System of teachers behavior : methodology of applications

AIESEP World Congress, IDP, FC

Adubação nitrogenada em cobertura para a cultivar de arroz irrigado BRS Jaçanã em várzea de cerrado de Roraima.

bitstream/item/174673/1/bp-12-2009-arrozirr-antonio.pd

Manejo de irrigação para o feijão-de-metro, nas fases vegetativa e produtiva, em ambiente protegido Irrigation scheduling for asparagus bean in vegetative and productive stages in greenhouse

O manejo adequado da irrigação é uma prática agrícola que requer informações para cada cultura explorada, em particular nas fases fenológicas do ciclo produtivo pois muitas espécies possuem períodos críticos durante os quais o estresse hídrico causa sérias reduções na produção. Este trabalho teve, como objetivo, avaliar o efeito de cinco níveis de potencial matricial de água no solo sobre o crescimento e produção do feijão-de-metro. O experimento foi conduzido em casa de vegetação, na área experimental pertencente ao Departamento de Engenharia da Universidade Federal de Lavras, Lavras, MG. O delineamento experimental foi o de blocos casualizados, em esquema fatorial 5 x 2, com quatro repetições. Os tratamentos foram constituídos de cinco potenciais matriciais de água no solo como indicativos do momento de irrigar (-15, -35, -55, -75 e -95 kPa), em duas fases fenológicas (vegetativa e produtiva), monitorados por sensores instalados a 0,15 m de profundidade. Os resultados permitiram concluir que a fase mais sensível ao déficit hídrico foi a produtiva e que a irrigação realizada no potencial matricial em torno de -15 kPa induziu a melhor resposta da cultura quanto ao desenvolvimento, produção e qualidade das vagens.<br>Proper irrigation water management requires knowledge on each exploited crop; particularly regarding vegetative and productive phases since many species have critical periods during which water stress causes serious yield reductions. This study was undertaken so as to assess the effect of five matric potential levels on asparagus bean growth and yield. The experiment was conducted under greenhouse conditions at the experimental area of Department of Engineering, Federal University of Lavras, Lavras, MG. The experimental design was randomized blocks in factorial 5 x 2. The treatments consisted of five matric potentials as indicative of the irrigation scheduling -15 -35 -55 -75 -95 kPa and at two phenological stages (vegetative and reproductive) as monitored by sensors installed at 0.15 m depth. The results allowed to conclude that the most sensitive phase to water deficit was the productive, and that irrigation held at matric potential around -15 kPa led to better crop response in the development, production and quality of pods

Beyond genomics: understanding exposotypes through metabolomics

Abstract Background Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact. Main text Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics. Conclusions Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation