Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Optimization of goose breast meat tenderness by rapid ultrasound treatment using response surface methodology and artificial neural network

The aim of this study was to develop a prediction model on tenderization of goose breast meat by response surface methodology (RSM) and artificial neural network (ANN). The experiments were operated on the basis of a three‐level, three‐variable (ultrasound power, ultrasound time, and storage time) Box‐Behnken experimental design. Under RSM and ANN optimum conditions, experimental Meullenet‐Owens razor shear (MORS) of meat (1862.6 g and 1869.9 g) was in reasonable agreement with predicted one. Nevertheless, better prediction capability of ANN was proved by higher R² (0.996) and lower absolute average deviation = 4.257) compared to those for RSM (0.852 and 16.534), respectively. These results revealed that ANN was more accurate and much better than RSM model for the optimization of tenderness of meat. The optimum conditions of ultrasound power, ultrasound time, and storage time given by ANN were 812 W, 24.5 min and 25.7 hr, respectively. Under the optimized condition, the cooking loss of meat significantly decreased by ultrasound treatment compared with untreated meat. Lower cooking loss and MORS at the optimal condition were beneficial to meet the satisfaction of consumer and producers for meat factory.     

High levels of whole raw soybean in diets for Nellore bulls in feedlot: effect on growth performance,carcass traits and meat quality

The objective of this study was to evaluate the effect of whole raw soybean (WRS) in the finishing diet of Nellore cattle on productive performance, carcass traits, meat quality, fatty acid profile of meat, and blood parameters. In a completely randomized design, 52 Nellore bulls (mean body weight ± SD: 380 ± 34 kg) were allotted for 84 days. The animals received the following diets with a forage: concentrate ratio of 40/60: (i) WRS0: control diet without soybean grains; (ii) WRS8: diet containing 8% WRS in dry matter basis; (iii) WRS16: diet containing 16% WRS, and (iv) WRS24: diet containing 24% WRS. At intervals of 28 days, the animals were weighed, muscle and adipose tissue was analysed by ultrasound, and blood samples were collected. The animals were slaughtered on day 85 and liver weight and hot carcass weight were measured during slaughter. The pH and carcass dressing were calculated at 24 h after slaughter. Longissimus dorsi muscle samples were collected for the determination of fatty acid profile of meat, ether extract, tenderness and sensory analysis of meat aged for 14 days. Blood cholesterol content increased linearly with increasing proportion of whole raw soybean grains. The diet did not affect performance or carcass attributes. The WRS8 had the highest shear force values. In fatty acid profile, C14:0 decreased (p = 0.05), whereas 16:1, 20:0 and 20:1 fatty acids increased linearly with increasing proportion of WRS (p < 0.05). However, concentration of conjugated linoleic acid cis 9, trans 11 and 17:0 increased with WRS24 and WRS16. In the sensory analysis, WRS24 was more tender with respect to the other treatments (p < 0.05). Finally, the inclusion of WRS in the finishing diet of feedlot Nellore bulls only evidenced little changes in fatty acid profile and tenderness, in animals fed diets containing 16 or 24% soybean.     

Tag-SNP selection using Bayesian genomewide association study for growth traits in Hereford and Braford cattle

The aim of this study was to perform a Bayesian genomewide association study (GWAS) to identify genomic regions associated with growth traits in Hereford and Braford cattle, and to select Tag-SNPs to represent these regions in low-density panels useful for genomic predictions. In addition, we propose candidate genes through functional enrichment analysis associated with growth traits using Medical Subject Headings (MeSH). Phenotypic data from 126,290 animals and genotypes for 131 sires and 3,545 animals were used. The Tag-SNPs were selected with BayesB (π = 0.995) method to compose low-density panels. The number of Tag-single nucleotide polymorphism (SNP) ranged between 79 and 103 SNP for the growth traits at weaning and between 78 and 100 SNP for the yearling growth traits. The average proportion of variance explained by Tag-SNP with BayesA was 0.29, 0.23, 0.32 and 0.19 for birthweight (BW), weaning weight (WW205), yearling weight (YW550) and postweaning gain (PWG345), respectively. For Tag-SNP with BayesA method accuracy values ranged from 0.13 to 0.30 for k-means and from 0.30 to 0.65 for random clustering of animals to compose reference and validation groups. Although genomic prediction accuracies were higher with the full marker panel, predictions with low-density panels retained on average 76% of the accuracy obtained with BayesB with full markers for growth traits. The MeSH analysis was able to translate genomic information providing biological meanings of more specific gene products related to the growth traits. The proposed Tag-SNP panels may be useful for future fine mapping studies and for lower-cost commercial genomic prediction applications.     

鲁西黄牛与利鲁杂交牛肉质特性的研究

本研究采用二因子多水平有重复的试验设计,对我国著名的优良地方品种鲁西黄牛及利鲁杂交牛的不同解剖部位（背最长 股二头肌）肉品的理化性状各食用品质特性进行了系统深入的研究。结果表明;鲁西黄年号利鲁杂交牛的各部位肉品ＰＨ值下降缓慢,肉品保水性能好、贮存损失较低和熟肉率较高,并且其肉品蛋白质含量高,氨基酸和矿物质营养丰富,具有良好的食用品质特性。分析表明;品种因子地肉品的评硬度,嫩度、肉口中脂肪含量、必需     

Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data

Wearable sensors have been explored as an alternative for real-time monitoring of cattle feeding behavior in grazing systems. To evaluate the performance of predictive models such as machine learning (ML) techniques, data cross-validation (CV) approaches are often employed. However, due to data dependencies and confounding effects, poorly performed validation strategies may significantly inflate the prediction quality. In this context, our objective was to evaluate the effect of different CV strategies on the prediction of grazing activities in cattle using wearable sensor (accelerometer) data and ML algorithms. Six Nellore bulls (average live weight of 345 ± 21 kg) had their behavior visually classified as grazing or not-grazing for a period of 15 d. Elastic Net Generalized Linear Model (GLM), Random Forest (RF), and Artificial Neural Network (ANN) were employed to predict grazing activity (grazing or not-grazing) using 3-axis accelerometer data. For each analytical method, three CV strategies were evaluated: holdout, leave-one-animal-out (LOAO), and leave-one-day-out (LODO). Algorithms were trained using similar dataset sizes (holdout: n = 57,862; LOAO: n = 56,786; LODO: n = 56,672). Overall, GLM delivered the worst prediction accuracy (53%) compared with the ML techniques (65% for both RF and ANN), and ANN performed slightly better than RF for LOAO (73%) and LODO (64%) across CV strategies. The holdout yielded the highest nominal accuracy values for all three ML approaches (GLM: 59%, RF: 76%, and ANN: 74%), followed by LODO (GLM: 49%, RF: 61%, and ANN: 63%) and LOAO (GLM: 52%, RF: 57%, and ANN: 57%). With a larger dataset (i.e., more animals and grazing management scenarios), it is expected that accuracy could be increased. Most importantly, the greater prediction accuracy observed for holdout CV may simply indicate a lack of data independence and the presence of carry-over effects from animals and grazing management. Our results suggest that generalizing predictive models to unknown (not used for training) animals or grazing management may incur poor prediction quality. The results highlight the need for using management knowledge to define the validation strategy that is closer to the real-life situation, i.e., the intended application of the predictive model.     

Accuracy of genomic prediction using different models and response variables in the Nordic Red cattle population

Breeding animals can be accurately evaluated using appropriate genomic prediction models, based on marker data and phenotype information. In this study, direct genomic values (DGV) were estimated for 16 traits of Nordic Total Merit (NTM) Index in Nordic Red cattle population using three models and two different response variables. The three models were as follows: a linear mixed model (GBLUP), a Bayesian variable selection model similar to BayesA (BayesA*) and a Bayesian least absolute shrinkage and selection operator model (Bayesian Lasso). The response variables were deregressed proofs (DRP) and conventional estimated breeding values (EBV). The reliability of genomic predictions was measured on bulls in the validation data set as the squared correlation between DGV and DRP divided by the reliability of DRP. Using DRP as response variable, the reliabilities of DGV among the 16 traits ranged from 0.151 to 0.569 (average 0.317) for GBLUP, from 0.152 to 0.576 (average 0.318) for BayesA* and from 0.150 to 0.570 (average 0.320) for Bayesian Lasso. Using EBV as response variable, the reliabilities ranged from 0.159 to 0.580 (average 0.322) for GBLUP, from 0.157 to 0.578 (average 0.319) for BayesA* and from 0.159 to 0.582 (average 0.325) for Bayesian Lasso. In summary, Bayesian Lasso performed slightly better than the other two models, and EBV performed slightly better than DRP as response variable, with regard to prediction reliability of DGV. However, these differences were not statistically significant. Moreover, using EBV as response variable would result in problems with the scale of the resulting DGV and potential problem due to double counting.     

Gender status effect on carcass and meat quality traits of feedlot Angus × Nellore cattle

The study evaluated the effect of gender status on carcass and meat quality of feedlot Angus × Nellore cattle. A total of 176 cattle, 20 months old, were confined for 190‐days and assigned to four treatments: bulls, immunocastrated, steers, and heifers. Bulls had greater rib eye area and HCW (p = 0.0001). Heifers had increased fat thickness (p = 0.0001). Steers and heifers had higher marbling scores (p = 0.0001). There was interaction between gender and aging time for Warner‐Bratzler Shear Force (p = 0.0002), L* (p = 0.0118), and b* (p = 0.0113) values of beef. The sensory panel results showed that beef from bulls had the lowest consumer overall acceptance (p = 0.0278). Especially, regardless tenderness, steers and immunocastrated beef were considered tender, independent of aging time. Beef produced by heifers, steers, and immunocastrated is considered to be of higher quality than bulls. Thus, it is may be an interesting alternative to produce high‐quality beef than bulls, to attend the consumer demand for high‐quality products. Additionally, the low fatty acids n6 levels and low n6:n3 ratio, high levels of CLA, MUFAs, and oleic acid suggests that the heifer meat is favorable for human health.     

Characteristics of Biceps femoris and Longissimus thoracis muscles of five cattle breeds grown in a feedlot system

Our experiment was conducted to study physical quality and chemical composition of meat of Angus (A), Hereford (H), Friesian Holstein (FH), Australian Commercial Cross (ACC) and Murray Grey (MG) cattle breeds grown in a feedlot system. Significant differences were observed among five cattle breeds for cooking loss, tenderness, fatty acid composition, collagen and cholesterol content of meat. However, pH, water‐holding capacity, water, ash, fat and crude protein contents were not different. Cholesterol content of meat of A and FH was lower (P < 0.01) than that of H, ACC and MG. Acidity (pH), cooking loss, shear force, water, ash, crude protein, collagen and cholesterol content of Biceps femoris muscle were higher than those of Longissimus thoracis muscle, but water‐holding capacity and fat content were lower. Unsaturated fatty acid content of Biceps femoris muscle was higher (P < 0.01) than that of Longissimus thoracis. In conclusion, the differences among cattle breeds had a great effect on cooking loss, shear force, collagen, fatty acid composition and cholesterol of meat, but had little effect on water‐holding capacity, pH and proximate composition of meat. The meat of Hereford cattle was the best quality, because of the lowest shear force, cooking loss and collagen. Longissimus thoracis muscle was relatively better in cooking loss, tenderness and collagen content than Biceps femoris muscle.     

Effect of animal age,postmortem chilling rate,and aging time on meat quality attributes of water buffalo and humped cattle bulls

The study was aimed to investigate the influence of animal age, post‐slaughter chilling rate, and aging time on meat quality of M. longissimus dorsi (LD) of water buffalo (Bubalus bubalis) and humped cattle (Bos taurus indicus) bulls. After slaughtering, one side of carcasses was subjected to rapid chilling (RC) (0 ± 2°C) and other side was hanged in controlled room temperature (25 ± 2°C) for 3 hr, then allowed to the chiller (0 ± 2°C). The meat quality traits were analyzed at 1, 7, and 14 days of storage. It was noted that rapidly chilled carcasses from the younger animals of both species missed the ideal pH/temperature window, which affects the toughness of the meat. Buffalo meat presented higher shear force, color L* values, and lower b* value as compared to the cattle meat. Moreover, meat shear force values decreased while all color coordinates and cooking loss values increased with lengthening the storage time in both age groups of cattle and buffalo. In conclusion, the tenderness of cattle meat was superior to that of buffalo and RC adversely affect the shear force values of young cattle and both age groups of buffalo bulls.     

Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese–Nordic reference population

This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows genotyped with 54K chip, 510 Nordic Holstein bulls genotyped with HD chip, and 4398 Nordic Holstein bulls genotyped with 54K chip and with deregressed proofs for five milk production traits. Based on these data, the accuracy of imputation from 54K to HD marker data and the accuracy of genomic predictions in Chinese Holstein were assessed. The allele correct rate increased around 2.7 and 1.7% in imputation from the 54K to the HD marker data for Chinese Holstein bulls and cows, respectively, when the Nordic HD‐genotyped bulls were included in the reference data for imputation. However, the prediction accuracy was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy of genomic predictions increased 6.5 percentage points together with a reduction of prediction bias. The HD markers did not outperform the 54K markers in genomic prediction based on the present data. The results indicate that for Chinese Holsteins, it is necessary to genotype more individuals with 54K chip to increase reference population rather than increasing marker density.     

Across-breed validation study confirms and identifies new loci associated with sexual precocity in Brahman and Nellore cattle

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10^–3) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10^–3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.     

Carcass quality and meat tenderness of Hawaii pasture-finished cattle and Hawaii-originated, mainland feedlot-finished cattle

The objective of this study was to compare the carcass quality and meat tenderness of Hawaii cattle finished on subtropical pasture with those of mainland US feedlot-finished cattle that were shipped from Hawaii after weaning. Rib-eye steak samples were collected from 30 feedlot-finished cattle harvested at a slaughter house in Washington State, USA and from 13 subtropical pasture-finished cattle harvested at a local slaughter house in Hawaii, then shipped to meat science laboratory at the University of Hawaii, Manoa. Samples were aged for 2?weeks at 4°C and frozen for later proximate analysis and meat tenderness measurement. Feedlot-finished cattle had significantly heavier carcass weight (353 vs 290?kg) and thicker backfat (13.5 vs 6.6?mm), but no significant difference was observed in rib-eye area between the two groups. Marbling score (Small) and United States Department of Agriculture quality grade (Choice) of the pasture-finished beef were not significantly (P?相似文献   

Signatures of selection in Charolais beef cattle identified by genome‐wide analysis

Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8–59.3 Mb on BTA 4; 67.5–69.3 on BTA 5; 39.5–41.0 Mb on BTA 6; and 26.4–29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits.     

Weighted single‐step genome‐wide association study and pathway analyses for feed efficiency traits in Nellore cattle

The aim was to conduct a weighted single‐step genome‐wide association study to detect genomic regions and putative candidate genes related to residual feed intake, dry matter intake, feed efficiency (FE), feed conversion ratio, residual body weight gain, residual intake and weight gain in Nellore cattle. Several protein‐coding genes were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for these traits. These genes were associated with insulin, leptin, glucose, protein and lipid metabolisms; energy balance; heat and oxidative stress; bile secretion; satiety; feed behaviour; salivation; digestion; and nutrient absorption. Enrichment analysis revealed functional pathways (p‐value < .05) such as neuropeptide signalling (GO:0007218), negative regulation of canonical Wingless/Int‐1 (Wnt) signalling (GO:0090090), bitter taste receptor activity (GO:0033038), neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction (bta0742) and glucagon signalling pathway (bta04922). The identification of these genes, pathways and their respective functions should contribute to a better understanding of the genetic and physiological mechanisms regulating Nellore FE‐related traits.     

Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low‐density SNP panels: Evidence that long‐range LD is a major contributing factor

Previously accurate genomic predictions for Bacterial cold water disease (BCWD) resistance in rainbow trout were obtained using a medium‐density single nucleotide polymorphism (SNP) array. Here, the impact of lower‐density SNP panels on the accuracy of genomic predictions was investigated in a commercial rainbow trout breeding population. Using progeny performance data, the accuracy of genomic breeding values (GEBV) using 35K, 10K, 3K, 1K, 500, 300 and 200 SNP panels as well as a panel with 70 quantitative trait loci (QTL)‐flanking SNP was compared. The GEBVs were estimated using the Bayesian method BayesB, single‐step GBLUP (ssGBLUP) and weighted ssGBLUP (wssGBLUP). The accuracy of GEBVs remained high despite the sharp reductions in SNP density, and even with 500 SNP accuracy was higher than the pedigree‐based prediction (0.50–0.56 versus 0.36). Furthermore, the prediction accuracy with the 70 QTL‐flanking SNP (0.65–0.72) was similar to the panel with 35K SNP (0.65–0.71). Genomewide linkage disequilibrium (LD) analysis revealed strong LD (r² ≥ 0.25) spanning on average over 1 Mb across the rainbow trout genome. This long‐range LD likely contributed to the accurate genomic predictions with the low‐density SNP panels. Population structure analysis supported the hypothesis that long‐range LD in this population may be caused by admixture. Results suggest that lower‐cost, low‐density SNP panels can be used for implementing genomic selection for BCWD resistance in rainbow trout breeding programs.     

Association of markers in the bovine CAPN1 gene with meat tenderness in large crossbred populations that sample influential industry sires

Two previously identified single-nucleotide polymorphism markers located within the micromolar calcium-activated neutral protease gene (CAPN1) were evaluated for their association with variation in meat tenderness using one commercial sample of Simmental x Angus crossbred calves and one multibreed, crossbred research herd. The commercial sample included 362 animals sired by 23 registered Simmental bulls bred to unregistered Angus cows and represented current industry animals in which to test the predictive merit of the markers. The second sample was a research herd including 564 steers from the Germplasm Evaluation Cycle VII population at the U.S. Meat Animal Research Center, produced with semen from popular sires of the seven Bos taurus beef breeds with the most registrations in the United States (Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental) on Angus, Hereford, and MARC III cows. These animals form a relatively outbred population that constituted a stringent test of the predictive merit of the genetic markers, although small groups were half-sibs. Warner-Bratzler shear force measurements were used to determine tenderness phenotypes for all animals. The populations were genotyped for two markers that predict variation at amino acid positions 316 and 530 of the mu-calpain polypeptide, produced by the CAPN1 gene. Minor allele frequencies for markers 316 and 530 in the commercial sample were 0.17 and 0.37, respectively, and in the Cycle VII animals, were 0.20 and 0.28, respectively. Both markers showed association with shear force in the commercial sample (P = 0.04) and the Cycle VII population (P = 0.02), supporting the hypothesis that they represent potential markers to aid selection for improved meat tenderness in commercial populations of beef cattle in the United States.     

A genomewide association mapping study using ultrasound‐scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound‐derived measurements of the rib‐eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.     

Effect of postmortem treatments on the tenderness of meat from Hereford, Brahman and Brahman-cross beef cattle

The effect of postmortem aging (7, 14, 21 or 28 d), high-voltage electrical stimulation (stimulated or not stimulated) and blade tenderization (none or once; crossbreds only) on the sensory and cooking properties of meat from four beef breeds or breed-types (purebred Hereford, purebred Brahman, Hereford x Brahman and Brahman x Hereford) was determined. The meat from purebred Brahman cattle that was not electrically stimulated was less tender and more variable in tenderness than that from other breed-types but electrical stimulation reduced these differences in tenderness. The Brahman crossbred steers produced meat that was not different in tenderness or variability in tenderness from that of purebred Hereford steers, although all were only judged "slightly tender." Electrical stimulation reduced the length of postmortem aging needed to reach a given level of tenderness regardless of breed or breed-type. Meat from crossbred animals that was blade-tendernized was not different in tenderness from meat that was electrically stimulated. The results of this investigation indicate that purebred Brahman muscle was inherently less tender, but postmortem tenderization procedures produced meat that was similar tenderness to that of the other breed-types used in this study.     

Genetic association between different criteria to define sexual precocious heifers with growth,carcass, reproductive and feed efficiency indicator traits in Nellore cattle using genomic information

The aim of this study was to estimate genetic parameters for different precocious calving criteria and their relationship with reproductive, growth, carcass and feed efficiency in Nellore cattle using the single‐step genomic BLUP. The reproductive traits used were probability of precocious calving (PPC) at 24 (PPC24), 26 (PPC26), 28 (PPC28) and 30 (PPC30) months of age, stayability (STAY) and scrotal circumference at 455 days of age (SC455). Growth traits such as weights at 240 (W240) and 455 (W455) days of age and adult weight (AW) were used. Rib eye area (REA), subcutaneous fat thickness (SFT), rump fat thickness (RFT) and residual feed intake (RFI) were included in the analyses. The estimation of genetic parameters was performed using a bi‐trait threshold model including genomic information in a single‐step approach. Heritability for PPC traits was moderate to high (0.29–0.56) with highest estimates for PPC24 (0.56) and PPC26 (0.50). Genetic correlation estimates between PPC and STAY weakened as a function of calving age. Correlation with SC455, growth and carcass traits were low (0.25–0.31; ?0.22 to 0.04; ?0.09 to 0.18, respectively), the same occurs with RFI (?0.09 to 0.08), this suggests independence between female sexual precocity and feed efficiency traits. The results of this study encourage the use of PPC traits in Nellore cattle because the selection for such trait would not have a negative impact on reproductive, growth, carcass and feed efficiency indicator traits. Stayability for sexual precocious heifers (PPC24 and PPC26) must be redefined to avoid incorrectly phenotype assignment.