Farmers’ preferential choice decisions to alternative cassava value chain strands in Morogoro rural district, Tanzania

The study was conducted to determine farmers’ preferential choice decision of alternative cassava value chain strands and as well as factors behind such decisions in Morogoro rural District, Tanzania. Factor analysis was first used to reduce and identify the factors (variables for further analysis whereby the factors with highest eigen-value were applied to develop factor scores to measure the attitudinal variables. Results indicate that farmers have positive risk attitude towards participation in the alternative cassava value chain strands for commercialization. A count data model known as Poisson model was applied to determine the factors which influenced this attitude. Results indicated that farm size, experience, female-headed households and land-holding had influenced the farmers’ preferential choice decision. Recommendations for enhancing farmers’ participation in profitable cassava value chain strands are strengthening coordination, provision of improved cassava varieties and introduction of cassava processing technologies.Preferential choice decisions; factor analysis; cassava farmers; risk attitude; Poisson model

Economics of rainwater harvesting for crop enterprises in semi-arid areas: the case of Makanya Watershed in Pangani River Basin, Tanzania

River basinsWatershedsRainWater harvestingVillagesMaizeBeansRunoff

Economics of rainwater harvesting for crop enterprises in semi-arid areas: the case of Makanya Watershed in Pangani River Basin, Tanzania

River basinsWatershedsRainWater harvestingVillagesMaizeBeansRunoffEconomic aspects

Temporal Modulation of Traveling Waves in the Flow Between Rotating Cylinders With Broken Azimuthal Symmetry

The effect of temporal modulation on traveling waves in the flows in two distinct systems of rotating cylinders, both with broken azimuthal symmetry, has been investigated. It is shown that by modulating the control parameter at twice the critical frequency one can excite phase-locked standing waves and standing-wave-like states which are not allowed when the system is rotationally symmetric. We also show how previous theoretical results can be extended to handle patterns such as these, that are periodic in two spatial direction.Comment: 17 pages in LaTeX, 22 figures available as postscript files from http://www.esam.nwu.edu/riecke/lit/lit.htm

The effect of nitrogen-fertilizer and optimal plant population on the profitability of maize plots in the Wami River sub-basin, Tanzania: A bio-economic simulation approach

Maize (Zea mays L.) is the essential staple in sub-Saharan Africa (SSA) and Tanzania in particular; the crop accounts for over 30% of the food production, 20% of the agricultural gross domestic product (GDP) and over 75% of the cereal consumption. Maize is grown under a higher risk of failure due to the over-dependence rain-fed farming system resulting in low income and food insecurity among maize-based farmers. However, many practices, including conservation agriculture, soil and water conservation, resilient crop varieties, and soil fertility management, are suggested to increase cereal productivity in Tanzania. Improving planting density, and the use of fertilizers are the immediate options recommended by Tanzania's government. In this paper, we evaluate the economic feasibility of the improved planting density (optimized plant population) and N-fertilizer crop management practices on maize net returns in semi-arid and sub-humid agro-ecological zones in the Wami River sub-Basin, Tanzania. We introduce a bio-economic simulation model using Monte Carlo simulation procedures to evaluate the economic viability of risky crop management practices so that the decision-maker can make better management decisions. The study utilizes maize yield data sets from two biophysical cropping system models, namely the APSIM and DSSAT. A total of 83 plots for the semi-arid and 85 plots for the sub-humid agro-ecological zones consisted of this analysis. The crop management practices under study comprise the application of 40 kg N-fertilizer/ha and plant population of 3.3 plants/m2. The study finds that the use of improved plant population had the lowest annual net return with fertilizer application fetching the highest return. The two crop models demonstrated a zero probability of negative net returns for farms using fertilizer rates of 40 kg N/ha except for DSSAT, which observed a small probability (0.4%) in the sub-humid area. The optimized plant population presented 16.4% to 26.6% probability of negatives net returns for semi-arid and 14.6% to 30.2% probability of negative net returns for sub-humid zones. The results suggest that the application of fertilizer practices reduces the risks associated with the mean returns, but increasing the plant population has a high probability of economic failure, particularly in the sub-humid zone. Maize sub-sector in Tanzania is projected to continue experiencing a significant decrease in yields and net returns, but there is a high chance that it will be better-off if proper alternatives are employed. Similar studies are needed to explore the potential of interventions highlighted in the ACRP for better decision-making

Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach

Maize (Zea mays L.), sorghum (Sorghum bicolor L. Moench) and rice (Oryza sativa) are essential staple crops to the livelihoods of many Tanzanians. But the future productivity of these crops is highly uncertain due to many factors including overdependence on rain-fed, poor agricultural practices and climate change and variability. Despite the multiple risks and constraints, it is vital to highlight the pathways of cereal production in the country. Understanding the pathways of cereals helps to inform policymakers, so they can make better decisions to improve the viability of the sector and its potential to increase food production and income for the majority population. In this study, we employ a Monte Carlo simulation approach to develop a multivariate empirical (MVE) distribution model to simulate stochastic variables for main cereal crops in Tanzania. Eleven years (2008–2018) of yields and prices data for maize, sorghum and rice were used in the model to simulate and forecast yields and prices in Dodoma and Morogoro regions of Tanzania for a seven-year period, from 2019 to 2025. Dodoma and Morogoro regions represent semi-arid and sub-humid agro-ecological zones, respectively. The simulated yields and prices were used with total costs and total area harvested for each crop to calculate the probable net present value (NPV) for each agro-ecological zone. The results on crop yield show a slightly increasing trend for all three crops in Dodoma region. Likewise, rice yield is expected to marginally increase in Morogoro with a decreasing trend for maize and sorghum, meanwhile, the prices for the three crops all are projected to increase for the two regions. Generally, the results on economic feasibility in terms of NPV revealed a high probability of success for all the crops in Dodoma despite a higher relative risk for rice. The results in Morogoro presented a high probability of success for rice and sorghum with maize indicating the highest relative risk, and a 2.41% probability of negative NPV. This study helps to better understand the outlook of the main cereal crop sub-sectors in two agro-ecological zones of Tanzania over the next seven years. With high dependence on rain-fed agriculture, production of main cereals in Tanzania are likely to face a high degree of risk and uncertainty threatening livelihoods, incomes and foo

Farmers’ preferential choice decisions to alternative cassava value chain strands in Morogoro rural district, Tanzania

The study was conducted to determine farmers’ preferential choice decision of alternative cassava value chain strands and as well as factors behind such decisions in Morogoro rural District, Tanzania. Factor analysis was first used to reduce and identify the factors (variables for further analysis whereby the factors with highest eigen-value were applied to develop factor scores to measure the attitudinal variables. Results indicate that farmers have positive risk attitude towards participation in the alternative cassava value chain strands for commercialization. A count data model known as Poisson model was applied to determine the factors which influenced this attitude. Results indicated that farm size, experience, female-headed households and land-holding had influenced the farmers’ preferential choice decision. Recommendations for enhancing farmers’ participation in profitable cassava value chain strands are strengthening coordination, provision of improved cassava varieties and introduction of cassava processing technologies

Symptoms and functional limitations related to respiratory health and carbon monoxide poisoning in Tanzania: a cross sectional study

BACKGROUND: The burden of chronic respiratory symptoms and respiratory functional limitations is underestimated in Africa. Few data are available on carbon monoxide (CO) poisoning in sub-Saharan Africa and existing data is derived from CO in ambient air, but not from biomarkers in the blood. METHODS: Data from the Tanzanian Lung Health study, a cross-sectional study on lung health among outpatients and visitors to an urban as well as a rural hospital in Tanzania, was analyzed to describe respiratory symptoms and functional limitations. Saturation of peripheral blood with carbon monoxide (SpCO) was measured transcutaneously and non-invasively in participants using a modified pulse oxymeter indicative of CO poisoning. Univariate and multivariate analysis was performed. RESULTS: Nine hundred and ninety-seven participants were included in the analysis, the median age of participants was 46 years (49% male). 38% of participants reported some degree of chronic shortness of breath and 26% felt limited in their daily activities or at work by this symptom. The median SpCO was 7% (IQR 4-13, range 2-31%) among all participants without active smoking status (N = 808). Participants cooking with gas or electricity had the lowest SpCO (median 5%), followed by participants cooking with charcoal (median 7%). Cooking with wood, particularly using a stove, resulted in highest SpCO (median 11.5%). Participants from households where cooking takes place in a separate room had the lowest SpCO as compared to cooking outside or cooking in a shared room inside (6% vs. 9% vs.10.5%, p < 0.01). Sex or the activity of cooking itself was not associated with a difference in SpCO. Multivariate analysis confirmed cooking in a separate room (as compared to cooking outside) and living in a rural vs. urban setting as protective factors against high SpCO. CONCLUSION: The findings demonstrate a high burden of chronic respiratory symptoms which also cause socioeconomic impact. High levels of SpCO indicate a relevant burden of carbon monoxide poisoning in the local population. The level of CO in the blood is more dependent on shared exposure to sources of CO with the type of housing and type of cooking fuel as most relevant factors, and less on person-individual risk factors or activities

Proactive prevention: Act now to disrupt the impending non-communicable disease crisis in low-burden populations

Non-communicable disease (NCD) prevention efforts have traditionally targeted high-risk and high-burden populations. We propose an alteration in prevention efforts to also include emphasis and focus on low-risk populations, predominantly younger individuals and low-prevalence populations. We refer to this approach as “proactive prevention.” This emphasis is based on the priority to put in place policies, programs, and infrastructure that can disrupt the epidemiological transition to develop NCDs among these groups, thereby averting future NCD crises. Proactive prevention strategies can be classified, and their implementation prioritized, based on a 2-dimensional assessment: impact and feasibility. Thus, potential interventions can be categorized into a 2-by-2 matrix: high impact/high feasibility, high impact/ low feasibility, low impact/high feasibility, and low impact/low feasibility. We propose that high impact/high feasibility interventions are ready to be implemented (act), while high impact/low feasibility interventions require efforts to foster buy-in first. Low impact/high feasibility interventions need to be changed to improve their impact while low impact/low feasibility might be best re-designed in the context of limited resources. Using this framework, policy makers, public health experts, and other stakeholders can more effectively prioritize and leverage limited resources in an effort to slow or prevent the evolving global NCD crisis.Fil: Njuguna, Benson. Moi Teaching & Referral Hospital; KeniaFil: Fletcher, Sara L.. State University of Oregon; Estados UnidosFil: Akwanalo, Constantine. Moi Teaching & Referral Hospital; KeniaFil: Asante, Kwaku Poku. Kintampo Health Research Centre; GhanaFil: Baumann, Ana. Washington University in St. Louis; Estados UnidosFil: Brown, Angela. Washington University in St. Louis; Estados UnidosFil: Davila Roman, Victor G.. Washington University in St. Louis; Estados UnidosFil: Dickhaus, Julia. New York University Grossman School of Medicine; Estados UnidosFil: Fort, Meredith. Colorado School Of Public Health; Estados UnidosFil: Iwelunmor, Juliet. Saint Louis University; Estados UnidosFil: Irazola, Vilma. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Mohan, Sailesh. Centre For Chronic Disease Control; India. Public Health Foundation Of India; IndiaFil: Mutabazi, Vincent. Regional Alliance For Sustainable Development; RuandaFil: Newsome, Brad. Center for Translation Research and Implementation Science; Estados UnidosFil: Ogedegbe, Olugbenga. New York University Grossman School of Medicine; Estados UnidosFil: Pastakia, Sonak D.. Purdue University College Of Pharmacy; Estados UnidosFil: Peprah, Emmanuel K.. University of New York; Estados UnidosFil: Plange Rhule, Jacob. Ghana College Of Physicians And Surgeons; GhanaFil: Roth, Gregory. University of Washington; Estados UnidosFil: Shrestha, Archana. Kathmandu University School Of Medical Sciences; NepalFil: Watkins, David A.. University of Washington; Estados UnidosFil: Vedanthan, Rajesh. New York University Grossman School of Medicine; Estados Unido

Selecting sites to prove the concept of IAR4D in the Lake Kivu Pilot Learning Site

Selecting sites is an essential step in enabling the assessment of the impact of Integrated Agricultural Research for Development (IAR4D) in the Lake Kivu Pilot Learning Site. This paper reports on the process of identifying distinct administrative territories (sites) in which to establish innovation platforms and to monitor similar communities that are experiencing alternative agricultural research for development interventions. We show how the research design for the Sub- Saharan Africa Challenge Programme (SSACP) has been modified to take into account the key conditioning factors of the LKPLS without relinquishing robustness. A key change is the explicit incorporation of accessibility to multiple markets. Candidate sites were stratified according to the national political context, followed by good and poor accessibility to markets and finally according to security considerations and agro-ecology. Randomisation was carried out at all levels, although the need for paired counterfactual sites required the diagnosis of conditioning factors at the site level. Potential sites were characterised in terms of existing or recent agricultural research initiatives, as well as local factors that would have a direct effect on the success of interventions seeking to improve productivity, ameliorate the degradation of natural resources and enhance incomes through better links to markets. Fourteen sites were selected during the initial phase, and a further ten sites were added one year afterwards due to the need for more innovation platforms to test IAR4D. The site selection was successful in pairing action and counterfactual sites in terms of the baseline socioeconomic conditions of farming households. The unavoidable proximity of action and counterfactual sites, however, allows the possibility of spill-over effects and could reduce the measurable impact of IAR4D