) and maternal (9.6 kg greater than average of observations) contributions to weaning weight, followed by AL, SR and HE for all three traits. An equation was derived for net returns that included parameters for feed intake and direct and maternal weaning weight. A linear programming model was designed to incorporate this equation as the objective function and determine the breeding system(s) that maximized net returns under various production conditions. In general, LR produced the greatest net returns, followed by SR and either AL or HE, depending on specific resource constraints (limited feed supply or herd size) included in the model.(ABSTRACT TRUNCATED AT 250 WORDS)