Beef Cattle Population Research Articles

JENIS DAN POPULASI LALAT PADA TERNAK SAPI DI DESA TOLOK, KECAMATAN TOMPASO, KABUPATEN MINAHASA

TYPES AND POPULATION OF FLY ON BEEF CATTLE AROUND TOLOK VILLAGE AT TOMPASO DISTRICT OF MINAHASA REGENCY. The Study was conducted to evaluate types and population of fly on beef cattle around Tolok village at Tompaso district of Minahasa regency. Observation was applied during a month involving sixteen beef cattle. Flies were cached using insect net one time on every two weeks. Collections of flies were conducted three times and types of fly were also identified including their population. Results of observation showed that there were three types fly on beef cattle including Haematobia exigua, Stomoxys Calcitrans and Musca domestica. The population of these flies were Haematobia exigua of 94.43 individuals, Stomoxys Calcitrans of 10.49 individuals and Musca domestica of 7.74 individuals. The dominant fly during collection at Tolok village was type of Haematobia exigua. Key words: Fly population, dominating fly type, beef cattle.

292 Genetic trend for feed efficiency, growth and carcass traits in three Canadian beef cattle populations involved in the Kinsella breeding project.

292 Genetic trend for feed efficiency, growth and carcass traits in three Canadian beef cattle populations involved in the Kinsella breeding project.

Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle

The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.

Genetic parameters of longevity for improving profitability of beef cattle.

The objective of this study was to estimate genetic parameters for longevity and assess the suitability of using these selection criteria to improve the genetic merit of the beef cattle population of the Czech Republic. The performance record database, which contains records of 363,000 beef cattle animals of 19 breeds and their crosses, was used. The populations of Charolais and Aberdeen Angus were large enough that the genetic parameter estimations and all analyses were done for these breeds separately. Two similar approaches of longevity definition based on probabilities were considered as follows: productive longevity (PL), which is the number of calvings at target ages of 78, 90, 150, and 160 mo, and longevity (L), which is based on the probabilities of cow reappearance in the next parity. A multibreed single-trait animal model for L and a multitrait animal model for combinations of 78/150 and 90/160 mo for PL were used. Specific combinations of months were established based on the analysis and represented the critical culling rates in the studied population. The high genetic correlations (0.88-0.95) of the combination 90/160 suggested that the PL at 160 mo of age can be predicted on the basis of the value at 90 mo, which will make earlier selection possible. Combination 78/150 is less efficient in the Czech population of beef cattle due to the lower correlations (0.79-0.93) between traits. The estimated heritabilities were low for both traits (below 0.14), but the additive genetic variance was sufficient for identifying animals with high genetic merit.

Pedigree analysis for determination of genetic diversity in mexican beef cattle populations

El objetivo de este estudio fue evaluar la diversidad genética de siete poblaciones de bovinos para carne en México, mediante análisis de sus pedigríes. Los análisis se realizaron con el programa Endog, utilizando información de los animales inscritos en el libro genealógico nacional de cada raza. Los tamaños de los pedigríes estudiados fueron: Angus (AN)= 73,271; Brangus Negro (BN)= 68,474; Brangus Rojo (BR)= 12,925; Hereford (HE)= 13,248; Limousin (LI)= 53,221; Salers (SA)= 14,065; y Suizo Europeo (SE)= 184,788. En general, las poblaciones mostraron mejoras importantes en la integridad de sus pedigríes en los 10 años más recientes, con parámetros comparables a los publicados en otras poblaciones de bovinos. El intervalo generacional varió de 5.1 a 7.2 años entre razas. Los coeficientes de consanguinidad y de relación genética aditiva promedio fueron relativamente bajos en las diferentes poblaciones (0.9-4.2 y 0.3-6.5 %, respectivamente); aunque en algunas razas (BN, BR y HE) se detectaron incrementos de estos indicadores en los 10 años más recientes. El tamaño efectivo de población fluctuó entre 24 y 192, con valores menores que 50 en BR y SA. Los parámetros relacionados con la probabilidad de origen de los genes indican que las contribuciones desbalanceadas de los animales fundadores, los cuellos de botella y la deriva genética, han tenido un efecto importante en las poblaciones actuales, con la consecuente pérdida de diversidad genética. Se recomienda continuar o adoptar estrategias de apareamiento que minimicen la consanguinidad, y el uso intensivo de pocos animales para mantener la variabilidad genética de futuras generaciones, así como ampliar la diversidad genética mediante el uso estratégico de genes provenientes de otros países.

Gene set enrichment analysis of SNP data in dairy and beef cattle with bovine respiratory disease.

Bovine respiratory disease (BRD) is a complex disease that is associated with infection by bacterial and viral pathogens when cattle fail to adequately respond to stress. The objective of this study was to use gene set enrichment analysis of SNP data (GSEA-SNP) and a network analysis (ingenuity pathway analysis) to identify gene sets, genes within gene sets (leading-edge genes) and upstream regulators associated with BRD in pre-weaned dairy calves and beef feedlot cattle. BRD cases and controls were diagnosed using the McGuirk health scoring system. Holstein calves were sampled from commercial calf-raising facilities in California (1003 cases and 1011 controls) and New Mexico (376 cases and 372 controls). Commercial feedlot cattle were sampled from Colorado (500 cases and 499 controls) and Washington (504 cases and 497 controls). There were 102 and 237 unique leading-edge genes identified in the dairy calf and beef cattle populations respectively. Six leading-edge genes (ADIPOQ, HTR2A, MIF, PDE6G, PRDX3 and SNCA) were associated with BRD in both dairy and beef cattle. Network analysis identified glucose as the most influential upstream regulator in dairy cattle, whereas in beef cattle, TNF was the most influential upstream regulator. The genes, gene sets and upstream regulators associated with BRD have common functions associated with immunity, inflammation and pulmonary disease and provide insights into the mechanisms that are critical to BRD susceptibility in cattle.

Characterization of copy number variants in a large multibreed population of beef and dairy cattle using high-density single nucleotide polymorphism genotype data.

Copy number variants (CNVs) are a form of genomic variation that changes the structure of the genome through deletion or duplication of stretches of DNA. The objective of the present study was to characterize CNVs in a large multibreed population of beef and dairy bulls. The CNVs were called on the autosomes of 5,551 cattle from 22 different beef and dairy breeds, using 2 freely available software suites, QuantiSNP and PennCNV. All CNVs were classified into either deletions or duplications. The median concordance between PennCNV and QuantiSNP, per animal, was 18.5% for deletions and 0% for duplications. The low concordance rate between PennCNV and QuantiSNP indicated that neither algorithm, by itself, could identify all CNVs in the population. In total, PennCNV and QuantiSNP collectively identified 747,129 deletions and 432,523 duplications; 80.2% of all duplications and 69.1% of all deletions were present only once in the population. Only 0.154% of all CNVs identified were present in more than 50 animals in the population. The distribution of the percentage of the autosomes that were composed of deletions, per animal, was positively skewed, as was the distribution for the percentage of the autosomes that were composed of duplications, per animal. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of deletions were 0.019%, 0.037%, and 0.201%, respectively. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of duplications were 0.013%, 0.028%, and 0.076%, respectively. The distributions of the number of deletions and duplications per animal were both positively skewed. The interquartile range for the number of deletions per animal in the population was between 16 and 117, whereas for duplications it was between 8 and 23. Per animal, there tended to be twice as many deletions as duplications. The distribution of the length of deletions was positively skewed, as was the distribution of the length of duplications. The interquartile range for the length of deletions in the population was between 25 and 101 kb, and for duplications the interquartile range was between 46 and 235 kb. Per animal, duplications tended to be twice as long as deletions. This study provides a description of the characteristics and distribution of CNVs in a large multibreed population of beef and dairy cattle.

Upgrading breeding value estimation in beef cattle

This paper gives a summary of the possibility for applying genomic information for breeding value estimation in beef cattle breeding. This process is called genomic prediction and is now widely used in dairy cattle globally as well as in some beef and sheep populations. The advantage of genomic prediction is a more accurate estimate of the genetic merit of an individual at a young age thereby facilitating greater annual genetic gain, predominantly through shorter generation intervals. Genomic predictions are more advantageous for sex-linked (e.g., milk yield), low heritability (e.g., fertility) and difficult-to-measure (e.g., feed intake) traits. The larger the reference population, on average, the more accurate the genomic predictions; additionally, the closer genetically the reference population is to the candidate population, the greater the accuracy of genomic predictions. Research is continuing on strategies to generate accurate genomic predictions using a reference population consisting of multiple breeds (and crossbred). Retrospective analysis of real-life data where genomic predictions have been operation for several years clearly shows a benefit of this technology.

A comprehensive comparison between single- and two-step GBLUP methods in a simulated beef cattle population

The statistical methods used in the genetic evaluations are a key component of the process and can be best compared by using simulated data. The latter is especially true in grazing beef cattle production systems, where the number of proven bulls with highly reliable estimated breeding values is limited to allow for a trustworthy validation of genomic predictions. Therefore, we simulated data for 4980 beef cattle aiming to compare single-step genomic best linear unbiased prediction (ssGBLUP), which simultaneously incorporates pedigree, phenotypic, and genomic data into genomic evaluations, and two-step GBLUP (tsGBLUP) procedures and genomic estimated breeding values (GEBVs) blending methods. The greatest increases in GEBV accuracies compared with the parents’ average estimated breeding values (EBVPA) were 0.364 and 0.341 for ssGBLUP and tsGBLUP, respectively. Direct genomic value and GEBV accuracies when using ssGBLUP and tsGBLUP procedures were similar, except for the GEBV accuracies using Hayes’ blending method in tsGBLUP. There was no significant or slight bias in genomic predictions from ssGBLUP or tsGBLUP (using VanRaden’s blending method), indicating that these predictions are on the same scale compared with the true breeding values. Overall, genetic evaluations including genomic information resulted in gains in accuracy >100% compared with the EBVPA. In addition, there were no significant differences between the selected animals (10% males and 50% females) by using ssGBLUP or tsGBLUP.

Ultrasonographic measurements in first trimester concepti identify predictors of birth weight and postnatal development in cattle.

The placenta is a major driver of prenatal growth and involved in programming of postnatal performance. We therefore determined placental and embryo-fetal ultrasonographic parameters in early pregnancy and their relationships with birth weight and postnatal weights in a Bos indicus-Bos taurus composite beef cattle population. Pregnancies were generated in 2-yr-old Droughtmaster heifers by artificial insemination after estrus synchronization in 2 consecutive years (2009, n = 36 and 2010, n = 57), with a subset of 2010 heifers used again as lactating 3-yr-old cows in 2011 (n = 24). Each cohort was managed as 1 contemporary group for measurements of Corpus luteum diameter, amnion length and width, placentome width and thickness, and embryo-fetal crown-rump length, at 7 and 8 wk of gestation. This was followed by recordings of birth weight, branding weight at 5 to 6 mo of age and weaning weight 2 mo later. At a significance threshold of P < 0.05, placentome thickness at week 7 was negatively correlated with weights at birth (r = -0.23), branding (r = -0.25), and weaning (r = -0.35), whereas placentome width at week 7 (r = 0.24) and thickness at week 8 (r = 0.29) were positively correlated with birth weight. Thicker placentomes in males at week 7 (7%) difference mirrored sex differences in weights at birth (7%), branding (10%), and weaning (6%). The sex difference trend for birth weight was not consistent across sire-year combinations, ranging from -3.2 to +4.7 kg (birth weight of males - females per sire). These results support the hypothesis that placental parameters at the transition from embryo to fetal stage are major predictors of fetal and postnatal growth, albeit with significant environmentally induced plasticity, in stabilized B. indicus-B. taurus composite populations, and suggest that elements of B. indicus-B. taurus reciprocal differences in birth weight persist in composite populations.

DEMANDA DE SORGO GRANO EN MÉXICO CON LA TÉCNICA DE RETRASOS DISTRIBUIDOS

&lt;p&gt;Sorghum (&lt;em&gt;Sorghum vulgare&lt;/em&gt; Pers) is one of the most important grains for the Mexican livestock industry, it is the second largest basic grain and is considered the main ingredient in the production of balanced nourishment. In order to estimate the determining factors of grain sorghum demand in Mexico, a multi-variable linear econometric model for the 1995-2014 period was estimated using the distributed delays technique. The results displayed that sorghum demand responds inelastically to changes in price, with price elasticities of 0.35 and 0.42 in the short and long term, while an increase in the price of maize causes the demand for sorghum to increase by 0.39 and 0.47, which makes it a substitute and inelastic good for grain consumption. Unit percentage increases in beef cattle and milk population would increase sorghum demand by 0.60 and 0.51. The adjustment rate between the current consumption and the desired grain consumption was 0.85, it is a quick adjustment, so the market does not overreact to changes in prices, and it is stable and controlled in the short term. Is possible to conclude that demand for sorghum in Mexico is more influenced by the increase of beef and milk cattle as well as poultry.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Synergistic effects of complementary production systems help reduce livestock environmental burdens

Global demand for food and energy pushes the agrifood sector to increase production which, in turn, increases pressures on ecosystems. An integrated approach is essential to cope with agro-environmental challenges and ensure sustainable agricultural productions. The current study follows the principles of industrial ecology and explores potential greenhouse gas mitigation practices by considering multiple agricultural sectors as complementary industries. The focus of the study was the production of meat, considering the dairy and beef industries as complementary sectors. They were studied as an integrated system in order to evaluate how these two meat production systems can contribute at reducing environmental impacts and make agricultural productions more sustainable. We use Canada as an example because it has two very different meat production systems: Western Canada raise beef cattle quasi-exclusively and has relatively few dairy cattle; in contrast, Eastern Canada, has a balanced production of beef and dairy cattle (about 50/50). This situation provides an ideal opportunity to achieve the objective of this study. Calculations were based on the Unified Livestock Industry and Crop Emissions Estimation System (ULICEES) calculator. Our results show synergy between integrated beef and dairy systems in Eastern Canada resulted in a 22% lower carbon footprint (CF) of meat compared to the scenario where meat was only produced by the beef industry. A scenario where western Canada would have equal size dairy and beef populations indicated that western meat CFs would be 31% lower than its current levels. This study illustrates how complementary multi-product agricultural production systems acting in synergy can increase production efficiencies compared to specialized single-product systems. It shows that such production strategy represents one of the great opportunities to reduce the environmental impacts from agricultural production systems.

The Effort of Beef Needs Supplying for Coming Years in Indonesia

The increase in beef production is constrained by the slow growth of beef cattle population which is caused by the cattle breeding business that is considered less commercially profitable. The supplying of beef needs in a critical and effective manner is always increasing each year, so the price of beef is fluctuate. The various priority concept of the government's main program for the development of beef cattle is always done in every region in Indonesia. But the production of beef is still less and the government have to import the beef to fulfill the beef production. Therefore, this issues need necessary operational steps to provide more open space for some factors and leverage points in the supplying of beef needs. The purpose of this review is to examine the efforts to supply beef needs for the future in Indonesia critically. The high price of beef is not a mistake of the government. Basically, the government has tried to make the beef cattle population increased, to fulfill the consumer needs and the prices of beef is affordable for the customer. To cope with the higher beef prices, the government is make a policy of developing small, medium-sized, and big beef cattle breeding industries through seed cattle spreads on plantations of oil palm, rubber and cultivable fields for the development of beef cattle population. It is expected that in the coming year, beef cattle business can be oriented to agribusiness bussiness so that farmer's welfare will increase and can support Indonesia as the world food granary.

Study of Beef Availability Potential in Yogyakarta Special Province (DIY) through Multi Criteria Analysis (MCA) Model by Spatial Geographic Information System

The increasing human population and income per capita in Indonesia have many impacts to the demand of food, not only staple food but also the secondary food too, including meat and beef demand. Based on data from Central Statistics Bureau of 1995–2016, beef demand in Indonesia has been increasing. This condition must be anticipated by preparing the supply, especially the availability of beef in Daerah Istimewa Yogyakarta province. In Yogyakarta city, one of the regencies of DIY, the demand rate grows by 3.2%/year, higher than the supply growth rate by 2.08 %/year. This gap needs to be thought through the case of scarcity of beef on the market. This study aimed to identify the potential of supply in five parameters i.e.: beef population, the availability of semen for artificial insemination (IB), the availability of livestock feed plants (HMT), the number of cows that enter DIY, and the number of cows that exit from DIY. A model Spatial Geographic Information Systems (SGIS) has been used in this study. The study revealed the most potential area for the development of beef agribusiness, based on the availability side, was Gunung Kidul Regency, and the less potential was Yogyakarta municipality.

36 Incorporation of Putative Functional Variants in the Ncapg, ARRDC3, PLAG1 and ERGIC1 Genes Improves Accuracies of Genomic Predictions for Growth Traits in Beef Cattle.

In beef cattle, body weight is an important trait and optimizing size at various ages is of key economic interest. In our previous study, we identified four large-effect pleiotropic QTLs located on BTA6, 7, 14 and 20 associated with body weights in several beef breeds. Some 96 new functional variants of candidate genes within these and some other QTL regions were selected from the dbSNP and assayed into the new versions of GeneSeek Genomic Profilers (GGP-LD, GGP-UHD and GGP-50K). Some 5,964 Simmental and 2,871 Red Angus animals were genotyped with one of these assays. Some 200 animals of each population were used as the test and the rest for training purposes. Only 9,439 autosomal markers in common between these assays were used in the analyses. We compared accuracies of genomic predictions for birth, weaning and yearling weights fitting 9K, 9K plus 96 functional variants or only 96 functional variants in BayesC0 model using GenSel software. The correlations between estimated molecular breeding values (MBV) and adjusted phenotypes divided by the square root of the trait heritability were used as a measurement of accuracy, which are shown in Table 1. The accuracies of MBV were equal or higher in the model including additional 96 functional variants. Interestingly, genomic predictions were more accurate for yearling weight using only 96 functional variants in both Simmental and Red Angus populations. These functional variants accounted for significant amount of additive genetic variances of body weights in these populations. Some functional variants including rs109570900 encoding p.Ile442Met in NCAPG, rs109901274 encoding p.Tyr182Cys in ARRDC3, rs136369910 encoding g.25019900A>G in PLAG1 and rs43350563 encoding c.322G>A in ERGIC1 were among significantly associated markers with remarkable impact on body weights. Knowledge of such functional variants improves the accuracies of genomic predictions and would create new opportunities for the selection of animals with appropriate body weights for harvest or maternal purposes and could decrease dystocia in beef cattle population. Table 1. The accuracies of genomic predictions for birth, weaning and yearling weights using different marker sets Table 1. The accuracies of genomic predictions for birth, weaning and yearling weights using different marker sets

Developing Sustainable Livestock Production by Feed Adequacy Map: A Case Study in Pasuruan, Indonesia.

Feed is a main factor of sustainable livestock population, where the availability of suitable land for grass growth is urgent. Modern agriculture has dramatically reduced the diversity of forages due to the massive monoculture. This study was aimed to obtain data on the size of the existing land, distribution, potential feed production, and to obtain the carrying capacity based on feed adequacy map. The research was conducted on 6 dairy and beef cattle farms in Pasuruan Regency (7°38′S,112°54′E), East Java Province, Indonesia: Tutur, Puspo, Lumbang, Lekok, Grati, and Purwodadi. Population and distribution are represented spatially through thematic maps. The mapping using the Indonesia land-base map (Rupa Bumi Indonesia-RBI) scale 1: 25,000, GPS handsets, and surveyors. Nguling had the highest beef cattle population (15,519 AU), while Tutur had the highest dairy cattle population (22,033 AU). Farmers were able to provide feed in the form of food-crop waste. Bangil had the highest carrying capacity of feed and safe criteria followed by Pohjentrek, while Lekok, Tutur, Puspo, Lumbang, Purwosari, Nguling, and Prigen subdistricts had very critical criteria. Based on the overall feed index, Pasuruan had a vulnerable criteria. The land carrying capacity status between land availability (SL) and land requirement (DL) was deficit. Less than 15% of land had low water carrying capacity. By carrying capacity index of crops waste (CCICW), the carrying capacity of food crops was high. The land carrying capacity status was deficit.

Aplikasi Fuzzy Inference System untuk Menentukan Lokasi Pengembangan Sentra Peternakan Rakyat (SPR) Sapi Potong di Kabupaten Jember

The development of community farming center (SPR) of cattle beef to consolidate the potential of people's cattle beef to be managed optimally to increase the production and welfare of farmers in realizing national beef self-sufficiency. Jember Regency as one of the centers of cattle beef in East Java Province has a policy to develop SPR in a number of sub-districts but still faces a number of problems that is determining which district will be chosen as SPR location. This research aims to design the model of determining SPR cattle beef location using fuzzy inference system technique. A number of key criteria in location determination are explored then designed into decision support models using the Matlab fuzzy tool box. The results showed that there are three key criteria for determining the location of SPR development of cattle beef, namely 1) potential Feed from plants; 2) population of cattle beef; and the availability of facilities and infrastructure. Decision support model is built with fuzzy inference system technique using Triangular Fuzzy Number (TFN) representation model and MAMDANI inference method. The number of rules built as many as seven rules with the operator or and and and. Model simulation results show that the locations that are categorized as Very Suitable for SPR development of cattle beef are Silo, Sumberjambe, and Ledokombo Subdistricts, While sub District Gumukmas, Sumberbaru, Puger, Wuluhan, Kencong, Bangsalsari, Mumbulsari, and Jenggawah, fall into the Suitable category.

ANALISIS PENDAPATAN USAHA PETERNAK SAPI POTONG DI KECAMATAN WEDA SELATAN KABUPATEN HALMAHERA TENGAH

ABSTRACT INCOME ANALYSIS OF SMALLHOLDER FARMERS FOR BEEF CATTLE IN SOUTH WEDA DISTRICT OF CENTRAL HALMAHERA REGENCY. Objective of this study was to evaluate the income and factors affecting income of smallholder farmer of beef cattle on the high land and low land at South Weda district of Central Halmahera regency. Samples of these smallholder farmers were defined by purposive method based on high population of beef cattle. Quantitative data were analyzed by multiple regression model. Results showed that the average production costs were IDR 37,310,606.00 on high land location and IDR 25,597,372.00 on low land location. The average output of smallholder farmers from beef cattle were IDR 56,397,059.00 on high land location and IDR 38,475,000.00 on low land location. Therefore, their incomes were IDR 19,086,453.00/year on high land location and IDR 12,877,628.00/year on low land location. Result of multiple regression analysis showed that beef cattle stock variable (animal value at end of year) affected on the smallholder farmer income of beef cattle, while education and age of smallholders did not affect on their income at South Weda district of Central Halmahera regency. Key words: Smallholder farmer income, South Weda district Central Halmahera regency.

Beef Cattle Business in Dry Land Area Parangloe District Gowa

The study was conducted in the village Payangkalang Parangloe District of Gowa in South Sulawesi in 2017, with the field survey method Substance himself to Bali beef cattle breeders, through interviews and questionnaires to 18 farmers, by the way (sample random sampling). Respondents beef cattle breeders, classified into 2 (two) business model with a scale of 2 adult males and 3 females scale adult stem, this data will be analyzed using economic analysis of income B/C. Based on the information that the beef cattle population of Bali is quite a many, so that the criterion for consideration for the study area. Beside that all cattle breeders Bali is already a member of a group of farmers. The results showed that net profit in the maintenance of Bali beef cattle female parent of $13.381.250/year with B/C ratio of 1.2 and a gain on the maintenance of male cattle Bali for $ 3.881.250 year, with B/C ratio of 1.1. To maintain a profitable cattle faremr cows, while the majority of beef cattle Bali parent can still be maintained as an investment for the procreation of children next year.

Fast genomic prediction of breeding values using parallel Markov chain Monte Carlo with convergence diagnosis

BackgroundRunning multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable burn-in period, for which all simulated data are discarded. In practice, this burn-in period is set arbitrarily and often leads to the performance of far more iterations than required. In addition, the accuracy of genomic predictions does not improve after the MCMC reaches equilibrium.ResultsAutomatic tuning of the burn-in length for running multiple-chain MCMC was proposed in the context of genomic predictions using BayesA and BayesCπ models. The performance of parallel computing versus sequential computing and tunable burn-in MCMC versus fixed burn-in MCMC was assessed using simulation data sets as well by applying these methods to genomic predictions of a Chinese Simmental beef cattle population. The results showed that tunable burn-in parallel MCMC had greater speedups than fixed burn-in parallel MCMC, and both had greater speedups relative to sequential (single-chain) MCMC. Nevertheless, genomic estimated breeding values (GEBVs) and genomic prediction accuracies were highly comparable between the various computing approaches. When applied to the genomic predictions of four quantitative traits in a Chinese Simmental population of 1217 beef cattle genotyped by an Illumina Bovine 770 K SNP BeadChip, tunable burn-in multiple-chain BayesCπ (TBM-BayesCπ) outperformed tunable burn-in multiple-chain BayesCπ (TBM-BayesA) and Genomic Best Linear Unbiased Prediction (GBLUP) in terms of the prediction accuracy, although the differences were not necessarily caused by computational factors and could have been intrinsic to the statistical models per se.ConclusionsAutomatically tunable burn-in multiple-chain MCMC provides an accurate and cost-effective tool for high-performance computing of Bayesian genomic prediction models, and this algorithm is generally applicable to high-performance computing of any complex Bayesian statistical model.