The key elements for genetic response in Finnish dairy cattle breeding

Selostus: Perinnöllinen edistyminen suomalaisessa lypsykarjan jalostusohjelmassa

Evaluation of the effect of the seed extract of Moringa oleifera Lam over the efficiency of organic filters in wastewater treatment of dairy cattle breeding

This study aimed to evaluate the effect of Moringa oleifera Lam extract on the removal of total solids (TS), total suspended solids (TSS) and chemical oxygen demand (COD), in different filter media for treating wastewater of dairy cattle breeding (DCW). The moringa seed extract was obtained by grinding 50 g of seeds in one liter of distilled water and, after passing the solution through a quantitative paper filter of 25 microns, 60 mL of the extract were added to wastewater from cattle breeding before the filtration process in organic filters made of thin coal, bamboo leaves, eucalyptus leaves, gliricidia branches and sawdust. This was followed by the completely randomized experimental design, adopting a factorial of 5 x 2. Aliquots of filtered effluent were collected and the total solids (TS) concentrations, total suspended solids (TSS) and chemical oxygen demand (COD) were determined. It was found that the increase in the efficiency of removal of COD and total solids can be attributed to the coagulating power of the moringa seed extract, wherein the filter medium with bamboo leaves presented the best performance, showing potential for use as alternative filter material in the primary treatment of DCW.

Corn production for silage intercropped with forage in the farming-cattle breeding integration

Corn cropping for silage, due to the plant material exportation, intercropping with forage provides greater ground cover and straw formation for the Direct Planting System (DPS) continuity. The objective of this study was to evaluate corn production for silage in DPS intercropped with four forages (Urochloa brizantha cv. Marandu, U. ruziziensis cv. Ruziziensis, Panicum maximum cv. Tanzânia and P. maximum cv. Áries). We applied three sowing methods (in row together with corn fertilizer; by no-till sowing simultaneously to corn sowing and at V4 corn stage) and corn without intercropping. The experiment was conducted in autumn/ winter of 2010, in Selvíria - MS, in a randomized block design in factorial arrangement (4 x 3 + 1) and 4 replications. For corn, we evaluated plant height, basal stem diameter, initial and final stand and silage production and for forage dry matter production. Morphological characteristics and corn yield were not affected by intercropping when compared to sole corn crop. Forage dry matter production sown in corn row with fertilizer is a highlight, which in addition to providing greater productivity, harnesses the operation during sowing.

USE OF PROGENY TESTING IN BEEF-CATTLE - PREDICTION OF GENETIC GAIN IN A NELORE CATTLE-BREEDING PROGRAM

Genetic gains predicted for selection, based on both individual performance and progeny testing, were compared to provide information to be used in implementation of progeny testing for a Nelore cattle breeding program. The prediction of genetic gain based on progeny testing was obtained from a formula, derived from methodology of Young and weller (J. Genetics 57: 329-338, 1960) for two-stage selection, which allows prediction of genetic gain per generation when the individuals under test have been pre-selected on the basis of their own performance. The application of this formula also allowed determination of the number of progeny per tested bull needed to maximize genetic gain, when the total number of tested progeny is limited.

Use of progeny testing in beef cattle: Prediction of genetic gain in a Nelore Cattle Breeding Program

Genetic gains predicted for selection, based on both individual performance and progeny testing, were compared to provide information to be used in implementation of progeny testing for a Nelore cattle breeding program. The prediction of genetic gain based on progeny testing was obtained from a formula, derived from methodology of Young and Weiler (J. Genetics 57: 329-338, 1960) for two-stage selection, which allows prediction of genetic gain per generation when the individuals under test have been pre-selected on the basis of their own performance. The application of this formula also allowed determination of the number of progeny per tested bull needed to maximize genetic gain, when the total number of tested progeny is limited.

Genomic selection and assisted reproduction technologies to foster cattle breeding

Genomics has been propagated as a paradigm shifting innovation in livestock during the last decade. The possibility of predicting breeding values using genomic information has revolutionized the dairy cattle industry and is now being implemented in beef cattle. In this paper we discuss how genomics is changing cattle breeding through genomic selection, and how this change is creating new ways to articulate assisted reproduction technologies with animal breeding. We also debate that the scientific community is still starting the long journey to reveal the functional aspects of the cattle genome, and that knowledge in this field is the frontier to a whole new venue for the development of novel applications in the livestock sector.

Corn production for silage intercropped with forage in the farming-cattle breeding integration

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

...Report on demonstration work carried out in the Western circle together with reports on the seed demonstration and cattle-breeding farms of that circle for the year...

Title varies slightly.

Comparison of genetic gains per year for carcass traits among breeding programs in the Japanese Brown and the Japanese Black cattle

The breeding program for beef cattle in Japan has changed dramatically over 4 decades. Visual judging was done initially, but progeny testing in test stations began in 1968. In the 1980s, the genetic evaluation program using field records, so-called on-farm progeny testing, was first adopted in Oita, Hyogo, and Kumamoto prefectures. In this study, genetic trends for carcass traits in these 3 Wagyu populations were estimated, and genetic gains per year were compared among the 3 different beef cattle breeding programs. The field carcass records used were collected between 1988 and 2003. The traits analyzed were carcass weight, LM area, rib thickness, s.c. fat thickness, and beef marbling standard number. The average breeding values of reproducing dams born the same year were used to estimate the genetic trends for the carcass traits. For comparison of the 3 breeding programs, birth years of the dams were divided into 3 periods reflecting each program. Positive genetic trends for beef marbling standard number were clearly shown in all populations. The genetic gains per year for all carcass traits were significantly enhanced by adopting the on-farm progeny testing program. These results indicate that the on-farm progeny testing program with BLUP is a very powerful approach for genetic improvement of carcass traits in Japanese Wagyu beef cattle.

Breeding experiments with Holstein-Friesian cattle : results of 35 years' research at Beltsville, Md. /

Caption title.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.