Milk yield persistency in Brazilian Gyr cattle based on a random regression model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

Drying temperature effects in peppermint essential oil content and composition

Studies were conducted to show the effect of different temperatures in the drying process on the amount and quality of essential oils of peppermint (Mentha piperita L.) The leaves were harvested in the Demeter Farmer, Botucatu, SP, Brazil in december, 1997. The leaves were dried at 40°C, 60°C and 80°C, until establishment of the weights. The essential oil was extracted by destilation in Clevenger apparatus and analysed by GC-MS. Higher drying temperature sharply decreased the essential oil content (% v/w) from 1.0% (40°C) to 0.14% (60°C) and 0.12% (80°C). Higher drying temperatures also affected the composition, decreasing the contents of 1,8 cineol and citronelal until 80°C, and increasing the contents of menthol and neomenthol until 60°C.

Test-day model for milk yield of dairy buffaloes in colombia

The test-day model is the preferred method for genetic evaluations in dairy cattle. For this study, 28372 test-day records of 1220 lactations from 1997 to 2009 were used. The (co)variance components for milk in test-day were estimated using a Uni and multiple-traits repeated animal model with the Restricted Maximum Likelihood method (REML). The Contemporary Group (herd, year, and season of parity) and the age of parity (linear and quadratic) fixed effects, and the additive genetic, permanent environmental, and residual random effects were included in the model. The heritabilities ranged between 0.06 and 0.45 during lactation. The genetic correlations were greater than 0.93. In conclusion, the test-day model is appropriate for the genetic evaluation of dairy buffaloes in Colombia.

Yield and phytochemical characterization of essential oil from Ocimum selloi B. obtained by hydrodistillation and supercritical fluid extraction

The yield and chemical composition of essential oils from leaves of Ocimum selloi B. submitted to organic and mineral fertilization, obtained by hydrodistillation and supercritical fluid extraction (SFE) were compared. Essential oil was extracted in a Clevenger-type apparatus for 2 h 30 min and analyzed by GC-MS (Shimadzu, QP 5050-DB-5 capillary column - 30 m × 0.25 mm × 0.25 μm). Carrier gas was helium (1.7 ml/min); split ratio: 1:30. Temperature program: 50°C, rising to 180°C at 5°C/min, 180°C, rising to 280°C at 10°C/min. Injector temperature: 240°C and detector temperature: 230°C. Identifications of chemical compounds were made by matching their mass spectra and Kovat's indices (IK) values with known compounds reported in the literature. An Applied Separations-apparatus (Speed SFE, model 7071, Allentown, PA, EUA) was used for SFE extractions. They were conducted at pressure 200 bar and temperature 30°C (20 min in static mode and 40 min in dynamic mode). The supercritical CO2 flow rate was (6.8±0.7)×10-5 kg-CO2/s. The essential oil collected was immersed in ethylene glycol bath (5°C). The yield of essential oils obtained by SFE was larger than hydrodistillation in both fertilization treatments (279 and 333% for organic and mineral fertilizations, respectively). There were no differences between the fertilization treatments. The amount of the volatile components showed by GC-MS chromatogram was highest in the essential oil obtained by hydrodistillation than SFE. The main volatile constituents of the essential oils were trans-anethole (Hydrodistillation: organic - 52.4%; mineral - 55.0%/ SFE: Hydrodistillation - 62.8%; mineral - 66.8%) and methyl-chavicol (Hydrodistillation: organic - 37.3%; mineral - 38.3%/ SFE: organic - 8.4%; mineral - 4.3%). A reduction of methyl-chavicol relative proportion of essential oil obtained by SFE was observed. Cys-anethole, α-copaene, trans-cariofilene, germacrene-D, β-selinene, biciclogermacrene and spathulenol were expressed only in hydrodistillation. The extraction of essential oil by SFE presented larger yield of essential oil than hydrodistillation technique, presenting, however, these essential oils, different phytochemical profiles.

Biomass production and chemical composition of essential oil of Piper callosum as affected by spacing in Manaus, Amazonas State, Brazil

The family Piperaceae contains nearly 2000 species, most of them distributed in two genera, Piper and Peperomia. In Brazil circa 170 Piper species are found, mainly in tropical areas Their use ranges from flavoring and culinary to raw material for pharmaceutical and cosmetic industry. One of these species, Piper callosum, is used in folk medicine in the Amazon area. The objective of this study was to evaluate the production of biomass (aerial parts) as well as yield and composition of the essential oil from the leaves, according to different spacing between cultivated plants at Embrapa Western Amazon, in Manaus, State of Amazonas, Brazil. The experimental design was randomized blocks, with four treatments and seven replicates with six plants. Biomass production was inversely proportional to the spatial arrangements, with the greatest biomass production (1034.93 kg/ha) in the shortest spacing (E1), although no statistical difference was verified between E3 and E4. The same response was observed for the production of essential oil. The chemical composition of the oil was not affected by spacing, and major compounds found were safrole (59.1%), beta-pinene (8.3%), alpha-pinene (6.5%), methyl eugenol (6.3%) and 1,8-cineole (4.1).

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.

Application of Reactions Norms in Study of Genotype Environmental Interaction for Milk Yield of Buffaloes

The aim of this study was to estimate genetic parameters for milk yield (MY) in buffaloes using reaction norms. Model included the additive direct effect as random and contemporary group (herd and year of birth) were included as fixed effects and cow age classes (linear) as covariables. The animal additive direct random effect was modeled through linear Legendre polynomials on environment gradient (EG) standardized means. Mean trends were taken into account by a linear regression on Legendre polynomials of environmental group means. Residual variance was modeled trough 6 heterogeneity classes (EG). These classes of residual variance was formed : EG1: mean = 866,93 kg (621,68 kg-1011,76 kg); EG2: mean = 1193,00 kg (1011,76 kg-1251,49 kg); EG3: mean = 1309,37 kg (1251,49 kg -1393,20 kg); EG4: mean = 1497,59 kg (1393,20 kg-1593,53 kg); EG5: mean = 1664,78 kg (1593,53 kg -1727,32kg) e EG6: mean = 1973,85 kg (1727,32 kg -2422,19 kg).(Co) variance functions were estimated by restricted maximum likelihood (REML) using the GIBBS3F90 package. The heritability estimates for MY raised as the environmental gradient increased, varying from 0.20 to 0.40. However, in intermediate to favorable environments, the heritability estimates obtained with Considerable genotype-environment interaction was found for MY using reaction norms. For genetic evaluation of MY is necessary to consider heterogeneity of variances to model the residual variance.

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.

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.

Diurnal effects on mentha canadensis oil concentration and composition at two different harvests

Japanese cornmint, also known as menthol mint (Mentiza canadensis L. syn M. arvensis L.), is an essential oil crop cultivated in several countries in Asia and South America. The plant is currently the only commercially viable source for natural menthol as a result of the high concentration of menthol in the oil compared with other crops. The hypothesis of this study was that harvesting at regular intervals within a 24-hour period would have an effect on essential oil concentration and composition of Japanese cornmint grown at high altitude in northern Wyoming. Flowering plants were harvested every 2 hours on 7 to 8 Aug. and on 14 to 15 Aug. and the essential oil was extracted by steam distillation and analyzed by gas chromatography mass spectroscopy (GC-MS). The effects of harvest date (Harvest 1 and Harvest 2) and harvest time (12 times within a 24-hour period) were significant on oil concentration and yield of menthol, but only harvest date was significant on the concentration of menthol in the oil. The interaction effect of harvest date and harvest time was significant on water content and on the concentrations of menthol and menthofuran in the oil and on the yield of limonene, menthol, and menthofuran. Overall, the oil concentration in grams per 100 g dried material for the two harvests (1.26 and 1.45, respectively), the concentration of menthol in the oil (67.2% and 72.9%, respectively), and menthol yield (1066 to 849 mg/100 g dried biomass) were higher in plants at Harvest 2 as compared with plants at Harvest 1. The oil concentration was higher in plants harvested at 1100 HR or at 1300 am and lowest in the plants harvested at 1500 BR. Menthol yield was the highest in plants harvested at 1300 HR and lowest in the plants harvested at 0700 HR, 1900 am, or at 0300 HR. This study demonstrated that harvesting time within a 24-hour period and harvest date (maturity of the crop) may affect essential oil concentration and composition of Japanese cornmint grown at high altitude in northern Wyoming.

Association between single-nucleotide polymorphisms and milk production traits in buffalo

The aim of this study was to identify single-nucleotide polymorphisms (SNPs) in buffaloes associated with milk yield and content, in addition to somatic cell scores based on the cross-species transferability of SNPs from cattle to buffalo. A total of 15,745 SNPs were analyzed, of which 1562 showed 1% significance and 4742 with 5% significance, which were associated for all traits studied. After application of Bonferroni's correction for multiple tests of the traits analyzed, we found 2 significant SNPs placed on cattle chromosomes BTA15 and BTA20, which are homologous to buffalo chromosomes BBU16 and BBU19, respectively. In this genome association study, we found several significant SNPs affecting buffalo milk production and quality. Furthermore, the use of the high-density bovine BeadChip was suitable for genomic analysis in buffaloes. Although extensive chromosome arm homology was described between cattle and buffalo, the exact chromosomal position of SNP markers associated with these economically important traits in buffalo can be determined only through buffalo genome sequencing.

Utility of inline milk fat and protein ratio to diagnose subclinical ketosis and to assign propylene glycol treatment in lactating dairy cows

The objective was to identify a fat-to-protein ratio (FPR) cut-off to diagnose subclinical ketosis (SCK) and to evaluate the effect of propylene glycol (PPG) treatment of cows with high FPR. The optimized cut-off was > 1.42; sensitivity (Se) = 92%; specificity (Sp) = 65%. A cut-off > 1.5 was selected for the PPG trial for balanced Se-Sp. Fat-to-protein ratio cut-offs > 1.25, 1.35, 1.50, 1.60, and 1.70 resulted in Se-Sp of 100% to 49%, 96% to 59%, 75% to 78%, 33% to 90%, and 8% to 96%, respectively. The proportions of cows with FPR > 1.25, 1.35, 1.42, 1.50, 1.60, and 1.70 were 60%, 50%, 44%, 30%, 14%, and 6%, respectively. Incidences of clinical ketosis and milk yield were similar between cows that received 400 mL of PPG (n = 34) and control cows (n = 38). Prevalence of SCK at enrollment was 29.2%; therefore, FPR > 1.5 is not indicated for treatment. Lower cut-offs should be used for screening.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.