Efecto del riego deficitario sobre la producción de Tiftón 85

Deficit irrigation consists of application of amounts of water less than plant requirements for satisfying water deficiencies of the crop, and this may maximize efficiency of water use. The aim of this study was to evaluate the effect of deficit irrigation on production of Tifton 85 grass. The experiment was carried out on the Santa Helena Farm in the municipality of Bom Despacho, MG, Brazil. Five levels of irrigation were used as treatments (28%, 42%, 57%, 71%, and 85% of the crop coefficient value) in randomized blocks with three replications. The following variables were evaluated: dry matter production (kg ha-1), leaf/stem ratio, height (cm), dead plant material (%), leaf area index, leaf area ratio (m2 kg-1), leaf weight ratio (kg kg-1), and specific leaf area (m2 kg-1). A difference was observed for Tifton 85 production in which the greatest average yield (6126.35 kg ha-1) was obtained through application of 71% Kc. For the other characteristics, there was no difference for any of the variables evaluated.El riego deficitario consiste en la aplicación de láminas inferiores a las necesarias para satisfacer las deficiencias hídricas de un cultivo, además que puede maximizar la eficiencia en el uso del agua. El objetivo de este trabajo fue estudiar el efecto del riego deficitario en la producción del cultivo Tifton 85. El experimento fue realizado en la Hacienda Santa Helena situada en el municipio de Bom Despacho, Minas Gerais (MG) Brasil. Los tratamientos utilizados fueron: cinco láminas de riego (28%, 42%, 57%, 71% y 85% del valor de coeficiente de cultivo) en bloques aleatorios con tres repeticiones. Fueron evaluadas las siguientes variables: producción de materia seca (kg ha-1), relación hoja/altura, altura (cm), materia muerta (%), índice de área foliar, relación de área foliar (m2 kg-1), relación de peso foliar (kg kg-1) y área foliar especifica (m2 kg-1). Se observó una diferencia en la producción de Tifton 85, donde el mayor promedio de producción (6126.35 kg ha-1) se obtuvo con la aplicación de las láminas 71% Kc. Para las demás características no hubo diferencia en ninguna de las variables estudiadas.Fil: Silva, Anita Cristina Costa da.Fil: Lima, Luiz Antonio.Fil: Almeida, Willian Fernandes de.Fil: Thebaldi, Michael Silveira.Fil: Silva, Antônio Carlos da

Production of lettuce with brackish water in NFT hydroponic system

Groundwater reserves in the semi-arid regions, which are mostly brackish, could be used to meet local water demands. Hydroponic cultivation is an alternative of rational use of water. Thus, the objective of this work was to evaluate the technical feasibility of using brackish groundwater in the semi-arid region of Bahia and Recôncavo of Bahia for hydroponic production of curly lettuce cv. ‘Verônica’ and purple lettuce cv. ‘Quatro Estações’. The experiment was conducted in a greenhouse in the city of Cruz das Almas, Bahia State, in a randomized block experimental design, composed of seven treatments [T1- public-supply water; T2- water from the well of UFRB; T3- reject water from the well of Cruz das Almas; T4- water from the well of Sapeaçu; T5- reject water from the well of Sapeaçu; T6- reject water from the well of Conceição do Coité and T7- artificially salinated water (NaCl)] and six replicates in an experimental hydroponic structure using the nutrient film technique (NFT). The following variables were analyzed: number of leaves, shoot fresh matter, shoot length, root length, shoot dry matter, and root dry matter. Relative shoot dry matter production in curly lettuce increased by 1, 5, and 2% in the treatments T2, T3, and T4, respectively, whereas in purple lettuce, the increments were 10, 1, and 20%, respectively, for the same treatments. The use of brackish groundwater from the deep tubular wells of the Federal University of Recôncavo da Bahia and Sapeaçu and desalination reject water from the tubular well of Cruz das Almas proved to be technically feasible for hydroponic lettuce production

Alignment and contribution of nursing doctoral programs to achieve the sustainable development goals

Background: Different social segments from several regions of the world face challenges in order to achieve the sustainable development goals (SDGs). Nursing represents the greatest number of health workforce in the globe, dealing with these challenges in different paths, among them the training of human resources. In this context, the goal of this study was to compare the relationship between the objectives and research areas underlying nursing doctoral programs in Latin America and the SDGs. Method: Documental research comparing data of all Latin American nursing doctoral programs and the SDGs, conducted between January and March 2020. Results: From the total of 56 existing programs in Latin America, this study analyzed 52 of them, representing 92.8% of the total. Most nursing doctoral programs have contributed to SDG 3, in addition to goals 1, 2, 4, 5, 6, 8, 9, 10, 12 and 16. The SDGs 11, 13, 14, 15 and 17 were not related to any of the analyzed programs. Data reveal that the training of nursing PhDs is essential to fulfilling these goals. Results also indicate a need of programs to remain committed to relationships that enhance nursing skills to cope with the current challenges in terms of global health, such as investments for the reduction of social and gender inequities. Conclusion: The doctoral training of nurses in Latin America needs to be better aligned with the sustainable development goals (SDGs), since there is a high concentration in SDG 3. We believe that nursing will bring a greater contribution to the movement to protect planetary health as the principles governing nursing practices are better aligned with international health demands and agendas.publishersversionpublishe

Involvement of brassinosteroids and ethylene in the control of mitochondrial electron transport chain in postharvest papaya fruit

The plant hormones brassinosteroids (BR) and ethylene (ET) act together to regulate plant metabolism. We used BR and 1-methylcyclopropene (1-MCP, an ET action inhibitor) to elucidate the interactions between both hormones for the regulation of mitochondrial respiratory pathways in papaya fruit. The exogenous application of the 24-epibrassinolide (epiBR) enhanced the alternative oxidase (AOX) capacity. While treatment with Brz2001 (Brz is a specific inhibitor of the BR synthesis) also enhanced AOX capacity, these effects lacked in fruit treated simultaneously with epiBR and Brz. Changing the BR level had no effect on ET emission rate in the first 24 h, but a reduction in ET emission was observed in Brz-treated fruit on the fifth day. Together with Brz, epiBR increased the ET production on the fifth day, following the day in which the treatment was carried out. When the ET sensitivity of fruit was inhibited by the application of 1-MCP, the effects of epiBR and Brz were opposite to those obtained without 1-MCP. AOX capacity was slightly inhibited by epiBR in fruit pre-treated with 1-MCP. Data suggest that BR and ET act antagonistically, therefore regulating, directly or indirectly, AOX capacity during papaya fruit ripening.Instituto de Fisiología Vegeta

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