36 resultados para Beginning inference
Resumo:
This study aimed to evaluate the potential for milk production (MP), lactation length (LL) and calving interval (CI), analyze the environmental component affecting these traits, and to estimate the heritability and repeatability for milk production in crossbreds of Murrah buffalo cows in the state of Alagoas, Brazil. Data was composed of 487 observations of MP from 136 lactations recorded between the years of 2000 and 2010. In the analysis of variance for PL, the fixed effects were season (1- October to March, 2 -April to September) and year of the beginning of lactation, calving order and the LL (covariate). For the analysis of LL only the fixed effect of year of the beginning of lactation was included, and finally for the CI analysis, year of the beginning of lactation and calving order. The estimates of covariance were obtained using unicharacteristic analysis by Bayesian inference method, applyingan animal model, through Gibbs sampling. The additive genetic, permanent environment and residual effects were included as random effects in the model. The averages (sd) of MP, LL and CI were 2,218.03 kg (408.18), 282.59 days (39.48) e 422.49 days (91.05), respectively. All the effects included in the models were important (P<0.01). The estimates of heritability and repeatability for PL were 0.29 and 0.69, respectively. The results suggest that there is a moderate genetic variability among individuals for PL, indicating the possibility to obtain gain using selection.
Resumo:
There are three distinct and complementary objectives in this article in order to clarify the higher education outline in Brazil, specifically evening courses (classes are held on weekdays, generally from 7:00 pm to 10:30 pm) and thesecurrent sector policies. The first objective is to present a short historical overview on the establishment of evening courses in Brazil, including those in the higher education level, occurred on the middle of last century. The second objective is to demonstrate the growth of evening higher education in Brazil, considering that in 1998, of the 2.1 million college enrollments, 55.3% were enrolled in evening courses; in 2010, twelve years later, of the 5.4 million students enrolled, there were 63.5% enrolled in evening courses. This expansion is due to the growing need of many students who must work while attending college, to defray costs of the study as well as personal and family costs. The reality of the working student is hostile considering external factors, such as transport problems, public security and lack of legislation for flexible working hours. The third objective is to discuss current public policies to expand eveningopenings in public institutions which represent nowadays only 16.1% of the 3.4 million enrollments for evening classes, including federal (6.8%), state (7.0%) and municipal (2.3%) institutions. In the third objective it is included the discussion of programs for scholarships and tuition loans. The methodology applied was to rescue historical information on the establishment and the expansion of evening courses in Brazil, analyzing the current general Brazilian policies and the specific ones from the State of São Paulo. The research results pointed to the importance of federal programs for scholarships and tuition loans for students from private institutions such as the 1,382,484 scholarships since 2004 (PROUNI Program) and the 847,000 tuition loans since 1999 (FIES Program). Important steps have been made by the Brazilian government. Considering that there are 3,987,424 enrollments in private institutions, the effectiveness of the programs for scholarships and tuition loans is still insufficient to meet the universal benefits for the student’s needs. Evening courses became the real instrument of social inclusion for many Brazilian youths and must be expanded quantitatively and qualitatively, with aggressive public policies, including also, scholarships and tuition loans.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.