Multiple-trait genomic evaluation for milk yield and milk quality traits using genomic and phenotypic data in buffalo in Brazil

The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

Age of No-Till System and Nitrogen Management on Common Bean Nutrition and Yield

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

Strength gain through eccentric isotonic training without changes in clinical signs or blood markers

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

Dry matter yield and tillering of brachiarias sown at depths intercropped with corn

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

Heavy metals and yield of cowpea cultivated under composted tannery sludge amendment

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

Influence of rootstocks and pruning times on yield and on nutrient content and extraction in 'Niagara Rosada' grapevine

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

Effect of potassium sources and rates on arabica coffee yield, nutrition, and macronutrient export

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

Growth and yield of anthurium in response to gibberellic acid

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

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Effects of feeding corn silage inoculated with microbial additives on the ruminal fermentation, microbial protein yield, and growth performance of lambs

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

ASIAN SOYBEAN RUST INTEGRATED MANAGEMENT POTENTIAL: DISEASE SEVERITY, PLANT DEVELOPMENT AND YIELD COMPONENTS, CULTIVAR MG/BR-46 (CONQUISTA)

Soybean rust caused by Phakopsora pachyrhizi Sydow & P. Sydow is one of the major diseases of the soybean crop. The aim of this study was to evaluate the effects of sowing dates, plant populations and reduced doses of fungicides on soybean rust severity and its effects on plant development and yield, cultivar MG/BR46 (Conquista). Field experiments were conducted in the 2009/2010 and 2010/2011 harvests, under natural rust infestation of soybean rust. As from the appearance of the first disease symptoms, also began the fungicide spraying and the disease severity assessments. To understand the nature and extent of the effects of different treatments, a multivariate analysis of factors was applied. For the majority of the agronomic characters and factors, one-third to two-thirds of their variability can be explained by changes in plant populations or by differences in the fungicide treatments, and the remainder, was explained by sowing date variations. The fungicide treatments and sowing dates are determinants in disease severity and its interference on crop productivity. The characters of plant growth are more dependent on plant population variations. Treatments with azoxystrobina + ciproconazol promoted smaller disease severities, reflecting in productivity increase. The plant populations can be reduced up to 160.000 plants ha(-1) without losses in the disease control and the soybean yield. In general, the earliest sowings provided increase in the plant development, although the rust control was less efficient.

Occurrence of heat waves in Triangulo Mineiro and Alto Paranaiba and their effect on milk yield and feed intake in cattle

The aim of this study was to estimate milk production and food consumption during the occurrence of heat waves in the Triangulo Mineiro and Alto Paranaiba, MG by means of bioclimatic zoning based on the Temperature and Humidity Index (THI). Therefore a history of heat wave occurrence between the years 2000-2010 was compiled. The decline in milk production (DMP) and reduced food consumption (RFC) were simulated in cities where periods of heat waves were identified. Frutal and Ituiutaba had the highest rate of heat wave occurrence per year. The DMP and RFC showed bioclimatic differences between the cities of Uberaba, Ituiutaba and Frutal. The cities with the best bioclimatic conditions were Sacramento and Patrocinio, as they presented a THI classified outside of the emergency range, with a night THI of below 76 and without heat waves. Therefore, the occurrence of heat waves can impair food intake and decrease milk production, thereby most effectively demonstrating the effects of thermal stress on dairy cows in the Triangulo Mineiro and Alto Paranaiba, MG region.

Physical-chemical characterization and wet milling yield of four maize hybrids

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