Building sustainable societies through vertical soilless farming: A cost-effectiveness analysis on a small-scale non-greenhouse hydroponic system

This research article was published by Elsevier in 2022The growing rate of population and urbanization among African cities versus the reducing arable land has roused curiosity in soilless farming as an urban farming method to enhance food security and urban sustainability. This study investigated the economic viability of producing 60 heads of lettuce using a vertical non-circulating hydroponic system outside the green house as a low cost sustainable urban food production prospect for Africa. This was based on a hydroponic experiment set up in Uganda, East Africa 4 capital budgeting techniques were used for the analysis, that is; Net Present Value (NPV), Profitability index (PI), Internal Rate of Return (IRR) and Non-discounted Pay Back Period (NDPBP). A sensitivity and scenario analysis were adopted for risk analysis while regression analysis was considered for forecasting and modelling purposes. A discount rate of 10% was considered for the analysis based on the loan borrowing rate. The unit production cost equaled to 0.46$/head and sale price was estimated at 0.75/head. Initial costs deemed necessary for annual production were estimated at 171.1$. Results showed the following economic values: NPV (16.37$), IRR (12.57%), PI (1.1) and NDPBP (4,5) for annual crop production of 6 cycles. NPV was sensitive to changes in discount rate and unit price while revenue varied with a change in quantities sold and unit price as per the scenario analysis. A significant negative and positive linear relationship was found between unit price of lettuce versus quantity sold and revenue earned correspondingly. Adoption of vertical hydroponic lettuce production can be considered an equally cost-effective venture with substantial profits cetris paribus with the potential to increase food security and sustainability around urbanities. Further research needs to be done to assess the profitability of producing other vegetables using the same system across various seasons and cities

Stay visual inspection or go weighing? Insights from a value chain analysis for cooking banana in Uganda.

European UnionInternational Fund for Agricultural Developmen

Stay visual inspection or go weighing? Insights from a value chain analysis for cooking banana in Uganda.

Playwright: N/A Director: N/A Academic Year: 1994-1995https://scholarworks.sjsu.edu/production_images/2388/thumbnail.jp

Postharvest losses along the cooking banana, potato and cassava fresh value chains in Uganda

Policy makers and development practitioners are challenged by the paucity of reliable data on the extent of postharvest losses (PHL) for devising suitable policies and strategies for their reduction. This study estimates PHL at different stages of the cooking banana, potato and cassava fresh value chains in Uganda by using cross-sectional data. A distinction was made between physical losses (product disappearing from the chain) and economic losses (partially deteriorated product sold at discounted price). Our findings indicate that the non-marketed output incurs very low physical losses (apart from potatoes, primarily during harvesting and storage) and, by definition, no economic losses. Conversely, substantial losses are found along the market chain. Physical losses affect about 30% of traded potatoes, followed by bananas (21%) and cassava (3%). However, the cassava value chain is characterized by much higher economic losses (about 47% of marketed roots sold at discount due to their rapid postharvest deterioration) than in the case of bananas and potatoes (10% and 8%, respectively). Overall, out of the total marketed output, 50% of cassava, 38% of potatoes and 30% of bananas incur either physical or economic losses. However, unlike banana and cassava that are mainly subsistence crops, potato in Uganda is primarily produced for the market. This results in a proportion of total potato production incurring PHL much higher (36%) than for banana and cassava (about 12%). Nevertheless, being its annual production enormous in the country, the quantity of bananas affected by PHL is about 7 and 25 times higher than the one of cassava and potato, respectively. Banana and cassava retailers - primarily women - are the value chain actors incurring the highest losses while, for potato, wholesalers are the most affected. Our findings contribute to policy prioritization and show that a diverse set of interventions is required to tackle PHL

Essays on the coffee supply chain in Uganda

Doctor of PhilosophyDepartment of Agricultural EconomicsJason BergtoldCoffee is grown by many countries worldwide (Killeen & Harper, 2016). Africa contributes 12% to total world production (Wondemu, 2017). Uganda is the second largest producing country in Africa, after Ethiopia (Mwesigye & Nguyen, 2020). Coffee is a labor-intensive industry employing over 100 million people in 60 developing countries (Collinson et al., 2005). It has been particularly important to Uganda’s economy since 1961. It has employed over 12 million people (ICO, 2019) generating export revenues of US$492 million in 2018 (UCDA, 2018). The current annual value of export revenues from coffee exceeds US$17 billion (FAOSTAT, 2018), contributing to 1.5% of Uganda’s Gross Domestic Product (GDP) in 2019 (ICO, 2019). Uganda contributes over 31.24% of total coffee exports from Africa (FAOSTAT, 2018), placing it among the major coffee exporting countries in the world. Despite the paramount importance of coffee to Uganda’s economy, the industry still faces bottlenecks in the coffee supply chain that limit growth. The purpose of this dissertation is to examine and assess two primary bottlenecks in the Uganda’s coffee supply chain, productivity at the farm level and maintaining quality through the supply chain. The total area under coffee production in Uganda has increased over the past ten years with no substantial increase in productivity. Standard productivity measures that examine technical efficiency and productivity though are not able to \account for the age of coffee trees or plantations, which is a limiting factor in coffee productivity. Productivity assessments assume a homogeneous production frontier across farms, which may result in biased productivity estimates due to differences in age of trees on a plantation. The purpose of the first essay is to analyze coffee farm efficiency and productivity change over time accounting for the average age of trees on coffee plantations. Data for the study comes from the two main coffee producing countries in Africa: Uganda, and Ethiopia. Uganda is the primary study area, with Ethiopia being used for comparative purposes and to provide a foundation for generalization of research findings. World Bank data from the 2013/2014 and 2015/2016 growing seasons is used, comprising of 187 Ugandan and 606 Ethiopian farm households. Efficiency and productivity change are estimated using Data Envelopment Analysis (DEA) techniques to derive measures based on the Malmquist Index and its decomposition. This estimation is completed in two stages. In the first stage, technical efficiency scores are estimated separately using an unconditional DEA model and a conditional DEA model that accounts for differences in the average age of the coffee trees at the farm household level. The two indexes are compared to determine the impact of the age of the coffee tree on efficiency and productivity change. Finally, in the second stage, CMI scores are whitened and a nonparametric Kernel regression of land and labor on CMI is conducted to determine the impact of land and labor efficiency on productivity change. Estimating coffee farm productivity in the short run using unconditional scores results in biased productivity estimates and misleading conclusions. The average age of the coffee trees has a negative and statistically significant marginal effect on coffee farm productivity change in both Uganda and Ethiopia. As the trees get older, the efficient frontier retracts. This is important for development programs such as extension to identify the actual productivity loss due to managerial inefficiency. In addition, it provides evidence for the potential efficacy of coffee tree planting programs to help small famers. Increasing land input in coffee production decreases productivity due to thinning of other inputs, while increasing labor inputs improves productivity since this is a limiting factor in coffee production. The second essay analyzes coffee marketing channels and the current quality incentive structures to understand their impact on coffee quality through the coffee supply chain. This essay specifically considers two market channels through which exporters make transactions: the middleman market channel and the farmers’ group market channel. Data for this study comes from two main coffee producing districts in Uganda, Masaka and Mbale. Primary data were collected using pre-tested questionnaires. The data is comprised of interviews with 120 middlemen and 30 exporters, as well as four focus group discussions with producers. We use discrete choice methods based on actor decisions in the coffee supply chain to test for differences in quality of coffee transacted through the middlemen and farmers’ group channels. We apply the Principal-Agent framework to explain the impact of market channels on coffee bean quality. Results show a significant positive marginal effect of the market channel on coffee quality. If the market channel changes from middlemen to farmers’ group, the probability of the quality of coffee being high increases by 55 percentage points. The farmers’ group channel leads to high quality because of symmetric information between farmers, farmers’ groups, and exporters and availability of price incentives. The low quality through the middlemen channel is due to lack of incentives and information asymmetry between the farmers, middlemen and exporters. The government of Uganda can help improve coffee quality through promoting formation of farmers’ groups. This can be done through providing extension services to create awareness and infrastructural support to poorer and more remote farmers

Cooking banana marketing protocol (Runyankole).

This protocol is designed to support farmers to improve the quality of their bananas in the field and the postharvest practices in a bid to facilitate access to better prices and niche markets. The protocol is organized into three sections: Section 1 Good Agricultural Practices (GAP); Section 2: Proper Harvest and Handling Practices and Section 3: Good Marketing Practices (GMP)

Cooking banana marketing protocol (Luganda).

This protocol is designed to support farmers to improve the quality of their bananas in the field and the postharvest practices in a bid to facilitate access to better prices and niche markets. The protocol is organized into three sections: Section 1 Good Agricultural Practices (GAP); Section 2: Proper Harvest and Handling Practices and Section 3: Good Marketing Practices (GMP)