4 resultados para Contamination marker
Resumo:
The establishment of a specific Marker-Assisted Selection Facility at the Embrapa Rice and Beans Biotechnology Laboratory, in 2014, has better supported the routine analysis with molecular markers demanded by the Embrapa Common Bean Breeding Program. In addition, it has also supported other Embrapa plant breeding programs, such as rice and cotton.
Resumo:
2009
Resumo:
In this work, the risk of groundwater contamination from organic substances in sewage sludge from wastewater treatment stations was evaluated in its worst case. The sewage sludge was applied as fertilizer in corn culture, prioritizing the substances for monitoring. The assessing risk took place in a Typic Distrophic Red Latossol (TDRL) area, in the county district of Jaguariúna, SP. The simulators CMLS-94 and WGEN were used to evaluate the risk of twenty-eight organic substances in sewage sludge to leach to groundwater. The risk of groundwater contamination was accomplished for a single sludge dose application in a thousand independent and equally probable years, simulated to esteem the substances leaching in one year after the application date of the sludge. It is presented the substances that should be priorly monitored in groundwater.
Resumo:
Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.