Assessment of variation in marginal productivity value of water in paddy farming systems in times of water stress

This research article was published in Water Journal, Volume 14, 2022.Global projections show that increases in agriculture water productivity (AWP) by 30 and 60% in rain-fed and irrigated agriculture, respectively, are required to ensure food security in the period 2000–2025. In sub-Saharan Africa, attempts to understand AWP has seen a lamping of input values which paints an unrealistic picture of AWP. We employed the residual imputation method to isolate the marginal productivity value of water in six paddy farming systems viz. the conventional transplant and flooding system (CTFS), the system of rice intensification (SRI), and the Kilombero Plantation Limited (KPL) mechanized system. Findings showed that AWP for rainfed CTFS is 0.39 kg/m3 or 0.003 US$/m3 , irrigated CTFS (0.30 kg/m3 or 0.002 US$/m3 ), rainfed SRI (0.68 kg/m3 or 0.08 US$/m3 ), irrigated SRI (0.52 kg/m3 or 0.06 US$/m3 ), rainfed KPL (0.33 kg/m3 or 0.05 US$/m3 ), and irrigated KPL (0.68 kg/m3 or 0.11 US$/m3 ). This shows that rainfed systems have good AWP, especially physical ones. We recommend a rollout of rainfed SRI to secure local food security and downstream ecosystem services. In addition, groupings of farmers will assist in optimizing resources, stabilizing markets, and prices for the better economic value of water (US$/m3 ). Adoption of SRI will require intensive demonstration that needs public financing. In addition, revamping the KPL off-taker arrangement with small-holder farmers could also be a good PPP anchor

Determinants of Consumer Preference for and Expenditure on Rice in the Kilimanjaro Region, Tanzania

The primary objective of the study was to examine determinants of consumer preferences for and expenditure on rice in the Kilimanjaro Region, Tanzania. Data were collected from a random sample of 230 participants, and analyzed using descriptive statistics and regression analyses. The descriptive statistics revealed that domestic rice was preferred by a majority of the participants over imported rice. The most important attribute for consumers was aroma, followed by taste, cleanness, and price. The logistic regression analysis showed that price of a substitute, quality, and household size had significant effects on preference for rice, domestic or imported. The OLS analysis revealed that the price of rice, income, frequency of consumption, and household size had significant effects on expenditure on rice. It is suggested that domestic rice should be promoted, and influential factors should be considered in any consumption and policy changes in the rice industry

Global soybean trade - the geopolitics of a bean

Following a collaborative effort and with the support of The UK Research and Innovation Global Challenges Research Fund (UKRI GCRF), the Trade, Development and the Environment Hub -- or simply Trade Hub, https://tradehub.earth/ -- has recently launched the report “Global Soybean Trade – The Geopolitics of a Bean”. Originally cultivated as a traditional staple food in China, soybean today is of the most important global commodities in international trade. The report examines the economics of the ‘soybean miracle’, exploring its complex – and often controversial – implications for people and ecosystems, and analysing how different institutions and stakeholders are addressing the growing sustainability concerns. This publication not only provide a comprehensive review of the existing publications and data, but also highlights some of the open questions that need to be addressed by Trade Hub partners and other stakeholders in order to increase the sustainability of the soybean supply chain, both globally and locally

Revisiting the Solow-Swan model of income convergence in the context of coffee producing and re-exporting countries in the world

The purpose of this paper is to investigate the Solow-Swan’s proposition that poorer countries grow faster than richer countries causing declining income disparities across countries. The role of coffee trade in income convergence is also analyzed to enrich our understanding of whether traditional cash export crops, like coffee, contribute significantly to income convergence. We found that, GDP per capita was growing faster among coffee producers than coffee re-exporters, supporting the Solow-Swan’s model. However, coffee export values and shares decreased with convergence for green coffee producers while increasing among re-exporters, implying unequal distribution of benefits along the global coffee value chain

Decomposition of GDP per capita inequality among EAC member countries, 2015–2018.

Decomposition of GDP per capita inequality among EAC member countries, 2015–2018.</p

Diagnostic study on performance of participatory farmer groups (PFGS) model for banana – coffee cropping system in the DASIP supported areas

Agriculture occupies a very important role in the lives of Tanzanians as well the national economy. It employs about 75 percent of the population and it accounts for 95 percent of the food consumed in the country (Ministry of Agriculture Food Security and Cooperatives - MAFS, 2012). In spite of the fact that agriculture is an important sector and the backbone of the national economy in Tanzania, it has failed to improve the livelihood of the rural people whose major occupation is agriculture. 1 Low productivity; under-utilization of the available land, water and human resources as well as low incomes and profitability due to poor agricultural practices, have remained the key features of agriculture in the country. Some of the key challenges include the lack of access to support services, continued dependence on rain fed agriculture, poor rural infrastructure, limited capital and access to financial services, lack of investment incentives in agriculture, weak producer organizations and institutional constraints (ibid). In an attempt to address these challenges, the Government of Tanzania (GoT), through a loan and grant from the African Development Bank (AfDB) is implementing a six year project namely: the District Agricultural Sector Investment Project (DASIP) starting from January, 2006. The overall aim of this project is to increase productivity and incomes of rural households in the project area within the overall framework of the Agricultural Sector Development Strategy (ASDP). DASIP is implemented in 28 rural districts in Kagera, Kigoma, Mara, Mwanza and Shinyanga regions. The Project has three field components and one project management component namely project coordination. The first field component deals with building the capacity of the project districts to train Participatory Farmer Groups (PFGs) through participatory adult education methods. The PFG members are trained in technical, organizational and management of their enterprises. The Terms of Reference (ToR) for the consultancy indicate that, about 11,000 PFGs will be formed by the end of the project life with each group constituting 25 members on average. The second field component deals with issues related to community planning and investment in agriculture. It aims at building capacity of project districts to plan, manage and monitor village and district agricultural development plans. In 28 project districts and 780 villages the projects supports the preparation and implementation of the District Agricultural Development Plans (DADPs) and Village Agricultural Development Plans (VADPs) respectively. The project supports 1,951 agriculture-related investments such as; constructions of cattle dip tanks, agricultural technologies; storage facilities, market places, market access infrastructure and water harvesting structures for livestock and irrigation of crops. The third field component deals with supports related to rural micro-finance and marketing. Specifically, the component aims at strengthening about 84 Savings and Credit Co-operatives Societies (SACCOS) in all the project districts. It is anticipated that, by the end of the project, 90 percent of target SACCOS will be able to maintain a repayment rate of 95 percent and more than 60 percent of SACCOS will be linked with agro processing facilities and marketing associations. Under this component, the project is also expected to establish a well functioning marketing system that will serve farmers in all the project districts. The project coordination component deals with the day-to-day co-ordination and management of project activities. The Project Coordination Unit (PCU) which is based in Mwanza is responsible for coordinating Project activities and ensuring all project resources are managed prudently. Few issues need to be underlined concerning the overall performance of the project. Firstly, the project has trained a total of 11,150 PFGs on improved agronomy practices, business plans, mini projects and later supported them with mini-grants however; the performance of PFGs obtaining training and mini-grants varies among PFGs. It is important that a comprehensive assessment of reasons behind variations be done in order to inform the process of successful attainment of the project objectives and sustainability. Secondly, the project through its Community Planning and Investment in Agriculture component, has to date funded a total of 1,951 micro-projects and agricultural technologies with 1,229 being infrastructure projects and 722 agricultural technology projects. While it was anticipated that all the completed projects or infrastructures would be utilized by the communities; only sixty percent are utilized. There are various factors that may have influenced or hindered the utilization of these infrastructures by communities and it is also important that these factors are studied. Variations were also observed among PFGs and target communities at large in terms of crop yield and livestock productivity, incomes, access to extension services, training, adoption of improved farming practices, use of farm implements, PFG membership and management of PFGs and community projects. Yet, the reasons behind these variations are not known with certainty.District Agricultural Sector Investment Projec

Data used in the analysis of average annual GDP (at purchaser prices).

(XLSX)</p

Supplementary table showing the results of regression models.

(DOCX)</p

Imports of goods and services for EAC member countries, South Sudan excluded.

Source: World Bank’s meta-data of development indicators (https://data.worldbank.org/country/).</p

List of value adding activities and trade regression models.

List of value adding activities and trade regression models.</p