20 research outputs found
Análise econômica do orégano irrigado considerando fatores de risco econômico
The oregano is a plant, rich in essential oil and very used as spice in the preparation of foods. The objective of this paper was to analyze the viability of irrigation for oregano in Presidente Prudente, São Paulo state, Brazil, including economic risk factors, their effect on irrigation total cost, as well as the different pumping kinds. The Monte Carlo simulation was utilized to study the economic factors: fixed cost, labor, maintenance, pumping and water. The use of irrigation for the oregano in the region of Presidente Prudente is indicated because of its economic feasibility and the reduced risks. The average values of the benefit/cost for all water depths tested were higher than 1, indicating viability. The use of irrigation promoted lower risks compared to the non irrigated crop. The micro irrigation system presented greater sensitivity to changes of prices of the equipment associated to the variation of the useful life of the system. The oregano selling price was the most important factor involved in annual net profit. The water cost was the factor of lesser influence on the total cost. Due to the characteristic of high drip irrigation frequency there was no difference between the tariffs based in use hour of electric energy classified as green and blue, which are characterized by applying different rates on the energy consumption and demand according to the hours of day and times of the year. For the studied region it was recommended drip irrigation water management of oregano with the daily application of 100% of pan evaporation Class A using electric motor with tariffs blue or green
Socioeconomic, demographic and nutritional factors associated with maternal weight gain in general practices in Southern Brazil
Índice de alimentação saudável para gestantes: adaptação para uso em gestantes brasileiras
Repositioning of the global epicentre of non-optimal cholesterol
High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe
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
Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)
From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions
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
Oregano production under various water depths estimated by means of the class A pan evaporation Produção de orégano com diferentes lâminas de irrigação estimadas a partir da evaporação do tanque classe A
The purpose of this experiment was to analyze the effect of five irrigation water depths on oregano production. Oregano is a plant rich in essential oil, commonly used as seasoning in food preparation. The water depths were estimated based on the class A pan evaporation (CPE): 0 CPE (without water replacement); 25 CPE, 50 CPE, 75 CPE, and 100% CPE. The analyzed variables were fresh and dry weight of leaves and roots, yield, net return, and water use efficiency. The experiment was carried out in Presidente Prudente, São Paulo State, Brazil, from February to May 2006. The best results for all the studied variables were found when 100% CPE was used. A linear positive relation was observed between water increments and fresh and dry weight of both the aboveground part and roots. The use of a water depth corresponding to 100% CPE resulted in the maximum productivity (8,089.7 kg ha-1), and in the highest net annual return (R 57.637,87 ha-1)