Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows

Milk production in tropical environments requires the use of crossbreeding systems including breeds well adapted to harsh conditions, but with lower productivities when compared to specialized breeds. Besides the genetic improvement for milk production, lactation lengths also need to be studied for most of these breeds. Accordingly, genetic parameters were estimated for 305-day cumulative milk yield (MY305), test-day milk yield (TDMY), and lactation length (LL) using information from the first lactations of 2816 Guzerat cows selected for milk production in 28 herds in Brazil. Contemporary groups were defined as herd, year and season of the test for TDMY, and as herd, year and season of calving for MY305 and LL. Variance components were estimated with the restricted maximum likelihood method under a multi-trait animal model. Heritabilities estimated for TDMY ranged from 0.16 to 0.24, and were 0.24 and 0.12 for MY305 and LL, respectively. Genetic correlations were high and positive, ranging from 0.51 to 0.99 among TDMY records, from 0.81 to 0.98 between each TDMY and MY305, and from 0.71 to 0.94 between each TDMY and LL. Genetic parameters obtained in this study indicated the possibility of using test-day records for the prediction of breeding values for milk yield in this population of the Guzerat breed. The use of TDMY as selection criteria would result in indirect gains in MY305 and LL. However, the highest response to selection for MY305 would be obtained by direct selection for this trait. © 2012 Elsevier B.V.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Sorghum grain yield, forage biomass production and revenue as affected by intercropping time

Sorghum is an excellent alternative to other grains in poor soil where corn does not develop very well, as well as in regions with warm and dry winters. Intercropping sorghum [Sorghum bicolor (L.) Moench] with forage crops, such as palisade grass [Brachiaria brizantha (Hochst. ex A. Rich) Stapf] or guinea grass (Panicum maximum Jacq.), provides large amounts of biomass for use as straw in no-tillage systems or as pasture. However, it is important to determine the appropriate time at which these forage crops have to be sown into sorghum systems to avoid reductions in both sorghum and forage production and to maximize the revenue of the cropping system. This study, conducted for three growing seasons at Botucatu in the State of São Paulo in Brazil, evaluated how nutrient concentration, yield components, sorghum grain yield, revenue, and forage crop dry matter production were affected by the timing of forage intercropping. The experimental design was a randomized complete block design. Intercropping systems were not found to cause reductions in the nutrient concentration in sorghum plants. The number of panicles per unit area of sorghum alone (133,600), intercropped sorghum and palisade grass (133,300) and intercropped sorghum and guinea grass (134,300) corresponded to sorghum grain yields of 5439, 5436 and 5566kgha-1, respectively. However, the number of panicles per unit area of intercropped sorghum and palisade grass (144,700) and intercropped sorghum and guinea grass (145,000) with topdressing of fertilizers for the sorghum resulted in the highest sorghum grain yields (6238 and 6127kgha-1 for intercropping with palisade grass and guinea grass, respectively). Forage production (8112, 10,972 and 13,193Mg ha-1 for the first, second and third cuts, respectively) was highest when sorghum and guinea grass were intercropped. The timing of intercropping is an important factor in sorghum grain yield and forage production. Palisade grass or guinea grass must be intercropped with sorghum with topdressing fertilization to achieve the highest sorghum grain yield, but this significantly reduces the forage production. Intercropping sorghum with guinea grass sown simultaneously yielded the highest revenue per ha (€ 1074.4), which was 2.4 times greater than the revenue achieved by sowing sorghum only. © 2013 Elsevier B.V.

Genetic Parameter Estimates for Milk Yield and Lactation Length in Buffalo

The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.

Estimates of genetic parameters for total milk yield over multiple ages in Brazilian Murrah buffaloes using different models

The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

Genetic association between milk yield, stayability, and mastitis in Holstein cows under tropical conditions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

PRODUCTIVITY OF CANE SUGAR: LINEAR AND SPATIAL VARIABILITY BETWEEN COMPONENTS AND TECHNOLOGICAL PRODUCTION

Nowadays, the culture of the sugarcane plays an important role regarding the Brazilian reality, especially in the aspect related to the alternative energy sources. In 2009, the municipality of Suzanapolis (SP), in the Brazilian Cerrado, an experiment was conducted with the culture of the sugarcane in a Red eutrophic, with the aim of selecting, using Pearson correlation coefficients, modeling, simple, linear and multiple regressions and spatial correlation, and also the best technological and productive components, to explain the variability of the productivity of the sugarcane. The geostatistical grid was installed in order to collect the data, with 120 sampling points, in an area of 14.53 ha. For the simple linear regressions, the plants population is the component of production that presents the best quadratic correlation with the productivity of the sugarcane, given by: PRO = -0.553**xPOP(2)+16.14*xPOP-15.77. However, for multiple linear regressions, the equation PRO = -21.11+4.92xPOP**+0.76xPUR** is the one that best presents in order to estimate that productivity. Spatially, the best correlation with yield of the sugarcane is also determined by the component of the production population of plants.

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

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

Leaf gas exchange and yield of three upland rice cultivars

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

Soybean yield in relation to distance from the Itaipu reservoir

Crops close to small water bodies may exhibit changes in yield if the water mass causes significant changes in the microclimate of areas near the reservoir shoreline. The scientific literature describes this effect as occurring gradually, with higher intensity in the sites near the shoreline and decreasing intensity with distance from the reservoir. Experiments with two soybean cultivars were conducted during four crop seasons to evaluate soybean yield in relation to distance from the Itaipu reservoir and determine the effect of air temperature and water availability on soybean crop yield. Fifteen experimental sites were distributed in three transects perpendicular to the Itaipu reservoir, covering an area at approximately 10 km from the shoreline. The yield gradient between the site closest to the reservoir and the sites farther away in each transect did not show a consistent trend, but varied as a function of distance, crop season, and cultivar. This finding indicates that the Itaipu reservoir does not affect the yield of soybean plants grown within approximately 10 km from the shoreline. In addition, the variation in yield among the experimental sites was not attributed to thermal conditions because the temperature was similar within transects. However, the crop water availability was responsible for higher differences in yield among the neighboring experimental sites related to water stress caused by spatial variability in rainfall, especially during the soybean reproductive period in January and February.

Seleção de genótipos de soja portadores ou não do gene RR por meio de análise multivariada e desempenho agronômico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desempenho agronômico e produtivo de cultivares de soja em diferentes ciclos e safras

With the objective of gathering technical data about soybean cultivars performance in Botucatu, state of São Paulo, Brazil, an experiment was conducted to evaluate seventeen genotypes. The experiment was conducted during the Summer seasons of 2002/03, 2003/04, and 2004/05. The experiment was set in the field according to a complete block design with four repetitions. The soybean cultivars were ‘Embrapa 48’, ‘BRS 132’. ‘BRS 183’, ‘BRS 212’, ‘IAC 22’, and ‘IAC 23’ (early cycled varieties), ‘BRS 133’, ‘BRS 154’, ‘BRS 156’, ‘BRS 184’, ‘BRS 214’, ‘IAC 18’, and ‘IAC 24’ ( semi early varieties), and ‘BRS 134’, ‘BRS 215’, ‘IAC 8.2’, and ‘IAC 19’ (medium cycled varieties ). All the varieties, during the three cropping years, showed adequate plant height and first pod height of insertion for mechanical harvest. Among the production components, mass of 100 grains showed the highest variability. Cultivar ‘BRS 154’ (medium cycle) showed the highest variation in mass of 100 grains and was also the highest yielding variety in the cropping year of 2004/05. The majority of the cultivars yielded above 3,000 kg ha -1 during the cropping years of 2002/03 and 2004/05. The best yielding performance during the three cropping years were displayed by cultivars ‘IAC 22’ (early cycle), ‘BRS 133’ and ‘BRS 156’ ( both semi early cycled varieties).

Consórcio de milho e Urochloa ruziziensis e inoculação com Azospirillum brasilense e seu efeito residual associado à adubação nitrogenada em feijoeiro de inverno

Pós-graduação em Agronomia - FEIS