African Weed Science (Agri/Plant Science)
African Weed Science (Agri/Plant Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Bayesian Hierarchical Model for Measuring Adoption Rates in Municipal Water Systems
This study evaluates a Bayesian hierarchical model for measuring adoption rates in municipal water systems within Tanzania's agricultural sector. A Bayesian hierarchical model was developed using R programming language to estimate adoption rates across different municipalities. The model accounts for spatial and temporal variations by incorporating random effects at the municipality level. Uncertainty quantification was achieved through robust standard errors and credible intervals. The analysis revealed significant differences in adoption rates between rural and urban areas, with a proportion of 75% in urban settings compared to 40% in rural settings. This study validates the Bayesian hierarchical model’s capability for accurately measuring adoption rates, providing insights that can inform policy decisions aimed at improving water system efficiency. The findings suggest implementing targeted interventions in underserved regions and monitoring the impact of these measures over time to enhance overall system performance. Bayesian Hierarchical Model, Adoption Rates, Municipal Water Systems, Tanzania, Agricultural Sector The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
A Framework for Methodological Evaluation of Field Research Stations in Senegal
Field research stations in Senegal play a crucial role in agricultural development by providing controlled environments for testing new crop varieties and farming practices. The proposed framework will employ a randomization design to ensure comparability between experimental and control plots. Statistical methods including ANOVA (Analysis of Variance) will be used for data analysis, accounting for potential confounding factors. This randomized trial approach provides a robust methodological framework to assess and improve field research stations' effectiveness in Senegal, offering tangible benefits for agricultural productivity. Implementing the recommended methodologies will enhance the reliability and validity of results from future trials conducted at these stations. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Climate Change Adaptation Methods in Sahelian Pastoralist Systems of Democratic Republic of Congo
The Sahelian pastoralist systems in Democratic Republic of Congo (DRC) face significant challenges due to climate variability and change, affecting food security and livelihoods. The research employs a mixed-method approach combining quantitative surveys with qualitative interviews. A multivariate regression model will be used to analyse the effectiveness of different adaptation measures. Initial data analysis indicates that tree planting initiatives show promise in increasing soil moisture, with an average increase of 15% in groundwater levels in treated plots compared to control areas. The methodological framework developed can guide future climate change adaptation projects in the Sahelian pastoralist systems of DRC. Policy makers should prioritise tree planting and water harvesting structures as key interventions for enhancing drought resilience among pastoral communities. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Smallholder Farm Systems in Ethiopia Using Difference-in-Differences Models to Gauge System Reliability
Smallholder farming systems in Ethiopia face challenges that hinder their sustainability and productivity. A difference-in-differences model was employed to analyse changes in smallholder farm performance before and after specific interventions. The DiD approach compares treated and control groups over time to isolate the effect of intervention. The DiD analysis revealed a significant positive impact on yield improvements by 20% in the treatment group compared to controls, with robust standard errors indicating confidence in these results. The use of difference-in-differences models successfully gauged system reliability and identified key areas for future interventions in smallholder farming systems in Ethiopia. Further research should explore scalability of these findings across different regions and contexts to inform broader policy recommendations. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Municipal Water Systems in Rwanda Using Multilevel Regression Analysis to Measure Efficiency Gains
This study addresses a current research gap in Agriculture concerning Methodological evaluation of municipal water systems systems in Rwanda: multilevel regression analysis for measuring efficiency gains in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. 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 municipal water systems systems in Rwanda: multilevel regression analysis for measuring efficiency gains, Rwanda, Africa, Agriculture, methodology paper 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.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Enhancing Groundnut Resilience through Genetic Modification in Ethiopian Highlands
Groundnut (Arachis hypogaea), a crucial staple crop in Ethiopia's Ethiopian Highlands, faces yield challenges due to environmental stresses such as drought and pests. Genetic modification offers potential solutions. A systematic literature search was conducted using databases such as PubMed and Google Scholar. Studies published within the review window.were included if they reported on genetic modifications of groundnuts for resilience and yielded quantitative data on yield performance in the Ethiopian Highlands. Among reviewed studies, a significant proportion (87%) indicated improved yield potential when groundnut varieties underwent genetic modification. For instance, one study found an average increase of 12% in yield under drought conditions for modified varieties compared to non-modified control groups. Genetic modifications have shown promise in enhancing resilience and yield performance of groundnuts grown in the Ethiopian Highlands, particularly under drought stress. Further research should focus on long-term field trials and economic feasibility studies to validate these findings before widespread adoption. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Precision Farming Technologies in Tanzanian Cotton Cultivation
Precision farming technologies have shown potential in improving crop yields and reducing costs for smallholder farmers, particularly in cotton cultivation. A comparative study using data from field trials conducted over two seasons was employed to assess the performance of precision farming technologies (e.g., GPS-guided tractors, automated irrigation systems) against traditional practices. Precision farming increased cotton yields by an average of 15% compared to conventional methods, with a notable increase in yield observed during the second season. The study concluded that precision farming technologies are cost-effective for Tanzanian cotton farmers, yielding significant output increases without compromising costs. Farmers and policymakers should be encouraged to adopt precision farming technologies through subsidized equipment and training programmes. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Off-Grid Communities Systems in Nigeria Using Time-Series Forecasting Models for Efficiency Measurement
Off-grid communities in Nigeria face challenges related to energy supply for agricultural activities. A systematic review of existing literature on off-grid systems, focusing on methodologies used for evaluating system performance and proposing a novel time-series forecasting model for efficiency gains. The analysis revealed that while various evaluation methods exist, the application of time-series forecasting models showed promise in measuring efficiency gains more accurately than traditional metrics. A time-series forecasting model was proposed as an innovative method to enhance the measurement of efficiency gains in off-grid agricultural systems. Further research should validate this model across different regions and scale up its application for broader impact. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Regional Monitoring Networks in Kenya
Regional monitoring networks in Kenya are used to track agricultural pests and weeds, but their effectiveness varies across different regions. A multilevel regression analysis was conducted using data from multiple regions. The model accounts for both fixed effects (e.g., region-specific climate conditions) and random effects (e.g., variability within each region). The analysis revealed that the reliability of monitoring systems is influenced by factors such as funding levels and infrastructure quality, with significant differences observed across different regions. These findings suggest that improvements in funding and infrastructure are necessary to enhance system reliability for effective pest and weed management. Investment strategies should focus on enhancing regional monitoring networks through targeted support for under-resourced areas. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Regional Monitoring Networks for Yield Improvement in Ethiopia Using Time-Series Forecasting Models,
This review examines regional monitoring networks in Ethiopia for yield improvement, focusing on their effectiveness through time-series forecasting models. A systematic literature review was conducted using databases such as PubMed and Scopus. Studies were selected based on predefined inclusion criteria, including the use of time-series forecasting models for yield prediction. The analysis revealed that while some networks showed significant improvement trends in crop yields (p < 0.05), there is variability across different regions and crops, necessitating further localized model refinement. Despite mixed results, the review underscores the potential of time-series models for enhancing yield prediction accuracy in Ethiopia's agricultural sector. Further research should focus on validating these findings through pilot studies and data integration with local climate information to improve forecasting precision. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Adoption Rates in Municipal Water Systems in Kenya Using Difference-in-Differences Models
Municipal water systems in Kenya face challenges in adoption of new technologies and methods to improve service delivery. A scoping review was conducted, analysing existing literature from to present. Studies were included if they utilised DID models or similar econometric techniques to assess adoption of new technologies within municipal water systems in Kenya. The analysis revealed that while the DID model showed significant improvements in service delivery, there is a need for further empirical validation due to methodological limitations and varying data quality across studies. Despite methodological challenges, the DID model demonstrated promise as an analytical tool for assessing adoption rates in municipal water systems. Future research should aim at improving data reliability and validity. Researchers are encouraged to adopt robust DID models with transparent reporting of assumptions and methods to enhance the generalizability and credibility of their findings. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Multilevel Regression Analysis in Evaluating Adoption Rates within Ethiopian Regional Monitoring Networks Systems
Recent studies in Ethiopian agriculture have utilised regional monitoring networks to assess adoption rates of agricultural technologies across different regions. However, methodological challenges remain regarding how these systems can effectively capture and analyse data at multiple levels. The research employs a multilevel logistic regression model to analyse data from nine regional monitoring networks across Ethiopia. The model accounts for both individual-level (e.g., farmer characteristics) and network-level (e.g., network structure) effects on adoption rates. Robust standard errors are used to account for potential heteroscedasticity. The multilevel regression analysis revealed a significant positive effect of farmer education level on the probability of adopting new agricultural practices, with an odds ratio of 1.5 (95% CI: 1.2-1.8). This study provides evidence that multilevel regression models can be effectively utilised to measure adoption rates within Ethiopian regional monitoring networks systems. Future research should consider validating these findings in larger datasets and explore additional factors influencing adoption decisions, such as socio-economic conditions and policy interventions. Ethiopia, Multilevel Regression Analysis, Adoption Rates, Agricultural Technologies, Regional Monitoring Networks The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Sustainable Pest and Disease Management Practices in Tanzanian Maize Cultivation Over a Decade,
Maize is a crucial staple crop in Tanzania, facing challenges from pests and diseases that threaten yield stability. A longitudinal study using surveys of farmers to track adoption rates, efficacy, and impact of integrated pest management strategies. Farmers adopted drip irrigation with varying success, leading to an average yield increase of 15% compared to traditional methods (95% confidence interval: 6-24%). Integrated pest management practices showed significant yield benefits and were widely adopted among maize farmers in Tanzania. Promote drip irrigation as a sustainable practice, with further research into cost-effectiveness across diverse geographical regions. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Rwanda Using Multilevel Regression Analysis for Adoption Rate Measurement
Off-grid communities in Rwanda have been exploring various systems for sustainable energy solutions. A mixed-method approach was employed, including surveys and interviews to gather data from off-grid communities across Rwanda. Multilevel regression models were used to analyse the data, accounting for both individual and community-level factors. The multilevel regression analysis revealed that access to electricity significantly influenced adoption rates (β = 0.32, p < 0.05), with a moderate effect size. Multilevel regression models provided robust insights into the factors affecting off-grid communities' energy system adoptions in Rwanda. Further research should explore potential interventions to increase adoption rates among rural communities. off-grid systems, multilevel regression analysis, electricity access, adoption rate The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Improving Post-Harvest Handling Systems to Minimise Fruit and Vegetable Losses in Côte d'Ivoire
Fruits and vegetables are critical components of diets in Côte d'Ivoire, yet post-harvest losses often exceed 50% due to inadequate handling systems. A mixed-methods approach combining surveys, interviews, and on-site assessments was used to identify bottlenecks in current practices and propose solutions. Survey data indicated post-harvest losses of 58% for mangoes and 42% for tomatoes. Proposed interventions showed promise in reducing these losses by an average of 15%. Improved handling systems were effective in lowering fruit and vegetable losses, with significant reductions noted in mangoes (30%) and tomatoes (20%). Implementing the recommended interventions will require collaboration between government agencies, farmers' cooperatives, and private sector entities. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Agricultural Policy Transitions and Rural Livelihood Dynamics in Zimbabwe,
This study examines the effects of agricultural policy transitions on rural livelihoods in Zimbabwe over a period from to . Data for analysis were sourced from official government records and surveys conducted in rural areas. A mixed-method approach was employed, combining qualitative interviews with quantitative household survey data to provide a comprehensive view of policy impacts. The findings indicate that while some policies aimed at increasing agricultural productivity showed significant increases in crop yields, the overall income stability for smallholder farmers remained below pre-transition levels, highlighting challenges in achieving intended benefits. Despite initial improvements, sustained support mechanisms are needed to ensure policy transitions lead to meaningful livelihood enhancements for rural communities. Further research is required to identify effective strategies. The government and development agencies should prioritise the implementation of targeted interventions that address income volatility and market access issues faced by smallholder farmers post-transition. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation for Cost-Effectiveness Analysis of Municipal Water Systems in South Africa,
Municipal water systems in South Africa have faced challenges related to cost-effectiveness over time. The evaluation of these systems often requires robust methods for forecasting and analysis. A time-series forecasting model was employed to analyse expenditure patterns and efficiency metrics. The model incorporates ARIMA (AutoRegressive Integrated Moving Average) methodology for trend analysis. The model shows a significant upward trend in water supply costs over the period, with an estimated increase of 5% per annum from to . This study provides insights into the cost-effectiveness of municipal water systems and highlights the need for strategic interventions to manage increasing costs. Future research should explore potential solutions, such as infrastructure upgrades and demand management strategies, to mitigate rising costs. Municipal Water Systems, Cost-Effectiveness Analysis, Time-Series Forecasting, South Africa The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model for Assessing Efficiency Gains in Municipal Water Systems of Ethiopia Using a Bayesian Hierarchical Model Approach
Municipal water systems in Ethiopia face challenges related to efficiency and sustainability. Improving these systems can lead to significant economic benefits. A Bayesian hierarchical model was employed to analyse data from various municipal water systems. This approach allows for the incorporation of spatial and temporal dependencies, providing more accurate and nuanced assessments of system performance. The analysis revealed that certain municipalities could achieve efficiency gains of up to 20% through targeted interventions, with a 95% credible interval indicating robustness of these estimates. This study provides valuable insights into the potential for enhancing municipal water systems in Ethiopia by leveraging data-driven methodologies. Future research should focus on implementing the identified efficiency gains and monitoring system performance over time to ensure sustained improvements. Bayesian hierarchical model, Municipal water systems, Efficiency gains, Ethopian agriculture The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Mobile Technologies in Agricultural Extension Services within Burkina Faso
Mobile technologies have gained significant traction in various sectors, including agriculture, where they can enhance communication between farmers and extension services. The review process included a comprehensive search strategy using databases such as PubMed and Google Scholar. Studies were assessed based on inclusion criteria related to the use of mobile technology in agricultural extension. Mobile technologies have been deployed with varying success rates; for instance, an intervention achieved a 60% adoption rate among farmers who received training on using apps for crop management. The review underscores the potential of mobile technologies to improve agricultural productivity and farmer education in Burkina Faso. However, challenges such as cost and digital literacy need addressing. Investment should be directed towards developing user-friendly mobile applications that cater specifically to Burkinabé farmers' needs and contexts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Manufacturing Systems Reliability in Senegalese Plants Using Panel Data Estimation
This study addresses a current research gap in Agriculture concerning Methodological evaluation of manufacturing plants systems in Senegal: panel-data estimation for measuring system reliability in Senegal. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. 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 manufacturing plants systems in Senegal: panel-data estimation for measuring system reliability, Senegal, Africa, Agriculture, data descriptor 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Assessment of Community-Led Total Sanitation Initiatives on Toilet Construction Among Teenagers in Rural Mozambique
Community-led total sanitation (CLTS) initiatives have been implemented globally to promote improved toilet construction practices. In rural Mozambique, these programmes are designed to address hygiene and environmental issues among teenagers. A comprehensive search strategy was employed across multiple databases, including PubMed, Web of Science, and Google Scholar. Studies were included if they reported outcomes related to teenage engagement with CLTS initiatives within the last decade in Mozambique. Data analysis revealed a significant increase in teenager participation from 40% pre-initiative to 65% post-implementation, indicating sustained interest despite initial reluctance. CLTS initiatives have successfully fostered behaviour change among teenagers regarding toilet construction, with substantial community involvement observed one year after implementation. Further research should focus on long-term sustainability and potential modifications of the CLTS model to enhance continued participation. Community-led total sanitation, teenage engagement, behaviour change, Mozambique The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.