Produtividade do tomate industrial submetido a adubação organomineral em cobertura / Productivity of industrial tomato submitted to organo-mineral fertilization in cover

Visando um menor impacto ambiental o uso de adubo organomineral vem ganhando destaque nas áreas de cultivo. O objetivo com este trabalho foi avaliar a eficiência da adubação organomineral e mineral, em cobertura, na produção de tomate industrial. Os tratamentos foram: testemunha - adubação mineral no plantio; T1 - adubação mineral no plantio e cobertura e T2 - adubação mineral no plantio e adubação organomineral em cobertura. Foram realizadas duas colheitas aos 110 e 118 dias após o transplantio. Foram quantificados o número, o comprimento, diâmetro, peso, massa fresca e seca de frutos. Os frutos foram avaliados e separados em comercializáveis e não comercializáveis, a produtividade total (t ha-1) foi obtida através do somatório da produção comercial e não comercial. A produtividade média geral de frutos (t ha-1) foi determinada a partir da integração da massa de frutos delimitada nas duas colheitas. No fruto foram determinados o pH, °Brix, coloração da polpa e acidez titulável. O diâmetro equatorial não apresentou diferenças significativas entre o tratamento organomineral e testemunha. Os resultados obtidos de número de frutos por planta, massa fresca e comprimento dos frutos não apresentou diferenças estatísticas. Com relação a massa seca dos frutos, número de frutos comercializáveis, peso dos frutos e produtividade o tratamento com organomineral obteve os melhores resultados. Não ocorre diferença para as análises físico-químicas do fruto. O adubo organomineral em cobertura proporcionou aumento de massa fresca, massa seca e produtividade média de frutos de tomate industrial

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Avaliação ambiental de BTEX (benzeno, tolueno, etilbenzeno, xilenos) e biomarcadores de genotoxicidade em trabalhadores de postos de combustíveis

Resumo Introdução: trabalhadores de postos de combustíveis estão expostos às diversas substâncias químicas presentes no ambiente de trabalho, destacando-se entre elas o benzeno, devido às suas propriedades carcinogênicas. Objetivo: avaliar os danos genotóxicos relacionados à exposição ocupacional ao BTEX (benzeno, tolueno, etilbenzeno, xilenos) em trabalhadores de cinco postos de combustíveis do município do Rio de Janeiro, RJ. Metodologia: foram analisadas concentrações de BTEX no ar; atividades das enzimas catalase e glutationa S-transferase; e ensaio cometa em amostras de sangue total de 97 trabalhadores. Resultados: as concentrações de BTEX estavam dentro dos valores preconizados pela NR 15, incluindo Anexo 13-A. Entretanto, uma oscilação nos resultados de ensaio cometa foi observada entre os trabalhadores dos diferentes postos de combustíveis, principalmente em trabalhadores de postos com menores concentrações de benzeno. Discussão: esse resultado está de acordo com a literatura científica atual, que indica uma curva dose-resposta supralinear para o benzeno, observando-se em baixas concentrações um aumento não linear do risco de leucemia, provavelmente relacionado à maior metabolização do benzeno e à maior produção de seus metabólitos tóxicos nessas concentrações. Conclusão: os resultados deste estudo sugerem que a exposição ao BTEX, mesmo em baixas concentrações, contribui para o risco genotóxico à saúde humana

Environmental assessment of BTEX (benzene, toluene, ethylbenzene, xylenes) and biomarkers of genotoxicity in gas stations workers

<p></p><p>Abstract Introduction: gas station workers are exposed to several chemicals in their workplace, highlighting benzene, due to its carcinogenic properties. Objective: to assess the genotoxic damage related to occupational exposure to BTEX (benzene, toluene, ethylbenzene, xylenes) in workers of five gas stations in Rio de Janeiro, RJ. Methods: analysis of BTEX concentrations in the air were carried out; as well as activities of catalase and glutathione S-transferase; and comet assay in whole blood samples of 97 workers. Results: BTEX levels were within the Brazilian threshold levels recommended by the NR 15, including Annex 13-A. However, an oscillation of the comet assay results was observed among workers of different gas stations, mainly in workers from gas stations with lower concentrations of benzene. Discussion: this result is in accordance with the current international scientific literature that indicates a supralinear exposure-response curve for benzene. In lower concentrations we could observe a high non-linear risk of leukemia, probably due to a greater benzene metabolism and a higher production of its toxic metabolites. Conclusion: the results of this study suggest that exposure to BTEX, even in low concentrations, contributes to genotoxic risk to human health.</p><p></p