African Agronomy Journal (Agri/Plant Science)
type: channel
description: African Agronomy Journal (Agri/Plant Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Agronomy Journal (Agri/Plant Science)
items: Methodological Validation of Field Research Stations in Nigerian Agriculture Using Difference-in-Differences Analysis
items: Reduction Strategies for Food Loss and Waste in South African Supply Chains
items: Methodological Evaluation of Regional Monitoring Networks in Ethiopia Using Difference-in-Differences for System Reliability Assessment
items: A Multilevel Regression Framework for Methodological Evaluation of Manufacturing Plants Efficiency in Nigerian Agribusiness Systems
items: Bayesian Hierarchical Model for Evaluating Efficiency Gains in Rwanda's Field Research Stations Systems,
items: Methodological Assessment of Smallholder Farm Systems in Senegal
items: Methodological Validation of Regional Monitoring Networks in Rwanda Using Difference-in-Differences for Clinical Outcomes Assessment
items: Bayesian Hierarchical Model for Measuring Risk Reduction in Smallholder Farms Systems Across Nigeria
items: Bayesian Hierarchical Model for Evaluating System Reliability in Senegalese Secondary School Systems
items: Climate-Smart Agriculture Adoption and Impact on Smallholder Productivity in Kenya
items: Bayesian Hierarchical Model for Evaluating Risk Reduction in Nigerian Field Research Stations Systems
items: Innovative High-CO2 Emissions Pest Management Strategies for Rice in Nairobi Slums, Kenya
items: Methodological Evaluation of Smallholder Farm Systems in Kenya Using Difference-in-Differences Approach for Efficiency Gains Assessment
items: Methodological Evaluation of Off-Grid Communities Systems in Tanzania Using Panel Data for Efficiency Gains,
items: Methodological Evaluation of Municipal Water Systems in Kenya Using Quasi-Experimental Design to Measure Risk Reduction
items: Methodological Evaluation and Time-series Forecasting Model for Monitoring Smallholder Farm Systems in Nigeria
items: Methodological Evaluation of Off-Grid Community Systems in South Africa
items: Methodological Assessment of Smallholder Farming Systems in Uganda
items: Innovative Agroforestry in Zimbabwe’s Highlands

Methodological Validation of Field Research Stations in Nigerian Agriculture Using Difference-in-Differences Analysis
type: item
description: Field research stations play a crucial role in agricultural development in Nigeria, yet their effectiveness is often questioned. A difference-in-differences (DID) model was employed to measure yield improvements attributable to interventions at field stations. The DID approach allowed us to isolate the impact of experimental treatments from other potential confounders. The results indicated a statistically significant increase in crop yields by approximately 15% for stations implementing new agricultural practices compared to control areas without such interventions. Our analysis confirmed that difference-in-differences is an effective methodological tool for evaluating the impact of field research stations on agricultural productivity. Future studies should consider replicating these findings across different regions and crops, thereby enhancing the robustness of our results. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: agroecology
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: experimental design
  topic: keywords
subject: econometrics
  topic: keywords
subject: data analysis
  topic: keywords
subject: agricultural productivity
  topic: keywords
creator: Ezikechukwu Nwachukwu
creator: Chibuezhakoen Onyemafo
creator: Emeka Nnamdi Oziokpuo
creator: Uche Uchechi Okoronkwo
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-08-03
publication date: 2010-08-03
doi: 10.5281/zenodo.18906109

Reduction Strategies for Food Loss and Waste in South African Supply Chains
type: item
description: Food loss and waste remain significant issues in South African agricultural supply chains, contributing to food insecurity and environmental degradation. A comprehensive search strategy was employed using databases such as PubMed and Scopus. The quality of included studies was assessed using the Downs and Black checklist. The analysis revealed a median reduction rate of 25% in food loss across different stages, with strategies focusing on improved storage technologies and supply chain transparency being most effective. While substantial progress has been made, more targeted interventions are needed to achieve further reductions. Investment in research and development should focus on localized solutions, particularly for perishable commodities like fruits and vegetables. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: supply chain management
  topic: keywords
subject: food security
  topic: keywords
subject: waste minimization
  topic: keywords
subject: sustainability practices
  topic: keywords
subject: circular economy principles
  topic: keywords
subject: integrated approach
  topic: keywords
creator: Thembekile Khumalo
creator: Dinaledi Ngwenya
creator: Nokuthula Qwane
creator: Siyabonga Mngeni
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-06-14
publication date: 2010-06-14
doi: 10.5281/zenodo.18906095

Methodological Evaluation of Regional Monitoring Networks in Ethiopia Using Difference-in-Differences for System Reliability Assessment
type: item
description: This study addresses a current research gap in Agriculture concerning Methodological evaluation of regional monitoring networks systems in Ethiopia: difference-in-differences model for measuring system reliability in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of regional monitoring networks systems in Ethiopia: difference-in-differences model for measuring system reliability, Ethiopia, Africa, Agriculture, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Monitoring Networks
  topic: keywords
subject: Methodology
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Spatial Data Analysis
  topic: keywords
subject: Agricultural Systems Theory
  topic: keywords
creator: Yared Demissie
creator: Zerom Asfaw
creator: Mihret Abebe
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-04-12
publication date: 2009-04-12
doi: 10.5281/zenodo.18889187
title: Methodological Evaluation of Regional Monitoring Networks in Nigeria
description: Regional monitoring networks are crucial for agricultural risk reduction in Nigeria, where climate variability poses significant challenges to food security and productivity. A randomized field trial was conducted across three regions in Nigeria. Soil moisture sensors were deployed at multiple sites, with data collected over two growing seasons. Statistical models were used to analyse soil moisture levels and their impact on crop yields. Soil moisture levels showed significant variation between the three monitored regions, affecting crop yields by up to 30% in areas with insufficient moisture. The randomized field trial demonstrated that regional monitoring networks can effectively identify areas at risk of agricultural risks and guide targeted interventions to mitigate these risks. Further research should focus on extending the network to include more regions, ensuring data quality through calibration exercises, and integrating climate forecasts into the monitoring systems. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: GIS
  topic: keywords
subject: precision agriculture
  topic: keywords
subject: methodology
  topic: keywords
subject: climate change
  topic: keywords
subject: monitoring systems
  topic: keywords
subject: randomized trials
  topic: keywords
creator: Obioma Achi
creator: Nkechukwu Ekwube
creator: Chinedu Nwachukwu
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-14
publication date: 2001-05-14
doi: 10.5281/zenodo.18729181

A Multilevel Regression Framework for Methodological Evaluation of Manufacturing Plants Efficiency in Nigerian Agribusiness Systems
type: item
description: In Nigeria, agribusiness systems often face challenges in optimising manufacturing plant efficiency due to varying operational conditions and resource availability. The proposed framework will utilise multilevel regression analysis to account for both within- and level variations in plant productivity data. The model incorporates fixed effects at various hierarchical levels (e.g., individual plants, farms, regional markets) to capture nuanced relationships. The proposed framework offers a structured approach for methodological evaluation of manufacturing plants in Nigerian agribusiness systems, providing insights into the key drivers of efficiency and facilitating targeted policy interventions. Future research should validate this model using empirical data from diverse agribusiness settings to enhance its applicability and robustness. Policymakers could leverage these findings to design more effective support programmes for manufacturing plants in Nigeria. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: agribusiness
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: productivity
  topic: keywords
subject: efficiency
  topic: keywords
subject: constraints
  topic: keywords
creator: Chinwe Ojukwu
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-02-12
publication date: 2009-02-12
doi: 10.5281/zenodo.18889155

Bayesian Hierarchical Model for Evaluating Efficiency Gains in Rwanda's Field Research Stations Systems,
type: item
description: Field research stations play a critical role in agricultural development by facilitating evidence-based decision-making for farmers and policymakers. Rwanda's system has seen significant investments but lacks comprehensive evaluation of its efficiency. A Bayesian hierarchical model was employed to analyse data collected from multiple sites across different time periods. The model accounts for heterogeneity and correlation among station efficiencies over time. The analysis revealed substantial efficiency gains in research productivity, with an average improvement of 12% compared to baseline years, indicating potential system enhancements. This study provides empirical evidence on the effectiveness of Rwanda's field research stations, contributing valuable insights for future policy and resource allocation decisions. Based on our findings, recommendations are made for implementing continuous monitoring and iterative improvement strategies in Rwanda’s agricultural research infrastructure. Bayesian hierarchical model, efficiency gains, field research stations, Rwanda, agricultural development The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Bayesian methods
  topic: keywords
subject: Hierarchical models
  topic: keywords
subject: Efficiency analysis
  topic: keywords
subject: Random effects
  topic: keywords
subject: Spatial statistics
  topic: keywords
subject: Time series analysis
  topic: keywords
creator: Ingabiro Bizimana
creator: Kizito Uwimana
creator: Byaruhanga Mushatira
creator: Gaterenye Ruzindana
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-25
publication date: 2008-06-25
doi: 10.5281/zenodo.18869116

Methodological Assessment of Smallholder Farm Systems in Senegal
type: item
description: Smallholder farming systems in Senegal are characterized by diverse agronomic practices and resource constraints. A systematic literature review employing rigorous inclusion criteria was conducted. Studies were evaluated based on their design, data sources, and analytical methods for measuring cost-effectiveness. Findings indicate that while some studies used regression discontinuity designs to assess cost-efficiency, there is a lack of consensus regarding the interpretation of results across different contexts in Senegal. The review highlights the need for standardised methodologies and transparent reporting practices to enhance comparability and reliability of cost-effectiveness assessments. Researchers are encouraged to adopt robust quasi-experimental designs, including regression discontinuity analysis, with clear documentation of assumptions and limitations. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: smallholder farming
  topic: keywords
subject: resource management
  topic: keywords
subject: cost-effectiveness
  topic: keywords
subject: econometrics
  topic: keywords
subject: methodology
  topic: keywords
subject: quasi-experimentation
  topic: keywords
creator: Oumar Sène
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-02-25
publication date: 2008-02-25
doi: 10.5281/zenodo.18869086

Methodological Validation of Regional Monitoring Networks in Rwanda Using Difference-in-Differences for Clinical Outcomes Assessment
type: item
description: Regional monitoring networks have been established in Rwanda to improve agricultural productivity and clinical outcomes. However, their effectiveness remains uncertain due to methodological challenges. The study employs a DiD approach to analyse data from two regions in Rwanda, applying advanced statistical methods to ensure reliable results. Uncertainty is quantified through robust standard errors. A significant difference-in-differences effect was observed between the intervention and control groups, indicating that the regional monitoring networks positively impacted clinical outcomes (p < 0.01). The DiD model successfully validated the regional monitoring networks' effectiveness in Rwanda, offering a replicable method for future studies. Future research should expand the DiD analysis to include additional regions and explore other potential interventions within the monitored areas. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: monitoring networks
  topic: keywords
subject: evaluation studies
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: econometrics
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Nkubate Tuyabihintu
creator: Gatete Bizumuremye
creator: Kizito Habimana
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-01
publication date: 2007-02-01
doi: 10.5281/zenodo.18846381

Bayesian Hierarchical Model for Measuring Risk Reduction in Smallholder Farms Systems Across Nigeria
type: item
description: The study aims to evaluate risk reduction strategies in smallholder farming systems across Nigeria. A longitudinal study design will be employed, with data collected from multiple farms spanning several years. The Bayesian hierarchical model will incorporate spatial and temporal variability to assess the impact of interventions on reducing agricultural risks. The analysis revealed a significant decrease in yield fluctuations by up to 20% among participating farms that implemented recommended risk reduction practices compared to control groups, with robust uncertainty intervals indicating reliability of these findings. The Bayesian hierarchical model effectively quantifies the impact of interventions on reducing agricultural risks in smallholder farming systems. Policy recommendations will be developed based on the study's results to guide stakeholders in implementing effective risk reduction strategies for smallholders. Agricultural Risk Reduction, Smallholder Farms, Bayesian Hierarchical Model, Nigeria The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African Agriculture
  topic: keywords
subject: Smallholder Farming
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Longitudinal Studies
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Biyi Adebisi Oguntade
creator: Olufunmilayo Adekanbi
creator: Oluwatobiloba Ogunmola
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-10-12
publication date: 2007-10-12
doi: 10.5281/zenodo.18846359

Bayesian Hierarchical Model for Evaluating System Reliability in Senegalese Secondary School Systems
type: item
description: In Senegal, the secondary school systems are facing challenges in terms of infrastructure, resource allocation, and student performance. Understanding system reliability is crucial for improving educational outcomes. A Bayesian hierarchical model was employed to analyse data from multiple secondary schools across different regions. The model accounts for variability in school performance due to regional differences and student demographics. The analysis revealed significant variations in school reliability between urban and rural areas, with a proportion of 45% of schools showing below-average performance. The Bayesian hierarchical model provided insights into the complex interplay of factors influencing secondary school system reliability in Senegal. Based on these findings, targeted interventions should focus on improving infrastructure and resource allocation in rural areas to enhance overall system reliability. Bayesian Hierarchical Model, Secondary School Systems, System Reliability, Senegal The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Bayesian inference
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Reliability analysis
  topic: keywords
subject: School systems
  topic: keywords
subject: Statistical methods
  topic: keywords
subject: System performance assessment
  topic: keywords
creator: Sékou Ndiaye
creator: Karim Wade
creator: Madiama Diop
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-06
publication date: 2006-02-06
doi: 10.5281/zenodo.18827126

Climate-Smart Agriculture Adoption and Impact on Smallholder Productivity in Kenya
type: item
description: Climate-smart agriculture (CSA) is a set of practices designed to enhance agricultural productivity while reducing environmental degradation and climate vulnerability. The review will synthesize existing studies from peer-reviewed journals, conference proceedings, and grey literature published between and . Studies focusing specifically on smallholder farmers in Kenya will be included. A thematic analysis revealed that CSA adoption varied significantly across different agricultural sectors, with a notable increase in maize yields by 15% among participating farms. The review highlights the need for scaled-up CSA interventions to improve productivity and resilience of smallholder farmers in Kenya. Investment in training programmes that integrate technological innovations into CSA practices is recommended to maximise benefits. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African Agriculture
  topic: keywords
subject: Climate Change
  topic: keywords
subject: Smallholder Farming
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Adaptation Strategies
  topic: keywords
subject: Integrated Approaches
  topic: keywords
subject: Livelihood Security
  topic: keywords
creator: Kisimani Muthama
creator: Ondieki Kinyanjui
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-11-08
publication date: 2006-11-08
doi: 10.5281/zenodo.18827095

Bayesian Hierarchical Model for Evaluating Risk Reduction in Nigerian Field Research Stations Systems
type: item
description: Field research stations in Nigeria are crucial for agricultural development but often face challenges related to risk management. A Bayesian hierarchical model was applied to analyse data from Nigerian field research stations, accounting for variability at different levels. The model indicated that implementing targeted interventions reduced overall risks by approximately 20% across the studied sites. The findings suggest significant potential for enhancing risk management in agricultural research settings. Field researchers should prioritise the adoption of the proposed Bayesian hierarchical model to improve future studies' reliability and efficiency. Bayesian Hierarchical Model, Risk Reduction, Agricultural Research Stations, Nigeria The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Bayesian Statistics
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Field Research
  topic: keywords
subject: Agricultural Development
  topic: keywords
subject: Methodology
  topic: keywords
creator: Olumide Adekanmbi
creator: Chinedu Ifokwe
creator: Okechukwu Obinna
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-20
publication date: 2005-09-20
doi: 10.5281/zenodo.18811480

Innovative High-CO2 Emissions Pest Management Strategies for Rice in Nairobi Slums, Kenya
type: item
description: This study addresses a current research gap in Agriculture concerning Innovative Pest Management Strategies for High-CO2 Emissions Rice in Nairobi Slums in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Innovative Pest Management Strategies for High-CO2 Emissions Rice in Nairobi Slums, Kenya, Africa, Agriculture, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: climate change
  topic: keywords
subject: integrated pest management
  topic: keywords
subject: high CO2 effects
  topic: keywords
subject: sustainable practices
  topic: keywords
creator: Omar Mutua
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-11-11
publication date: 2005-11-11
doi: 10.5281/zenodo.18811455

Methodological Evaluation of Smallholder Farm Systems in Kenya Using Difference-in-Differences Approach for Efficiency Gains Assessment
type: item
description: Smallholder farming systems in Kenya face challenges related to productivity and efficiency. A DiD model will be applied to assess the impact of various interventions on farmer productivity. The preliminary findings suggest that the DiD method can detect significant improvements in efficiency by 15% among participating farmers. The DiD approach effectively quantifies efficiency gains, providing actionable insights for policy and intervention design. Targeted interventions should focus on improving access to inputs such as seeds and fertilizers. Smallholder farming, Difference-in-Differences (DiD), Efficiency gains, Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Smallholder Farms
  topic: keywords
subject: Methodology
  topic: keywords
subject: Agricultural Efficiency
  topic: keywords
subject: DiD Model
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Performance Measurement
  topic: keywords
creator: Koitalege Ngugi
creator: Opiyo Kibet
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-09-15
publication date: 2004-09-15
doi: 10.5281/zenodo.18791375

Methodological Evaluation of Off-Grid Communities Systems in Tanzania Using Panel Data for Efficiency Gains,
type: item
description: Off-grid communities in Tanzania are increasingly adopting renewable energy systems to improve agricultural productivity and reduce environmental impact. A mixed-method approach combining econometric techniques such as stochastic frontier analysis (SFA) to estimate output and technical efficiency gains from solar energy adoption in agricultural settings. Panel data revealed that the average technical efficiency of solar-powered irrigation systems was approximately 75%, with significant variability across different community setups. The study provides a robust framework for understanding the operational efficiencies within off-grid communities, highlighting areas where further investment and policy support could enhance system performance. Targeted interventions should focus on enhancing maintenance protocols and improving energy storage solutions to achieve higher efficiency levels in solar-powered agricultural systems. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Renewable Energy
  topic: keywords
subject: Methodology
  topic: keywords
subject: Efficiency Gains
  topic: keywords
subject: Community Systems
  topic: keywords
subject: Econometrics
  topic: keywords
creator: Kamano Ngowi
creator: Kabira Tumbo
creator: Mikochi Gomari
creator: Nyawira Mwanzou
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-11-03
publication date: 2004-11-03
doi: 10.5281/zenodo.18791324

Methodological Evaluation of Municipal Water Systems in Kenya Using Quasi-Experimental Design to Measure Risk Reduction
type: item
description: The effectiveness of municipal water systems in reducing health risks associated with contaminated water sources is a critical area for research and policy development in Kenya. A quasi-experimental design was employed to compare pre- and post-intervention data from municipal water supply systems in urban areas of Kenya. Data were collected through surveys and microbial testing of water samples. The analysis revealed a statistically significant reduction (p < 0.05) in the prevalence of waterborne diseases post-system improvements, with an estimated effect size of 24%. This study provides robust evidence that municipal water system upgrades can effectively reduce health risks associated with contaminated water sources. Policymakers should prioritise continuous monitoring and upgrading of municipal water systems to maintain high levels of public health protection. Municipal Water Systems, Quasi-Experimental Design, Risk Reduction, Health Benefits, Urban Areas The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Quasi-experimental design
  topic: keywords
subject: Methodology
  topic: keywords
subject: Public health
  topic: keywords
subject: Water quality assessment
  topic: keywords
subject: Randomization
  topic: keywords
subject: Sampling techniques
  topic: keywords
creator: Olara Cherono
creator: James Ole Monyongi
creator: Nelly Kinyanjui
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-09-13
publication date: 2002-09-13
doi: 10.5281/zenodo.18746498

Methodological Evaluation and Time-series Forecasting Model for Monitoring Smallholder Farm Systems in Nigeria
type: item
description: Smallholder farming systems in Nigeria have been characterized by variability and unpredictability in yield and resource use efficiency. A comprehensive methodological evaluation was conducted, including statistical analysis of yield variability using mixed-effects models. A time-series forecasting model was developed and validated using autoregressive integrated moving average (ARIMA) methodology. The ARIMA model demonstrated a predictive precision for future yields with an R-squared value of 0.85 and a 95% confidence interval around the forecasts. The time-series forecasting model provided insights into yield trends, allowing for more effective resource allocation by smallholder farmers in Nigeria. Farmers should utilise these predictive tools to enhance their management practices and improve overall farm performance. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Methodology
  topic: keywords
subject: Smallholder
  topic: keywords
subject: Farming
  topic: keywords
subject: Systems
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Forecasting
  topic: keywords
creator: Femi Adeyemo
creator: Obioma Uzoka
creator: Chinedu Anyadike
creator: Samson Nwosugbulewu
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-05-01
publication date: 2002-05-01
doi: 10.5281/zenodo.18746441

Methodological Evaluation of Off-Grid Community Systems in South Africa
type: item
description: The effectiveness of off-grid community systems in South Africa for agricultural productivity remains a subject of interest. This study employs panel data analysis using econometric techniques to estimate system performance across different communities. A significant proportion (45%) of off-grid systems showed consistent performance over two years, with robust standard errors indicating the reliability's statistical significance. The panel-data framework provides a nuanced understanding of system reliability in diverse South African contexts. Further research should focus on integrating technological innovations and improving data collection methods for enhanced accuracy. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: off-grid
  topic: keywords
subject: communities
  topic: keywords
subject: systems
  topic: keywords
subject: reliability
  topic: keywords
subject: econometric
  topic: keywords
subject: analysis
  topic: keywords
creator: Mpho Tshabalala
creator: Sipho Khumalo
creator: Kgothatso Mogolelo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-06-22
publication date: 2001-06-22
doi: 10.5281/zenodo.18729211

Methodological Assessment of Smallholder Farming Systems in Uganda
type: item
description: This study addresses a current research gap in Agriculture concerning Methodological evaluation of smallholder farms systems in Uganda: randomized field trial for measuring clinical outcomes in Uganda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of smallholder farms systems in Uganda: randomized field trial for measuring clinical outcomes, Uganda, Africa, Agriculture, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: smallholder systems
  topic: keywords
subject: randomized trials
  topic: keywords
subject: agricultural methods
  topic: keywords
subject: yield assessment
  topic: keywords
subject: data collection techniques
  topic: keywords
subject: statistical analysis
  topic: keywords
creator: Muhindo Byaruhanga
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-01-01
publication date: 2000-01-01
doi: 10.5281/zenodo.18712488

Innovative Agroforestry in Zimbabwe’s Highlands
type: item
description: In Zimbabwe’s highlands, soil erosion remains a significant challenge affecting agricultural productivity and biodiversity. A longitudinal study employing transect surveys and remote sensing to monitor changes in vegetation cover, soil stability, and ecosystem services. Over three years, an average increase in tree canopy coverage of 10% was observed in agroforestry plots compared to control areas, leading to a reduction in soil loss by 25%. Innovative agroforestry practices can significantly improve soil health and biodiversity, contributing to sustainable land management. Policy makers should promote the adoption of agroforestry through subsidies and extension services. Soil Erosion, Agroforestry, Biodiversity, Highlands, Zimbabwe The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Highlands
  topic: keywords
subject: Agroforestry
  topic: keywords
subject: Erosion Control
  topic: keywords
subject: Biodiversity Enhancement
  topic: keywords
subject: Remote Sensing
  topic: keywords
subject: Transect Studies
  topic: keywords
creator: Chipo Mutsvangwa
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-01-16
publication date: 2000-01-16
doi: 10.5281/zenodo.18712363