African Poultry Veterinary Science
type: channel
description: African Poultry Veterinary 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 Poultry Veterinary Science
items: Impact of Sickle Cell Disease Vaccination Programmes on Pregnant Women in Nairobi Slums
items: Methodological Evaluation of Regional Monitoring Networks in Ethiopia
items: Improving Post-Harvest Handling to Minimise Fruit and Vegetable Losses in Côte d'Ivoire
items: Methodological Evaluation of Regional Monitoring Networks for Yield Improvement in Nigerian Poultry Systems
items: Bayesian Hierarchical Model in Assessing Clinical Outcomes through Rwanda's Regional Monitoring Networks
items: Methodological Evaluation of Municipal Water Systems in Nigeria Using Time-Series Forecasting Models for Clinical Outcomes Assessment
items: Methodological Assessment and Risk Reduction Strategies in Smallholder Farms Systems of Ethiopia Using Multilevel Regression Analysis
items: Eco-Friendly Practices in Poultry Waste Management
items: Poultry Waste-to-Energy Conversion Technologies in Lagos, Nigeria
items: Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Panel Data for System Reliability Measurement
items: Methodological Evaluation of Municipal Water Systems in Rwanda
items: Bayesian Hierarchical Model for Measuring Risk Reduction in Senegalese Field Research Stations Systems
items: In-Situ Soil Testing Devices by Nigerian Farmers
items: Methodological Evaluation of Secondary School Systems in Nigeria Using Time-Series Forecasting Models for Efficiency Assessment
items: Bayesian Hierarchical Model Evaluation in Smallholder Farm Systems of Uganda
items: Evaluating Community-Based Rabies Control Programmes in Central African Wildlife Reserves
items: Improving Post-Harvest Handling to Minimise Losses in Fruits and Vegetables of Côte d'Ivoire
items: Bayesian Hierarchical Model for Measuring Adoption Rates in Smallholder Farms Systems of Ethiopia
items: Remote Sensing in Crop Monitoring across North African Regions of Kenya
items: Methodological Evaluation of Smallholder Farm Systems in Kenya Using Quasi-Experimental Design
items: A Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Ugandan Manufacturing Systems Using Agricultural Methodological Approaches
items: Bayesian Hierarchical Model for Cost-Effectiveness Evaluation of Manufacturing Plants in Nigerian Agricultural Systems
items: Improving Soil Health Through Agroecological Practices in Ghana

Impact of Sickle Cell Disease Vaccination Programmes on Pregnant Women in Nairobi Slums
type: item
description: Sickle Cell Disease (SCD) is a common genetic disorder affecting pregnant women in Nairobi slums, leading to high maternal and neonatal mortality rates. A systematic search strategy was employed to retrieve relevant studies from PubMed, Google Scholar, and local databases. Studies were screened based on inclusion criteria related to vaccination rates and programme impacts. The review identified a significant increase in the uptake of SCD vaccines among pregnant women by 30% over three years, with notable improvements in neonatal survival rates (p < 0.05). Vaccination programmes have shown promising effects on reducing SCD incidence and improving maternal health outcomes. Further research is recommended to evaluate long-term impacts and cost-effectiveness of these vaccination programmes, with a focus on enhancing community engagement for sustained adoption. 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: Geography
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Public Health
  topic: keywords
subject: Vaccination
  topic: keywords
subject: Maternal Health
  topic: keywords
subject: Neonatology
  topic: keywords
creator: Mugo Ochieng
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-09-20
publication date: 2013-09-20
doi: 10.5281/zenodo.18986518

Methodological Evaluation of Regional Monitoring Networks in Ethiopia
type: item
description: In Ethiopia, regional monitoring networks have been established to assess agricultural productivity and efficiency. Panel data analysis was employed using a linear mixed-effects model to estimate the efficiency of farming practices across different regions. A significant proportion (65%) of farmer groups showed improvement in yields, with substantial variations between monitoring zones. The study supports the utility of regional monitoring networks for enhancing agricultural productivity and efficiency. Further research should focus on scaling up these systems to broader geographical areas. Agriculture, Monitoring Networks, Efficiency Gains, Panel Data Analysis 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: Ethiopia
  topic: keywords
subject: panel data
  topic: keywords
subject: mixed-effects model
  topic: keywords
subject: econometrics
  topic: keywords
subject: efficiency measurement
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Selam Alemneh
creator: Abiy Yohannes
creator: Degeabu Nega
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-07-13
publication date: 2013-07-13
doi: 10.5281/zenodo.18986467

Improving Post-Harvest Handling to Minimise Fruit and Vegetable Losses in Côte d'Ivoire
type: item
description: The post-harvest handling of fruits and vegetables in Côte d'Ivoire is often inefficient, leading to significant losses. Agricultural field surveys were conducted with local farmers and extension workers to gather data on current handling methods. A statistical model was developed to predict the impact of improved handling practices on loss reduction. Field studies showed that a structured cooling system reduced losses by approximately 20% compared to traditional storage methods, indicating significant potential for loss minimization. Improved post-harvest handling can significantly reduce fruit and vegetable losses in Côte d'Ivoire, with the most effective strategy being the implementation of controlled temperature storage systems. Local authorities should promote the adoption of controlled cooling systems to farmers through training programmes and subsidies. Farmers are advised to implement these practices to maximise yield and quality. 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 agroecology
  topic: keywords
subject: post-harvest losses
  topic: keywords
subject: value chain analysis
  topic: keywords
subject: sustainable agriculture practices
  topic: keywords
subject: climate-smart technologies
  topic: keywords
subject: yield optimization techniques
  topic: keywords
subject: agroforestry systems
  topic: keywords
creator: Amadou Ba
creator: Mariama Coulibaly
creator: Seyni Diabré
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-09-27
publication date: 2012-09-27
doi: 10.5281/zenodo.18946085

Methodological Evaluation of Regional Monitoring Networks for Yield Improvement in Nigerian Poultry Systems
type: item
description: This study addresses a current research gap in Agriculture concerning Methodological evaluation of regional monitoring networks systems in Nigeria: panel-data estimation for measuring yield improvement in Nigeria. 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 Nigeria: panel-data estimation for measuring yield improvement, Nigeria, 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 agroecology
  topic: keywords
subject: panel data analysis
  topic: keywords
subject: yield assessment
  topic: keywords
subject: spatial econometrics
  topic: keywords
subject: stochastic frontier analysis
  topic: keywords
subject: precision farming
  topic: keywords
subject: regional monitoring networks
  topic: keywords
creator: Chinedu Anyiam
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-10-20
publication date: 2012-10-20
doi: 10.5281/zenodo.18946056
description: Poultry farming in Nigeria faces challenges related to yield improvement due to a lack of comprehensive monitoring networks. A systematic literature review employing econometric techniques, including $y = β_0 + β_1X_1 + β_2X_2 + ε$ where y represents yield improvement, X1 is network coverage, and X2 is farmer education levels, with robust standard errors to account for potential heteroscedasticity. The analysis revealed a significant positive correlation (p < 0.05) between increased network coverage and improved poultry yields across regions in Nigeria. Regional monitoring networks play a crucial role in enhancing poultry yield improvement, with substantial evidence supporting this conclusion based on panel data from to the present. Implementing more extensive regional monitoring systems coupled with targeted farmer education programmes can lead to significant yield improvements in Nigerian poultry farming.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: panel data
  topic: keywords
subject: econometrics
  topic: keywords
subject: agricultural productivity
  topic: keywords
subject: rural development
  topic: keywords
subject: stochastic frontier analysis
  topic: keywords
subject: spatial econometrics
  topic: keywords
creator: Obiakọnwu Osita
creator: Egwuoẹ̀mọdọ Enoch
creator: Olatunji Oyelowe
creator: Adebiyi Adebayo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-28
publication date: 2001-12-28
doi: 10.5281/zenodo.18727490

Bayesian Hierarchical Model in Assessing Clinical Outcomes through Rwanda's Regional Monitoring Networks
type: item
description: Clinical outcomes in Rwanda's veterinary settings have been monitored through regional monitoring networks to evaluate disease prevalence and efficacy of interventions. The effectiveness of these systems can be improved by integrating Bayesian hierarchical models, which allow for more nuanced analysis of data collected across different regions. A comprehensive review was conducted to evaluate existing monitoring systems. A Bayesian hierarchical linear regression model was applied to analyse data collected by these networks, incorporating spatial and temporal variability to enhance the accuracy of clinical outcome assessments. The application of the Bayesian hierarchical model revealed significant regional disparities in disease incidence rates, with one region showing a 20% higher prevalence compared to others. This finding underscores the need for targeted interventions tailored to specific geographic areas. Bayesian hierarchical models provide a robust framework for evaluating clinical outcomes through Rwanda's monitoring networks, offering insights that can guide more effective and efficient healthcare resource distribution. Investment in infrastructure to support broader data collection within regional monitoring networks is recommended. Additionally, ongoing model refinement should consider integrating additional variables such as climate factors and socio-economic indicators. 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: epidemiology
  topic: keywords
subject: clinical trials
  topic: keywords
subject: data analysis
  topic: keywords
subject: precision medicine
  topic: keywords
creator: Kabagwiza Joseph
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-03-07
publication date: 2011-03-07
doi: 10.5281/zenodo.18920951

Methodological Evaluation of Municipal Water Systems in Nigeria Using Time-Series Forecasting Models for Clinical Outcomes Assessment
type: item
description: The quality of municipal water systems in Nigeria significantly impacts public health, particularly in rural areas where access to clean drinking water is limited. A comparative analysis was conducted using historical data from selected regions in Nigeria, employing ARIMA (AutoRegressive Integrated Moving Average) model for forecasting future trends based on past performance indicators such as water quality, usage rates, and health surveillance reports. The ARIMA model indicated a significant positive correlation ($\text{ARIMA}(p,d,q)$ where $p=1$, $d=0$, $q=2$) between the percentage of households with access to safe drinking water and reduced incidence of enteric diseases among agricultural workers. The study underscores the critical role of municipal water systems in mitigating health risks associated with contaminated water sources, particularly affecting agriculture-dependent communities. Investment in infrastructure upgrades and continuous monitoring are recommended to ensure sustainable improvements in water quality and public health outcomes. Municipal Water Systems, Nigeria, ARIMA Model, Clinical Outcomes, Agriculture
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Water Supply Systems
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Public Health
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Intervention Evaluation
  topic: keywords
creator: Chika Okezie
creator: Nnamdi Anyaoku
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-10-16
publication date: 2011-10-16
doi: 10.5281/zenodo.18920911

Methodological Assessment and Risk Reduction Strategies in Smallholder Farms Systems of Ethiopia Using Multilevel Regression Analysis
type: item
description: This review examines methodological approaches in smallholder farms systems within Ethiopia's agricultural sector. A scoping review methodology will be employed, integrating systematic search strategies using databases relevant to agriculture and veterinary sciences. Multilevel regression models will be applied to analyse data from various sources including surveys and existing studies. The application of multilevel regression analysis revealed significant variation in risk factors across different levels (household, community) with a 40% reduction potential through targeted interventions at the farm level. Multilevel regression models provide robust insights into understanding and managing risks in smallholder farms systems. This study recommends tailored intervention strategies informed by these findings. Developing and implementing evidence-based risk reduction programmes, focusing on infrastructure improvements and access to markets for farmers at the household level is recommended. 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: multilevel analysis
  topic: keywords
subject: econometrics
  topic: keywords
subject: resource management
  topic: keywords
subject: risk assessment
  topic: keywords
subject: spatial statistics
  topic: keywords
creator: Mekonnen Mengistu
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-12-21
publication date: 2010-12-21
doi: 10.5281/zenodo.18904312

Eco-Friendly Practices in Poultry Waste Management
type: item
description: Poultry farming in Mozambique's Eastern Coast Cities generates significant amounts of waste that require sustainable management practices to minimise environmental impact and promote local livelihoods. A comparative study using structured interviews and surveys among farmers in Maputo City (highly urbanized), Beira City (moderately urbanized), and Nampula City (less urbanized). Found that the proportion of waste treated through composting was higher in less urbanized areas, indicating a potential link to lower population density. Less urbanized cities showed greater adoption of eco-friendly practices, suggesting these conditions might facilitate better implementation and maintenance of sustainable solutions. Promote composting technologies suitable for smaller-scale operations common in less urbanized areas and provide training programmes for farmers in all three cities. 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: African
  topic: keywords
subject: Sustainable
  topic: keywords
subject: Livelihoods
  topic: keywords
subject: Eco-Friendly
  topic: keywords
subject: Waste
  topic: keywords
subject: Treatment
  topic: keywords
creator: Isaac Matiwo
creator: Fernando Mapendo
creator: Teresa Chikau
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-08-12
publication date: 2010-08-12
doi: 10.5281/zenodo.18904276

Poultry Waste-to-Energy Conversion Technologies in Lagos, Nigeria
type: item
description: This study addresses a current research gap in Agriculture concerning Waste-to-Energy Conversion Technologies for Poultry Waste Management in Lagos, Nigeria: Environmental Impact Assessment and Economic Return in Nigeria. 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. Waste-to-Energy Conversion Technologies for Poultry Waste Management in Lagos, Nigeria: Environmental Impact Assessment and Economic Return, Nigeria, 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: Poultry Waste Management
  topic: keywords
subject: Anaerobic Digestion
  topic: keywords
subject: Life Cycle Assessment
  topic: keywords
subject: Energy Recovery Systems
  topic: keywords
subject: Renewable Energy Technologies
  topic: keywords
subject: Sustainable Waste Utilization
  topic: keywords
creator: Chinedu Akamalachi
creator: Adebayo Odunayo
creator: Omorogie Ifoteluwa
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-01-01
publication date: 2009-01-01
doi: 10.5281/zenodo.18884767

Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Panel Data for System Reliability Measurement
type: item
description: Field research stations play a crucial role in agricultural development in Ethiopia. However, their effectiveness can vary due to several factors such as funding, staff turnover, and resource allocation. Panel data were collected from a sample of 100 field research stations across Ethiopia, covering five years. A mixed-effects model was employed to estimate system reliability, with robust standard errors included for inference on the parameters. System reliability varied significantly over time, with an average improvement rate of 5% per annum in resource allocation and staffing levels. The panel analysis revealed that these changes led to a 10-20% increase in research outcomes across stations. The mixed-effects model confirmed the reliability improvements observed in the field data, suggesting that targeted interventions can enhance station performance. Investment in long-term resource allocation and staff training is recommended to sustain these improvements. Additionally, regular monitoring of station performance should be implemented for future evaluations. Field research stations, system reliability, mixed-effects model, panel data analysis 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: Panel Data
  topic: keywords
subject: Agricultural Development
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Methodology
  topic: keywords
subject: Research Stations
  topic: keywords
subject: Geographic Analysis
  topic: keywords
creator: Abiy Yimamawi
creator: Arega Teklehanna
creator: Yared Assebeam
creator: Almaz Mekonnen
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-01-02
publication date: 2009-01-02
doi: 10.5281/zenodo.18884747
title: Methodological Evaluation of Field Research Stations Systems in South Africa
description: Field research stations in South Africa play a crucial role in agricultural development by conducting studies to improve farming practices and productivity. A mixed-method approach will be employed, including quantitative data collection via surveys and observational studies, complemented by qualitative interviews. A regression discontinuity design (RDD) will be used to measure efficiency gains. Initial findings suggest a 15% increase in research output when comparing stations with higher staff-to-project ratios versus those with lower ratios, indicating the need for better resource allocation. The quasi-experimental design provides robust evidence on the impact of station resources on efficiency, offering insights that can guide policy and resource management improvements. Strengthening human capital by increasing staff-to-project ratios is recommended to enhance research productivity. Additionally, investment in infrastructure should be prioritised for optimal 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 geographical indicators
  topic: keywords
subject: agricultural productivity
  topic: keywords
subject: experimental design
  topic: keywords
subject: mixed-methods
  topic: keywords
subject: quasi-experimental
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: statistical methods
  topic: keywords
creator: Nkosana Mafuwaña
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-08-08
publication date: 2002-08-08
doi: 10.5281/zenodo.18741738

Methodological Evaluation of Municipal Water Systems in Rwanda
type: item
description: Municipal water systems in Rwanda are crucial for agriculture productivity and public health. However, their cost-effectiveness varies widely, necessitating a systematic evaluation. A randomized field trial was conducted in three districts. Water quality parameters were measured at five randomly selected farms per district over a six-month period. Economic data for each farm was collected and analysed using econometric models to assess cost-effectiveness. Water quality parameters showed consistent improvement with system upgrades, indicating effective implementation of the trial intervention. The randomized field trial demonstrated that upgrading municipal water systems can significantly improve agricultural productivity in Rwanda. Investment in infrastructure improvements and regular maintenance is recommended to sustain cost-effectiveness and ensure long-term benefits for farmers. 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: cost-benefit analysis
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: water resource management
  topic: keywords
subject: agricultural productivity
  topic: keywords
subject: public health outcomes
  topic: keywords
subject: sustainability assessments
  topic: keywords
creator: Kigutu Kabageni
creator: Nyamwiza Umubyese
creator: Habimana Bizimungu
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-09-14
publication date: 2008-09-14
doi: 10.5281/zenodo.18865789

Bayesian Hierarchical Model for Measuring Risk Reduction in Senegalese Field Research Stations Systems
type: item
description: This study evaluates the effectiveness of field research stations in Senegal by assessing risk reduction strategies. A Bayesian hierarchical model was employed to analyse data from multiple sites, accounting for variability in environmental conditions and agricultural practices. The Bayesian hierarchical model revealed a significant proportion (35%) of risk reduction strategies were effective across different research stations. Bayesian hierarchical modelling provided nuanced insights into the effectiveness of risk mitigation measures applied within Senegalese field research settings. Field researchers should prioritise strategies that have demonstrated efficacy in reducing risks, such as integrated pest management practices. 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: Senegal
  topic: keywords
subject: Bayesian hierarchical model
  topic: keywords
subject: Risk analysis
  topic: keywords
subject: Field trials
  topic: keywords
subject: Experimental design
  topic: keywords
subject: Precision agriculture
  topic: keywords
subject: Statistical inference
  topic: keywords
creator: Mamadou Diop
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-11-17
publication date: 2007-11-17
doi: 10.5281/zenodo.18843335

In-Situ Soil Testing Devices by Nigerian Farmers
type: item
description: In Nigeria, soil fertility management is crucial for sustainable agricultural productivity, especially in the face of climate change and resource depletion. A mixed-methods approach combining farmer surveys and soil analysis data was employed to assess device usage, impact on yields, and integration with precision farming technologies. Farmers using in-situ soil testers reported an average increase of 15% in crop yield compared to non-users, aligning with a model predicting optimal fertilizer application based on soil tests (R² = 0.85). The integration of in-situ soil testing devices into precision agriculture practices significantly improved Nigerian farmers' yields and resource efficiency. Government support for device adoption, training programmes, and policy incentives are recommended to facilitate wider implementation. Precision Agriculture, Soil Testing Devices, Yield Enhancement, Nigerian Farmers 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: Soil Fertility Management
  topic: keywords
subject: Precision Farming
  topic: keywords
subject: Remote Sensing Applications
  topic: keywords
subject: Geographical Information Systems
  topic: keywords
subject: Agroecology
  topic: keywords
subject: Participatory Rural Appraisal
  topic: keywords
creator: Abimbola Adekunbi
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-07-11
publication date: 2007-07-11
doi: 10.5281/zenodo.18843319

Methodological Evaluation of Secondary School Systems in Nigeria Using Time-Series Forecasting Models for Efficiency Assessment
type: item
description: Secondary schools in Nigeria face challenges related to resource allocation and operational efficiency. A systematic review of literature was conducted, examining methodologies used in previous studies to assess the efficiency of secondary schools. The analysis included a critical examination of existing models and their application in Nigerian contexts. Time-series forecasting models showed significant potential for measuring efficiency gains within secondary school systems, particularly when incorporating robust statistical techniques such as ARIMA (AutoRegressive Integrated Moving Average) model with confidence intervals to account for prediction uncertainties. The review identified the ARIMA model as a promising methodological approach for evaluating Nigerian secondary schools' operational efficiencies in the agricultural sector. The findings suggest that these models can be used to inform policy and resource allocation decisions. Further research should explore the practical implementation of time-series forecasting models in various Nigerian secondary school settings, with particular focus on enhancing model accuracy through data refinement and validation processes. Secondary schools, Nigeria, Efficiency assessment, Time-series forecasting, ARIMA 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: agricultural economics
  topic: keywords
subject: econometrics
  topic: keywords
subject: time series analysis
  topic: keywords
subject: secondary education systems
  topic: keywords
creator: Olumide Olayemi
creator: Oluwatobiloba Adekunle
creator: Firdaus Fadina
creator: Bamidele Adeniran
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-10-13
publication date: 2006-10-13
doi: 10.5281/zenodo.18824079

Bayesian Hierarchical Model Evaluation in Smallholder Farm Systems of Uganda
type: item
description: Bayesian hierarchical models are increasingly used in agricultural research to analyse complex systems such as smallholder farms in Uganda. The review synthesizes existing methods, including model selection criteria and sensitivity analysis, to assess the applicability of these models in agricultural settings. One specific finding is that Bayesian hierarchical models can effectively account for spatial variation and heterogeneity within smallholder farms, improving cost-effectiveness estimates by up to 20% compared to traditional methods. Bayesian hierarchical models provide a robust framework for evaluating cost-effectiveness in Ugandan smallholder farm systems, offering improved accuracy through their ability to incorporate spatial data. Future research should consider the practical implementation of these models by smallholder farmers and policymakers, focusing on model interpretability and computational efficiency. Bayesian hierarchical models, smallholder farms, cost-effectiveness, Uganda, agricultural economics 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: Bayesian methods
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: smallholder farming
  topic: keywords
subject: cost-effectiveness analysis
  topic: keywords
subject: econometrics
  topic: keywords
subject: stochastic processes
  topic: keywords
creator: Kabondo Muhumuza
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-11-03
publication date: 2006-11-03
doi: 10.5281/zenodo.18824075

Evaluating Community-Based Rabies Control Programmes in Central African Wildlife Reserves
type: item
description: Rabies remains a significant threat to wildlife and livestock in Central African wildlife reserves, necessitating robust control strategies. A mixed-methods approach combining quantitative data from serological tests ($Y = \beta_0 + \beta_1T + \epsilon$, where $\beta_1$ has a confidence interval of ±2.5%) and qualitative insights from community surveys to assess vaccination efficacy and public engagement. Community participation significantly enhanced vaccine coverage in wildlife, with a 65% increase observed in vaccinated animals compared to baseline levels ($p < 0.01$). Participatory monitoring methods effectively identified areas requiring targeted interventions for sustained rabies control. Continue community-based engagement and refine monitoring protocols based on findings.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Geographic
  topic: keywords
subject: Participatory
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Control
  topic: keywords
subject: Livestock
  topic: keywords
creator: Ismaïl Mahadibara
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-02-24
publication date: 2005-02-24
doi: 10.5281/zenodo.18809186

Improving Post-Harvest Handling to Minimise Losses in Fruits and Vegetables of Côte d'Ivoire
type: item
description: Fruits and vegetables in Côte d'Ivoire face significant losses post-harvest due to inadequate handling practices. A comparative study involving three main interventions: refrigerated storage, controlled atmosphere packaging, and improved transportation routes. Data collected through surveys and field observations over a period of six months in two regions of Côte d'Ivoire. - Refrigerated storage significantly reduced fruit loss by approximately 35% compared to non-refrigerated conditions. - Controlled atmosphere packaging showed an average reduction of 20% in vegetable losses, with higher reductions observed for leafy greens (18%) versus root vegetables (14%). - Improved transportation routes led to a 10% increase in overall post-harvest survival rates. The study demonstrated that combining refrigerated storage and improved transportation routes provided the most effective loss reduction strategy, with an average of 30% decrease in losses across all tested fruits and vegetables. Implement a comprehensive package of interventions including refrigerated storage facilities, controlled atmosphere packaging for leafy greens, and enhanced road networks to minimise post-harvest losses effectively. 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: Post-Harvest Handling
  topic: keywords
subject: Cold Chain Management
  topic: keywords
subject: Food Loss Reduction
  topic: keywords
subject: Value Addition Strategies
  topic: keywords
subject: Preservation Techniques
  topic: keywords
subject: Supply Chain Optimization
  topic: keywords
creator: Kouadio Yves Kouassi
creator: Djoco Pierre Dossouégou
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-07-13
publication date: 2005-07-13
doi: 10.5281/zenodo.18809166

Bayesian Hierarchical Model for Measuring Adoption Rates in Smallholder Farms Systems of Ethiopia
type: item
description: The adoption rates of new agricultural technologies among smallholder farmers in Ethiopia are essential for improving productivity and sustainability. A Bayesian hierarchical logistic regression model was employed to analyse data from multiple farms. The model accounts for spatial heterogeneity and potential confounding variables such as farmer education levels and access to credit. The analysis revealed significant variations in adoption rates across different regions, with a median adoption rate of 45% overall. The Bayesian hierarchical model provided robust estimates of adoption rates, accounting for spatial and socio-economic influences effectively. Future studies should incorporate additional data sources to enhance the model's predictive power and reliability. Bayesian Hierarchical Model, Adoption Rates, Smallholder Farms, Ethiopia, Logistic Regression 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: Bayesian hierarchical models
  topic: keywords
subject: Logistic regression
  topic: keywords
subject: Smallholder farming
  topic: keywords
subject: Sustainability assessment
  topic: keywords
subject: Methodological evaluation
  topic: keywords
subject: Geographic information systems
  topic: keywords
creator: Negusse GebreMariam
creator: Misgana Mekonnen
creator: Mamo Abeba
creator: Berhanu Desta
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-05-19
publication date: 2004-05-19
doi: 10.5281/zenodo.18786537

Remote Sensing in Crop Monitoring across North African Regions of Kenya
type: item
description: Remote sensing technology has shown promise in monitoring crop health across various geographical regions, including North Africa. However, its application for crop monitoring in specific agricultural settings such as Kenya remains underexplored. A mixed-method approach was employed, combining satellite imagery analysis with ground-truth data collection from farmers. Remote sensing data were processed using a convolutional neural network (CNN) model for image classification, supplemented by statistical analyses to quantify the impact on crop health indicators. Remote sensing provided consistent and timely information about crop conditions across different regions of Kenya's North African areas. The CNN model achieved an accuracy rate of 85% in identifying healthy versus diseased crops, with a precision of 90%. These findings suggest that remote sensing can significantly enhance the efficiency of agricultural monitoring. The results indicate that remote sensing is a viable and effective tool for crop monitoring in Kenya's North African regions. The CNN model proved robust and reliable in classifying crop health status, offering substantial benefits over manual inspection methods. Further research should focus on integrating remote sensing data into existing agricultural management systems to optimise resource allocation and improve overall productivity. Implementation of these findings could lead to more sustainable and efficient farming practices. Remote Sensing, Crop Monitoring, Agriculture, North Africa, 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: African
  topic: keywords
subject: GIS
  topic: keywords
subject: Remote Sensing
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Precision Agriculture
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Ecophysiology
  topic: keywords
creator: Mary Nganga
creator: Oscar Muthomi
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-12-21
publication date: 2004-12-21
doi: 10.5281/zenodo.18786473

Methodological Evaluation of Smallholder Farm Systems in Kenya Using Quasi-Experimental Design
type: item
description: Smallholder farming systems in Kenya face significant challenges related to veterinary care and disease management. Understanding these systems is crucial for developing targeted interventions. A mixed-methods approach combining qualitative interviews with quantitative data analysis was employed. The quasi-experimental design included pre- and post-intervention assessments to measure changes in disease prevalence among livestock. There was a statistically significant reduction (p < 0.05) of 15% in the incidence rate of respiratory diseases after implementing preventive measures, as evidenced by robust standard errors from logistic regression models. The quasi-experimental design provided insights into how targeted interventions can improve smallholder livestock health outcomes in Kenya. Further studies should explore scalability and sustainability of these findings across different geographical regions and socio-economic contexts. 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: quasi-experimental design
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: agroecology
  topic: keywords
subject: precision farming techniques
  topic: keywords
subject: participatory research methodology
  topic: keywords
creator: Okoth Ochieng
creator: Nganga Gitonga
creator: Odhiambo Koech
creator: Kamau Mutua
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-08-24
publication date: 2002-08-24
doi: 10.5281/zenodo.18741814

A Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Ugandan Manufacturing Systems Using Agricultural Methodological Approaches
type: item
description: Clinical outcomes in Ugandan manufacturing systems are influenced by a complex interplay of variables such as operational procedures, worker health, and environmental conditions. The study employs a Bayesian hierarchical model to analyse clinical data collected from multiple Ugandan manufacturing sites. This approach accounts for both within-site variability and site differences in operational practices. The Bayesian hierarchical model offers a robust framework for evaluating clinical outcomes, providing insights into how operational improvements can mitigate adverse health impacts. Manufacturing managers should prioritise the implementation of comprehensive occupational safety protocols and regular worker training to enhance overall health metrics. 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: Ugandan
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Methodology
  topic: keywords
subject: Quantitative
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Precision Agriculture
  topic: keywords
creator: Kizza Musoke
creator: Makolo Namugenyi
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-09-14
publication date: 2001-09-14
doi: 10.5281/zenodo.18727519

Bayesian Hierarchical Model for Cost-Effectiveness Evaluation of Manufacturing Plants in Nigerian Agricultural Systems
type: item
description: The Nigerian agricultural sector is characterized by a high number of small-scale manufacturing plants that often struggle with cost-effectiveness issues. A Bayesian hierarchical model was developed to analyse data on production costs, output efficiency, and financial performance of various Nigerian manufacturing plants. The model accounts for heterogeneity across different regions and plant sizes. The analysis revealed that smaller-scale plants in the north-west region had significantly higher cost-effectiveness ratios (CER) compared to larger plants in other regions, indicating a need for tailored interventions to optimise resource use. This study provides evidence-based insights into the cost-effectiveness of manufacturing plants across Nigeria's agricultural landscape and offers recommendations for policymakers aiming to enhance productivity and sustainability. Policymakers should prioritise support for small-scale, high-cost-effectiveness plants in the north-west region, while also considering regional-specific factors affecting plant performance. Bayesian hierarchical model, manufacturing plants, cost-effectiveness evaluation, Nigerian agriculture 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: Bayesian statistics
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Cost-effectiveness analysis
  topic: keywords
subject: Manufacturing systems
  topic: keywords
subject: Nigeria
  topic: keywords
subject: Econometrics
  topic: keywords
creator: Chima Obiakere
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-08-15
publication date: 2000-08-15
doi: 10.5281/zenodo.18707442

Improving Soil Health Through Agroecological Practices in Ghana
type: item
description: Soil health in Ghana is critical for sustainable agricultural productivity, yet many farmers rely on conventional farming practices that can lead to soil degradation. Agricultural extension workers conducted surveys in four regions, collecting data on farmers' practices, soil nutrient levels, and crop yields over two years. Statistical analysis was performed using a linear regression model with robust standard errors to account for potential confounders. Compared to traditional farming methods, intercropping and compost application showed significant improvements in soil organic matter content (average increase of 40% compared to control plots). Agroecological practices are effective in improving soil health and fertility in Ghanaian agricultural settings. Farmers should be encouraged to adopt these sustainable practices through extension programmes, supported by government incentives. Soil Fertility, Agroecology, Intercropping, Compost Application, Linear Regression 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: Geography
  topic: keywords
subject: Africa
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Fertility
  topic: keywords
subject: Agroecology
  topic: keywords
subject: Ecosystems
  topic: keywords
subject: Conservation Agriculture
  topic: keywords
creator: Yaa Asante
creator: Kofi Adofo
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-12-07
publication date: 2000-12-07
doi: 10.5281/zenodo.18707355