Breeding objectives for the Boran breed in Kenya: Model development and application to pasture-based production systems

Bio‐economic profit models were developed and applied to evaluate biological and economic variables that characterize production systems utilizing the Boran breed. Production systems were described according to their sale age (24 months short‐fed or 36 months long‐fed), levels of input (low, medium or high) and final goal (beef or dual purpose) representing practical circumstances that exist in the various beef cattle farms in Kenya. The input variables were classified into production and economic variables. The outputs from the profit models included revenue, costs and feed intake of cows, heifers and steers in the different production systems. These models can be used to simulate changes in production and marketing circumstances. The biological relationships and assumptions in the model are general and flexible and can therefore be applied to a wide range of beef cattle production circumstances by changing the input variables. In addition, by modifying the herd dynamics and management variables this model may be applied in Kenya or other countries to production systems that utilize indigenous cattle genetic resources or their crosses with Bos taurus breeds.     

Breeding goals for the Kenya Dual Purpose goat. II. Estimation of economic values for production and functional traits

Economic values for production traits (milk yield, MY, kg; 12-month sale weight, LW, kg; consumable meat percentage, CMP) and functional traits (doe live weight, DoWT, kg; number of kids weaned, NKW; kidding frequency, KF; kidding rate, KR, %; doe weaning rate, DoWR, %; doe survival rate, DoSR, %; post-weaning survival rate, PoSR, %; pre-weaning survival rate, PrSR, % and; residual feed intake of yearlings, RFIgamma, kg and does RFId, kg) were estimated for the Kenya Dual Purpose goat (KDPG) for systems under two bases of evaluation. The production systems included smallholder low-potential (SLP), smallholder medium-potential (SMP) and smallholder high-potential (SHP), while the bases of evaluation considered were fixed flock-size and fixed feed resource. Under both bases of evaluation, economic values were highest in SMP apart from the economic values for feed intake-related traits (RFIy and RFId). In SMP, the economic values under fixed flock-size scenario were KSh 71.61 (LW), 20.90 (MY), 45.20 (CMP), 13.68 (NKW), 3.61 (KF), 6.52 (KR), 12.39 (DoWR), 22.96 (DoSR), 22.87 (PoSR), 13.18 (PrSR), -2.76 (RFIy) and -3.00 (RFId). The corresponding economic values under fixed feed resources scenario were KSh 73.28, 29.39, 45.20, 16.91, 4.76, 9.45, 13.84, 25.67, 25.15, 16.19, -2.76 and -3.00. Generally in all production systems, economic values for most traits were higher under fixed feed resource than under fixed flock-size scenario. In all systems, the economic values for most of the traits were sensitive to changes in prices of feed, milk and meat. The positive economic values for most traits under fixed flock-size scenario and fixed feed resource indicates that a unit increase in genetic merit for the traits would have a positive effect on the profitability of the systems.     

Economic values for production and functional traits of Small East African goat using profit functions

Economic values for production traits (milk yield, MY, g; 12-month live weight, yLW, kg; consumable meat percentage, CM, %) and functional traits (mature doe live weight, DoLW, kg; mature buck live weight, LWb, kg; kidding frequency, KF; pre-weaning survival rate, PrSR, %; post-weaning survival rate, PoSR,%; doe survival rate, DoSR, %; and residual feed intake, RFI, kg) were estimated using profit functions for the Small East African goat. The scenario evaluated was a fixed flock size, and the resultant economic values (Kes per doe per year) were 34.46 (MY), 62.35 (yLW), 40.69 (CM), 0.15 (DoLW), 2.84 (LWb), 8.69 (KF), 17.38 (PrSR), 16.60 (PoSR), 16.69 (DoSR) and ?3.00 (RFI). Similarly, the economic values decreased by ?14.7 % (MY), ?2.7 % (yLW), ?23.9 % (CM), ?6.6 % (DoLW), ?98 % (LWb), ?8.6 % (KF), ?8.2 % (PrSR), ?8.9 % (PoSR), ?8.1 % (DoSR) and 0 % (RFI) when they were risk rated. The economic values for production and functional traits, except RFI, were positive, which implies that genetic improvement of these traits would have a positive effect on the profitability in the pastoral production systems. The application of an Arrow-Pratt coefficient of absolute risk aversion (λ) at the level of 0.02 resulted in a decrease on the estimated economic values, implying that livestock keepers who were risk averse were willing to accept lower expected returns. The results indicate that there would be improvement in traits of economic importance, and, therefore, easy-to-manage genetic improvement programmes should be established.     

Breeding objectives for beef cattle used in different production systems: 1. Model development

A bio-economic model was developed to evaluate utilization of beef bulls in a variety of production systems. The model can simulate life-cycle production of both beef and dairy cow herds with or without an integrated feedlot system. The Markov chain approach is used to simulate herd dynamics. The herd is described in terms of animal states and possible transitions among them. Equilibrium herd structures of the integrated production systems are calculated in their stationary states. The economic efficiency of each system is a function of biological traits of animals and of management and economic parameters. The model allows estimation of marginal economic values for 16 traits separately in each system. The economic weight for each trait or direct and maternal trait component in each selection group and breed of interest is then calculated as the weighted sum of the economic values for the trait in all production systems in which the selection group has an impact. Weighting factors for each system are computed as the product of the number of discounted expressions for direct and maternal trait components transmitted in that system by the selection group and the proportion of total cows belonging to each system.     

鲁西黄牛肉用品系育种目标性状经济权重计算

根据鲁西黄牛肉用品系的育种和生产实际,在基础母牛群体规模固定的二阶开放核心群育种生产体系下,构建了核心群和商品群中犊牛、青年母牛、青年公牛、成年母牛、成年公牛和育肥牛6个群体,包含断奶重、周岁重、成年母牛体重、育肥期日增重、胴体等级、屠宰率、初产年龄、产犊间隔和生产年限9个目标性状的利润函数模型。采用边际预算法计算目标性状的经济值,经贴现指数和遗传标准差校正后估算其经济权重。结果表明,6个群体体系中,每头母牛年利润为-1033.96元;9个目标性状经济值分别为:1.44元/kg,1.49元/kg,-3.02元/kg,1.81元/g,315.45元/级,66.85元/%,-0.54元/d,-4.43元/d,0.09元/d;相对经济权重分别为0.11,0.11,0.14,0.26,0.14,0.12,0.01,0.08,0.03。结果表明,鲁西黄牛从役肉兼用向专门化肉用方向选育,需要加强生长发育性状选择的同时,兼顾胴体性状和繁殖性状。     

Bioeconomic evaluation of embryo transfer in beef production systems: III. Embryo lines for producing bulls.

A model was developed for the economic evaluation of embryos for producing bull lines for use in commercial beef production. The fundamental concept underlying the model is that a cloned and sexed embryo of known genetic characteristics for beef traits is used to produce a bull. After reaching physiological maturity, the bull is used in natural matings. Equations relating feed energy requirements and growth rates based on NRC requirements and costs and returns discounted to present value allow investigation of expected economic merits of progeny from different embryo bull lines. The model has the flexibility to determine optimal embryo characteristics for different production environments. Model sensitivity to variation in progeny sex ratios, growth rates, yield and quality grades, and herd fertility characteristics was examined. Net present values (NPV) per embryo transferred were determined at the optimal marketing age of progeny produced from mating the bull to 30 cows per year for 5 yr. Relative to the lowest NPV of $18,209 for progeny with an expected quality grade of Select and yield grade of 4 at 400 d, increments in NPV ranged from $329 to $22,708 depending on differences in expected progeny carcass grade characteristics. The difference between NPV for 100% male and 40% male sex ratios was $7,518. The NPV differences between progeny growth rates of 1.6 and .9 kg/d holding herd conception rate constant at .9 and .5 were $8,311 and $4,611, respectively. The model evaluates relative economic values of embryo lines for producing bulls, accommodating interactions among progeny characteristics, and environments.     

The economic value of days open in Holstein cows in Japan based on simulated changes in conception rate

Increasing herd‐life length and culling parity with increasing conception rate (CR) is necessary to increase lifetime profit from dairy cow production. Economic values of days open (DO) were determined by calculating changes in fertility traits, herd‐life length, and milk yield when the simulated CR were changed in increments of 1% from ?5% to 5% from the basal levels, which were obtained for Hokkaido and regions other than Hokkaido separately. When CR increased, number of artificial inseminations, DO, and milking length decreased. Furthermore, culling parity, and annual milk yield increased. Herd‐life length increased in Hokkaido and decreased in the other regions. The economic values of CR were 1,623.8 to 946.8 yen and of DO were 857.4 to 399.0 yen. Relative economic values of milk yield to days open per genetic standard deviation were higher in the other regions than in Hokkaido where the economic effect of selection for DO was expected to be equal to selection for 305‐day milk yield and herd life. If the survival rate of multipara cows in the other regions increases, then the economic value of DO would similarly increase in Hokkaido.     

Effects of production circumstances on expected responses for growth and carcass traits to selection of bulls in Japan.

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.     

Effects of incorporating environmental cost and risk aversion on economic values of pig breeding goal traits

Economic values (EVs) of traits, accounting for environmental impacts and risk preferences of farmers, are required to design breeding goals that contribute to both economic and environmental sustainability. The objective of this study was to assess the effects of incorporating environmental costs and the risk preferences of farmers on the EVs of pig breeding goal traits. A breeding goal consisting of both sow efficiency and production traits was defined for a typical Brazilian farrow‐to‐finish pig farm with 1,500 productive sows. A mean‐variance utility function was employed for deriving the EVs at finishing pig level assuming fixed slaughter weight. The inclusion of risk and risk aversion reduces the economic weights of sow efficiency traits (17%) while increasing the importance of production traits (7%). For a risk‐neutral producer, inclusion of environmental cost reduces the economic importance of sow efficiency traits (3%) while increasing the importance of production traits (1%). Genetic changes of breeding goal traits by their genetic standard deviations reduce emissions of greenhouse gases, and excretions of nitrogen and phosphorus per finished pig by up to 6% while increasing farm profit. The estimated EVs could be used to improve selection criteria and thereby contribute to the sustainability of pig production systems.     

Application of aggregate genotype in beef cattle breeding

Abstract

When developing total merit indices (TMI's), estimated breeding values (EBV's) may be lacking for several traits. Methodology exists to address these challenges, calculating index weights using economic values and genetic (co)variances between traits included in the TMI and aggregate genotype. TMI's including production and functional traits were developed for beef breeds in the Norwegian breeding scheme, and potential for genetic gain was evaluated. Selection based on the TMI developed in this study was found to improve growth and carcass quality, while genetic deterioration was expected for calving difficulty. Alternative selection indices were applied to avoid these effects, but reduced the genetic gain for production traits. The results of our study show that is possible to achieve genetic gain in most economically important traits for beef cattle by using a TMI. When additional EBV's and genetic correlations become available, these should be included into the TMI for further improvement.     

Genetic relationships of fertility traits with test‐day milk yield and fat‐to‐protein ratio in tropical smallholder dairy farms

The test‐day milk fat‐to‐protein ratio (TD‐FPR) could serve as a measure of energy balance status and might be used as a criterion to improve metabolic stability and fertility through genetic selection. Therefore, genetic parameters for fertility traits, test‐day milk yield (TD‐MY) and TD‐FPR, as well as, their relationships during different stages of lactation, were estimated on data collected from 25 968 primiparous Thai dairy crossbred cows. Gibbs sampling algorithms were implemented to obtain (co)variance components using both univariate linear and threshold animal models and bivariate linear‐linear and linear‐threshold animal models with random regression. Average TD‐MY and TD‐FPR were 12.60 and 1.15. Heritability estimates for TD‐MY, TD‐FPR and selected fertility traits ranged from 0.31 to 0.58, 0.17 to 0.19 and 0.02 to 0.05, respectively. Genetic correlations among TD‐FPR and TD‐MY, TD‐FPR and fertility traits, and TD‐MY and fertility traits ranged from 0.05 to ‐0.44, from ‐0.98 to 0.98 and ‐0.22 to 0.79, respectively. Selection for lower TD‐FPR would decrease numbers of inseminations per conception and increase conception at first service and pregnancy within 90 days. In addition, cow selection based only on high milk production has strong effects to prolong days to first service, days open and calving interval.     

长白和大白猪主要生长性状的遗传参数估计

旨在分析母猪的出生年份、出生季节、初生重、开测日龄等固定效应对长白、大白猪主要生长性状的影响,并对目标生长性状进行遗传参数估计（遗传力、遗传方差、表型相关和遗传相关）,为猪的遗传改良提供基本依据。本试验利用GLM模型分析试验猪群（398头长白猪和1 176头大白猪）的固定效应对猪生长性状的影响,并采用多性状动物模型对目标性状进行遗传参数估计。目标生长性状包括达100 kg体重日龄（age to 100 kg,AGE）、达100 kg背膘厚（backfat to 100 kg,BF）、100 kg平均日增重（average daily gain to 100 kg,ADG）。研究表明,在大白和长白猪中,猪的出生年、出生季、初生重以及开测日龄对生长性状均具有极显著的影响（P<0.001）;长白猪的AGE、ADG和BF的遗传力分别为0.321、0.327和0.324,大白猪对应性状的遗传力分别为0.454、0.469和0.408;长白猪的ADG和AGE之间的遗传相关、表型相关分别为-0.990、-0.995,大白猪的ADG和AGE之间的遗传相关、表型相关分别为-0.993、-0.998,均呈现较强的负相关。长白、大白猪的生长性状（AGE、ADG、BF）均属于中等遗传力性状,其出生年份、出生季节、初生重和开测日龄对猪的生长性状影响较大。在遗传参数估计分析时,提高样本数量并提升表型数据质量,可以增加遗传参数估计的可靠性。本研究中的生长性状遗传参数估计结果较为可靠,可为后续的遗传改良提供参考。     

Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian for growth performance in central Ethiopia

Breed additive and non-additive effects, and heritabilities of birth weight (BWT), weaning weight (WWT), 6 months weight (SMWT), yearling weight (YWT), eighteen months weight (EWT), 2 years weight (TWT) and average daily weight gain from birth to 6 months (ADG1) and from 6 months to 2 years (ADG2) were estimated in Ethiopian Boran (B) cattle and their crosses with Holstein Friesian (F) in central Ethiopia. The data analysed were spread over 15 years. Ethiopian Boran were consistently lighter (p < 0.01) than the B-F crosses at all ages. Ethiopian Boran also gained lower weight than all the crosses. At birth, 50% F crosses were significantly (p < 0.01) lighter than all the other crosses. However, the differences in SMWT, YWT, EWT, TWT, ADG1 and ADG2 were all non-significant among the crosses. The individual additive breed differences between B and F breeds were positive and significant (p < 0.01) for all traits. The individual heterosis effects were significant (p < 0.05) for all traits except WWT for which the effect was non-significant. The maternal heterosis effects were significant (p < 0.01) for BWT (2.5 kg) and WWT (-3.0 kg). The heritability estimates for all traits in B and crosses were generally moderate to high indicating that there is scope for genetic improvement through selection. Selection within B and crossbreeding should be the strategy to enhance the growth performance under such production systems.     

Estimates of genetic parameters for Boran, Friesian, and crosses of Friesian and Jersey with the Boran cattle in the tropical highlands of Ethiopia: milk production traits and cow weight

Breed additive and non‐additive effects plus heritabilities and repeatabilities for milk yield per lactation (LMY), milk yield per day (DMY), lactation length (LL), annual milk yield (AMY), annual milk yield per metabolic body weight (AMYBW) and cow weight at calving (BW) were estimated for 5464 lactation records collected from purebred Boran (B), Friesian (F), and crosses of Friesian and Jersey (J) breeds with the Boran breed raised in the tropical highlands of Ethiopia. Single trait analysis was carried out by using two equivalent repeatability animal models. In the first model the genotype was fitted as a fixed group effect, while in the second model the genotype was substituted by breed additive, heterotic and recombination effects fitted as fixed covariates. Both the F and J breed additive effects, measured as a deviation from the B breed were significant (p < 0.01) for all traits, except for BW of the J. The F and J additive contributions were 2774 ± 81 and 1473 ± 362 kg for LMY, 7.1 ± 0.2 and 4.8 ± 0.8 kg for DMY, 152 ± 7 and 146 ± 31 days for LL, 2345 ± 71 and 1238 ± 319 kg for AMY, 20.6 ± 0.9 and 18.9 ± 4.3 kg for AMYBW, and 140 ± 4 and ?21 ± 22 kg (p > 0.05) for BW. The heterotic contributions to the crossbred performance were also positive and significant (p < 0.01) for all traits. The F₁ heterosis expressed as a deviation from the mid‐parent values were 22 and 66% for LMY, 11 and 20% for DMY, 29 and 29% for LL, 21 and 64% for AMY, 42 and 42% for AMYBW, and 2% (p < 0.05) and 11% for BW for the F × B and J × B crosses, respectively. The recombination effect estimated for the F × B crosses was negative and significant for LMY (?526 ± 192 kg, p < 0.01), DMY (?3.0 ± 0.4 kg, p < 0.001), AMY (?349 ± 174 kg, p < 0.05) and BW (?68 ± 11 kg, p < 0.001). For the J × B crosses the recombination loss was significant and negative only for DMY (?2.2 ± 0.7 kg, p < 0.05) and BW (?33 ± 17 kg, p < 0.05). The direct heritabilities (h²) estimated for LMY, DMY, LL, AMY and AMYBW were 0.24 ± 0.04, 0.19 ± 0.03, 0.13 ± 0.03, 0.23 ± 0.04 and 0.17 ± 0.05, respectively. Based on the genetic parameters estimated, the best breeding strategy to increased milk production under highland Ethiopian conditions is to apply selection on purebred base populations (Boran and Friesian) and then crossing them to produce F₁ dairy cows. However, for breeding decision based on total dairy merit, further investigations are needed for traits such as milk quality, reproduction, longevity and survival.     

Genetic relationships among direct and maternal components of milk yield and maternal weaning gain in a multibreed beef herd.

Data spanning 1980 to 1993 from a multibreed beef herd including primarily eight breeds (Angus, Charolais, Gelbvieh, Hereford, Maine-Anjou, Pinzgauer, Simmental, and Tarentaise) were used to obtain 2,207 records on 200-d weaning gain (WG) and 1,826 records on 200-d milk yield (MY), obtained by machine milking after oxytocin injection. Estimates of (co)variances for the two traits (WG and MY) were obtained with REML with breed of calf, breed of cow, and heterotic effects modeled for the two traits. Animal effects of calf (CalfWG, CalfMY) and cow (CowWG, CowMY) contributions to each trait were modeled including 2,926 animals. The permanent environmental effect of the cow was modeled for MY, with 693 levels. Estimates of breed differences were generally similar to literature estimates. Simmental, Charolais, and Maine-Anjou were highest for CalfWG, and Tarentaise, Simmental, Gelbvieh, and Maine-Anjou were highest for CowMY. Heterosis was estimated at 8.00, 2.58, 4.05, and 5.50% of the mean for CalfWG, CowWG, CalfMY, and CowMy, respectively. Variance attributable to repeated records on CowMy represented 9% of phenotypic variance. Heritabilities estimated were .22 and .24 for CalfWG and CowWG and .04 and .35 for CalfMY and CowMY. Genetic correlations estimated between CalfWG and CowWG and between CalfMY and CowMY were -.35 and -.64, respectively. A genetic correlation between CowWG and CowMY of .76 indicates that maternal weaning gain evaluations are a good predictor of a cow's potential for milk yield.     

Effect of subsidy regimes on economic values of functional traits in beef cattle breeding

We investigated the impact of five monetary subsidy regimes on economic values of traits in a cow–calf pasture production system with surplus calves fed for slaughter. The following regimes were analysed: (1) maximum prices for slaughter animals actually received in the Czech Republic during 2004, with no subsidies of any kind; (2) prices as in (1), with subsidies awarded per hectare of permanent grassland and per calf born; (3) prices as in (1), with subsidies awarded per hectare of agricultural land, per hectare of pasture and meadow, per beef cow in a forage system and per livestock unit; (4) prices as in (1), with subsidies awarded per hectare of agricultural land; (5) no subsidies, but prices received for slaughter animals that covered production costs and resulted in 1% profitability. The modelled farm showed negative profit under real price conditions with no subsidies (regime 1), which led to an underestimation of economic values for functional traits. The same results were obtained in regimes in which subsidies did not depend on the number of animals (3) or on meat production from the enterprise (4). Economic values of production traits (growth and carcass traits) did not vary among subsidy regimes. To determine optimum economic values for functional traits in beef cattle, we advocate using the method applied in subsidy regime 5, no subsidies but prices for slaughter animals that cover production cost and a small profit.     

Simulated efficiency of range beef production. I. Growth and milk production

A revised version of the Texas A&M University Beef Cattle Production Model was used to simulate the effects of growth, milk production and management system on biological and economic efficiency of beef production in a northern plains, range environment. Animals varying in genetic potential for birth weight (BWA), yearling weight (YW), mature weight (WMA) and milk production (PMA) were simulated under both a weanling system of management (weaned calves custom-fed in the feedlot) and a yearling system (calves wintered on the ranch, then custom-fed after their second summer). The yearling system of management was biologically less efficient, but economically more efficient than the weanling system due primarily to heavier slaughter weights of fed animals. The advantage of the yearling system was most apparent for smaller genotypes. Herd efficiency improved with decreased BWA and increased YW, but changed little when WMA was varied while other growth traits were held constant. Increased PMA was favored for production of live weight at weaning and for production of slaughter product when feedlot costs were high. Increased PMA was not favored when feed costs for the cow herd were high. Economic weights generated from the simulation indicated the importance of selection for rapid early growth followed by selection for lighter birth weight. While larger genotypes were generally favored in this study, optimal cow size depended on economic conditions. Larger types were more biologically efficient and more economically efficient using standard costs, but medium- and small-size cattle were more efficient when feedlot costs were high. Small cattle were least efficient when feed costs for the cow herd were high.     

山东省荷斯坦奶牛体型性状遗传参数估计及系谱世代数的影响

旨在估计山东省荷斯坦奶牛体型性状遗传参数,为育种方案制定提供参考。本研究收集了山东省2010—2020年间的144个牛场31 963头头胎中国荷斯坦母牛的20个体型性状记录,其中性状评分由线性分转为功能分,将场、泌乳月、产犊月龄、鉴定员效应为固定效应,以个体的加性遗传效应作为随机效应,利用 DMU 软件,采用AI-REML结合EM算法并配合动物模型进行遗传参数估计。结果表明,体型性状的遗传力属于中等偏低水平,其估计值变化范围为0.049(后肢侧视)到 0.282(棱角性),性状间的遗传相关范围为-0.558(前乳头位置与乳房深度)至0.717(蹄踵深度与蹄角度)。体躯容量各性状间的遗传相关范围为0.118 (体深与体高)至0.461(胸宽与腰强度);尻角度与尻宽的遗传相关为-0.251;肢蹄各性状间的遗传相关范围为-0.035(蹄踵深度与后肢后视)到 0.717(蹄踵深度与蹄角度);泌乳系统各性状间的遗传相关范围为-0.558 (前乳头位置与乳房深度)至0.587(悬韧带与前乳房附着)。另外,体型性状的遗传力估计标准误在查找的系谱世代数为3的情况下为最小,这可能是由于系谱数据完整性的限制导致了该种情况,具体还需要进一步验证。加强对体型性状中遗传力较高且与泌乳系统遗传相关较强性状的选择,有利于奶牛生产性能的提高。另外,在本研究数据中,使用前3代系谱估计的遗传力标准误最小,因此,利用前3代系谱估算遗传参数可能较佳。     

Autoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle

Autoregressive (AR) and random regression (RR) models were fitted to test-day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and −0.019 (−0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and −0.022 (−0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder.     

Economic values and selection index in different Angus‐Nellore cross‐bred production systems

Bioeconomic models were developed to calculate economic values (EV) for economically important traits in beef cattle, to evaluate the impact of these traits on production profitability, to assess possible market changes with a payment system and to develop economic selection indexes for Angus cattle for two production systems. Two beef cattle production systems were simulated as follows: a cow‐calf cycle (CC) and a complete cycle (CoC). Following selection, positive changes in the EV were observed. In the CC, each 1.0% increment in weaning weight (WW), weaning rate (WR) and pregnancy rate (PR) resulted in increases in US$ 1.30, US$ 3.68 and US$ 3.55 per cow/year in profit, respectively. In the CoC, EV of US$ 1.01, US$ 1.79, US$ 1.19, US$ 1.34, US$ 6.84 and US$ 7.86 per cow/year were obtained for WW, year weight, yearling weight, final weight, WR and PR, respectively. The payment system for carcass quality showed that the scenario considering that 100% of the animals displayed uniform carcasses exhibited the highest EV and was considered optimal. Considering the sensitivity analysis, the price paid per animal was the factor that most affected the EV in both systems. The selection indexes obtained may be used in similar production systems, and the use of EV and selection indexes are important tools for any production system with positive change in profit after selection.