270 research outputs found

    Poverty Reduction Effects of Agricultural Technology Adoption: A Micro-evidence from Rural Tanzania

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    This article evaluates the impact of adoption of improved pigeonpea technologies on consumption expenditure and poverty status using cross-sectional data of 613 households from rural Tanzania. Using multiple econometric techniques, we found that adopting improved pigeonpea significantly increases consumption expenditure and reduces poverty. This confirms the potential role of technology adoption in improving household welfare as higher incomes translate into lower poverty. This study supports broader investment in agriculture research to address vital development challenges. Reaching the poor with better technologies however requires policy support for improving extension efforts, access to seeds and market outlets that stimulate adoption

    Impact of modern agricultural technologies on smallholder welfare: Evidence from Tanzania and Ethiopia

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    This paper evaluates the potential impact of adoption of improved legume technologies on rural household welfare measured by consumption expenditure in rural Ethiopia and Tanzania. The study utilizes cross-sectional farm household level data collected in 2008 from a randomly selected sample of 1313 households (700 in Ethiopia and 613 in Tanzania). The causal impact of technology adoption is estimated by utilizing endogenous switching regression. This helps us estimate the true welfare effect of technology adoption by controlling for the role of selection problem on production and adoption decisions. Our analysis reveals that adoption of improved agricultural technologies has a significant positive impact consumption expenditure (in per adult equivalent terms) in rural Ethiopia and Tanzania. This confirms the potential role of technology adoption in improving rural household welfare as higher consumption expenditure from improved technologies translate into lower poverty, higher food security and greater ability to withstand risk. An analysis of the determinants of adoption highlighted inadequate local supply of seed, access to information and perception about the new cultivars as key constraints for technology adoption

    Climate smart agriculture (CSA)

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    Climate change fundamentally shifts the agricultural development agenda. Changing temperature and precipitation, sea level rise, and the rising frequency of extreme climate events will significantly reduce global food production in this century unless action is taken. Major investments, private and public, will be needed.! Adapting agriculture to climate change is necessary to achieve food security, and agricultural mitigation can also reduce atmospheric greenhouse gas concentrations and slow climate change itself. There are many drivers of change affecting agricultural sectors around the world, including population growth, changes in consumer demand and market integration. Climate Smart Agriculture is an integrated approach to achieve food security in the face of climate change, while also mitigating climate change and contribute to other development goals

    "Nōgyō hisonyashinaigusa" by Yoshitake Tokuyama, 1826 - Reprinting by Original Text

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    Rapid changes in land use, food systems, and livelihoods require social–ecological systems that keep multiple options open and prepare for future unpredictability. Sustainagility refers to the properties and assets of a system that sustain the ability (agility) of agents to adapt and meet their needs in new ways. In contrast, sustainability tends to invoke persistence along current trajectories, and the resilience to return to current baselines. With three examples, the use and conservation of agrobiodiversity is explored along temporal, spatial, and human institutional scales for its role in sustainagility: first, farmers’ seed systems; second, complex pollination systems; and third, wildlife conservation in agricultural areas with high poverty. Incentives are necessary if agrobiodiversity is to provide benefits to future generation

    NMR chemistry analysis of red blood cell constituents in normal subjects and lithium-treated psychiatric patients

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    Red blood cells from 18 lithium carbonate-treated patients with bipolar affective disorder and 12 normal volunteers were analyzed using 1H-nuclear magnetic resonance (NMR) spectroscopy. The spectra were analyzed for alanine, adenosine triphosphate (ATP), choline, 2,3-diphosphoglycerol, glucose, glutathione, glycine, and lactate. Significant elevations of choline and lactate were found in the lithium-treated patients compared with normal, unmedicated subjects. The elevation of lactate due to anaerobic metabolism in the red blood cells was further investigated via fluoremetric analysis and appears to be caused by blood standing at room temperature. The observed increases in red blood cell choline are sufficiently high and statistically significant to warrant additional studies on the dramatic effects of lithium on this red cell metabolite, which might be important for an understanding of its mechanism of action in psychiatric disorders.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25491/1/0000032.pd

    Climate-smart agriculture global research agenda: Scientific basis for action

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    Background: Climate-smart agriculture (CSA) addresses the challenge of meeting the growing demand for food, fibre and fuel, despite the changing climate and fewer opportunities for agricultural expansion on additional lands. CSA focuses on contributing to economic development, poverty reduction and food security; maintaining and enhancing the productivity and resilience of natural and agricultural ecosystem functions, thus building natural capital; and reducing trade-offs involved in meeting these goals. Current gaps in knowledge, work within CSA, and agendas for interdisciplinary research and science-based actions identified at the 2013 Global Science Conference on Climate-Smart Agriculture (Davis, CA, USA) are described here within three themes: (1) farm and food systems, (2) landscape and regional issues and (3) institutional and policy aspects. The first two themes comprise crop physiology and genetics, mitigation and adaptation for livestock and agriculture, barriers to adoption of CSA practices, climate risk management and energy and biofuels (theme 1); and modelling adaptation and uncertainty, achieving multifunctionality, food and fishery systems, forest biodiversity and ecosystem services, rural migration from climate change and metrics (theme 2). Theme 3 comprises designing research that bridges disciplines, integrating stakeholder input to directly link science, action and governance. Outcomes: In addition to interdisciplinary research among these themes, imperatives include developing (1) models that include adaptation and transformation at either the farm or landscape level; (2) capacity approaches to examine multifunctional solutions for agronomic, ecological and socioeconomic challenges; (3) scenarios that are validated by direct evidence and metrics to support behaviours that foster resilience and natural capital; (4) reductions in the risk that can present formidable barriers for farmers during adoption of new technology and practices; and (5) an understanding of how climate affects the rural labour force, land tenure and cultural integrity, and thus the stability of food production. Effective work in CSA will involve stakeholders, address governance issues, examine uncertainties, incorporate social benefits with technological change, and establish climate finance within a green development framework. Here, the socioecological approach is intended to reduce development controversies associated with CSA and to identify technologies, policies and approaches leading to sustainable food production and consumption patterns in a changing climate

    Prospective open-label study of add-on and monotherapy topiramate in civilians with chronic nonhallucinatory posttraumatic stress disorder

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    BACKGROUND: In order to confirm therapeutic effects of topiramate on posttraumatic stress disorder (PTSD) observed in a prior study, a new prospective, open-label study was conducted to examine acute responses in chronic, nonhallucinatory PTSD. METHODS: Thirty-three consecutive newly recruited civilian adult outpatients (mean age 46 years, 85% female) with DSM-IV-diagnosed chronic PTSD, excluding those with concurrent auditory or visual hallucinations, received topiramate either as monotherapy (n = 5) or augmentation (n = 28). The primary measure was a change in the PTSD Checklist-Civilian Version (PCL-C) score from baseline to 4 weeks, with response defined as a ≥ 30% reduction of PTSD symptoms. RESULTS: For those taking the PCL-C at both baseline and week 4 (n = 30), total symptoms declined by 49% at week 4 (paired t-test, P < 0.001) with similar subscale reductions for reexperiencing, avoidance/numbing, and hyperarousal symptoms. The response rate at week 4 was 77%. Age, sex, bipolar comorbidity, age at onset of PTSD, duration of symptoms, severity of baseline PCL-C score, and monotherapy versus add-on medication administration did not predict reduction in PTSD symptoms. Median time to full response was 9 days and median dosage was 50 mg/day. CONCLUSIONS: Promising open-label findings in a new sample converge with findings of a previous study. The use of topiramate for treatment of chronic PTSD, at least in civilians, warrants controlled clinical trials

    What Is the Evidence Base for Climate-Smart Agriculture in East and Southern Africa? A Systematic Map

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    More than 500 million USD will soon be invested in climate-smart agriculture (CSA) programmes in sub-Saharan Africa. Improving smallholder farm management is the core of most of these programmes. However, there has been no comprehensive information available to evaluate how changing agricultural practices increases food production, improves resilience of farming systems and livelihoods, and mitigates climate change—the goals of CSA. Here, we present a systematic map—an overview of the availability of scientific evidence—for CSA in five African countries: Tanzania, Malawi, Mozambique, Zimbabwe and Zambia. We conducted a systematic literature search of the effects of 102 technologies, including farm management practices (e.g., leguminous intercropped agroforestry, increased protein content of livestock diets, etc.), on 57 indicators consistent with CSA goals (e.g., yield, water use efficiency, carbon sequestration, etc.) as part of an effort called the "CSA Compendium". Our search of peer-reviewed articles in Web of Science and Scopus produced 150,567 candidate papers across developing countries in the global tropics. We screened titles, abstracts and full texts against predetermined inclusion criteria, for example that the investigation took place in a tropical developing country and contains primary data on how both a CSA practice and non-CSA control affect a preselected indicator. More than 1500 papers met these criteria from Africa, of which, 153 contained data collected in one of the five countries. Mapping the studies shows geographic and topical clustering in a few locations, around relatively few measures of CSA and for a limited number of commodities, indicating potential for skewed results and highlighting gaps in the evidence. This study sets the baseline for the availability of evidence to support CSA programming in the five countries

    Climate-smart agriculture practices for mitigating greenhouse gas emissions

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    Agricultural lands make up approximately 37% of the global land surface, and agriculture is a significant source of greenhouse gas (GHG) emissions, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Those GHGs are responsible for the majority of the anthropogenic globalwarming effect.Agricultural GHG emissions are associated with agricultural soil management (e.g. tillage), use of both synthetic and organic fertilisers, livestock management, burning of fossil fuel for agricultural operations, and burning of agricultural residues and land use change. When natural ecosystems such as grasslands are converted to agricultural production, 20-40% of the soil organic carbon (SOC) is lost over time, following cultivation.We thus need to develop management practices that can maintain or even increase SOC storage in and reduce GHG emissions from agricultural ecosystems. We need to design systematic approaches and agricultural strategies that can ensure sustainable food production under predicted climate change scenarios, approaches that are being called climate-smart agriculture (CSA). Climate-smart agricultural management practices, including conservation tillage, use of cover crops and biochar application to agricultural fields, and strategic application of synthetic and organic fertilisers have been considered a way to reduce GHG emission from agriculture. Agricultural management practices can be improved to decreasing disturbance to the soil by decreasing the frequency and extent of cultivation as a way to minimise soil C loss and/or to increase soil C storage. Fertiliser nitrogen (N) use efficiency can be improved to reduce fertilizer N application and N loss. Management measures can also be taken to minimise agricultural biomass burning. This chapter reviews the current literature on CSA practices that are available to reduce GHG emissions and increase soil C sequestration and develops a guideline on best management practices to reduce GHG emissions, increase C sequestration, and enhance crop productivity in agricultural production systems
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