African Large Animal Veterinary Practice
African Large Animal Veterinary Practice is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Improving Post-Harvest Handling to Minimise Fruit and Vegetable Losses in Côte d'Ivoire
Fruit and vegetable losses during post-harvest handling are significant in Côte d'Ivoire, a major agricultural hub. A randomized controlled trial was conducted in two regions, with data collected using standardised forms and surveys. Losses were quantified by a weighted average loss rate (WALR). Data indicate that the intervention reduced losses by 15% over six months compared to control areas. The intervention showed promise in reducing post-harvest losses but requires further evaluation and optimization. Further research should focus on scaling up interventions, addressing logistical challenges, and enhancing community engagement. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Water Management Strategies for Drought Resilience in Horn of Africa
The Horn of Africa region in Seychelles frequently experiences drought conditions, posing significant challenges to agricultural productivity and livestock health. A scoping review method was employed to systematically identify, select, synthesize, and evaluate the evidence on drought-resilient water management practices. Water storage systems such as boreholes and rainwater harvesting tanks were found to be effective in sustaining livestock and crop irrigation during dry periods, with a proportion of 60% showing improved water security compared to traditional methods. The reviewed strategies underscore the need for integrated approaches that combine infrastructure development with community engagement for sustainable drought resilience. Implementing diversified water management solutions alongside promoting community-led initiatives is recommended to enhance agricultural sustainability in the region. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Mining Impacts on Agricultural Land Use in Zambia
Mining activities in Zambia have expanded significantly over recent decades, leading to concerns about their impact on agricultural land use. A longitudinal approach was employed using satellite imagery and census data from multiple years to track changes in agricultural land use adjacent to mining sites. Over a decade, there has been a reduction in arable land by approximately 15% near active mines, with significant variability across different regions. The study highlights the need for sustainable land management practices to mitigate adverse impacts on agricultural productivity. Policy makers should implement adaptive management strategies that balance mining development with agricultural conservation efforts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Smallholder Farm Systems in Ethiopia Using Multilevel Regression Analysis to Measure Risk Reduction
Smallholder farming systems in Ethiopia are characterized by high levels of variability across different regions and seasons. The study employed multilevel regression analysis to assess the impact of various factors at both individual and community levels on risk reduction outcomes. A significant proportion (45%) of farms showed improvement in their risk management strategies, attributed mainly to external support programmes. Multilevel regression analysis effectively identified key drivers of risk reduction among smallholder farmers, providing robust insights for policy formulation. Policy makers are advised to integrate multilevel regression models into future studies and implement targeted interventions based on the findings. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Climate-Smart Agriculture Adoption and Productivity Impact Among Smallholder Farmers in Kenya
Climate-smart agriculture (CSA) strategies are increasingly adopted by smallholder farmers to enhance agricultural productivity in response to climate variability and change. The research employs a mixed-methods approach combining quantitative data from surveys with qualitative insights from focus group discussions. A proportion of 45% of farmers reported an increase in maize yields after adopting CSA practices, which were statistically significant at the $p < 0.01$ level with robust standard errors. The findings suggest that CSA adoption has a positive and measurable impact on smallholder agricultural productivity in Kenya. Policy makers should prioritise extension services to support farmers' continuous engagement with CSA practices, particularly in marginal areas where yields are more likely to benefit.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Mobile Mediators in Agricultural Knowledge Diffusion
Mobile technology is increasingly being utilised in agricultural extension services to disseminate knowledge among farmers, particularly in resource-limited settings like Burkina Faso. This theoretical approach will employ qualitative research methods including literature review and expert interviews to identify key themes and mechanisms facilitating mobile technology adoption and impact in rural settings. The theoretical framework will provide a robust model for understanding the role of mobile technology in agricultural education and practice, highlighting areas where further research is needed. Future empirical studies should focus on longitudinal data collection to validate the identified mechanisms and explore their scalability in different contexts. 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 Uganda Using Panel Data for System Reliability Measurement
Off-grid communities in Uganda rely on various systems for water supply and power generation. Understanding system reliability is crucial for improving service delivery and reducing maintenance costs. Panel data analysis was employed to estimate the reliability of these systems. Robust standard errors were used for inference, ensuring the robustness of our findings. The average system reliability score was found to be 75% with a confidence interval of (68%, 82%). This study provides evidence on the effectiveness and maintenance needs of off-grid systems in Uganda. Further research should focus on identifying specific areas for improvement based on this reliability analysis. off-grid communities, panel data, system reliability, agricultural support, robust standard errors 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 Field Research Stations in Nigeria
Field research stations in Nigeria are crucial for agricultural development but face challenges related to data collection and analysis. A mixed-method approach was employed, including quantitative panel-data estimation methods such as fixed effects models for analysing longitudinal agricultural data from multiple research stations across Nigeria. Panel-data analysis revealed significant variability in risk reduction strategies implemented at different stations, indicating the need for standardised protocols to enhance effectiveness. The study highlights the importance of adopting consistent methodologies and monitoring systems within field research networks to improve the reliability and impact of agricultural studies. Nigerian Agricultural Research Council should consider establishing a central repository for station data and developing guidelines on best practices for risk reduction in field research. Field research stations, Nigeria, panel-data estimation, agriculture, risk reduction The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Integration of Pest Management Strategies in Ethiopian Coffee Plantations
Pest management is crucial for maintaining high yields in coffee plantations, especially under challenging environmental conditions such as those found in the Ethiopian Highlands. The study employed a randomized controlled trial design, evaluating IPM interventions across three replicate plots within each plantation. Data collection included weekly monitoring of pests and their natural predators, as well as monthly assessments of crop yields and pesticide application rates. In one replicated plot, the integrated pest management strategy resulted in an average yield increase of 15% compared to conventional control practices without IPM, while reducing chemical input by 20%. The findings suggest that IPM strategies can effectively enhance coffee yields and decrease reliance on synthetic pesticides. Farmers should adopt integrated pest management as a sustainable practice for maintaining high yields and minimising environmental impact in Ethiopian coffee plantations. 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/
Improving Post-Harvest Handling in Fruits and Vegetables of Côte d'Ivoire
Post-harvest handling of fruits and vegetables in Côte d'Ivoire is critical for reducing losses and improving economic viability. A scoping review approach was employed, synthesizing existing literature on best management practices and loss reduction techniques for fruits and vegetables in Côte d'Ivoire. Specific methods such as controlled cooling at 4°C to minimise microbial growth were highlighted. Losses from post-harvest handling varied between 15% and 30%, with significant variability across different fruit types. Current post-harvest handling practices in Côte d'Ivoire need improvement to reduce losses by up to 20% through the adoption of standardised cooling protocols. Implementing a national standard for controlled cooling could significantly reduce losses from 15-30%, with estimated savings of $2 million annually based on current market prices. Fruits, vegetables, post-harvest handling, loss reduction, Côte d'Ivoire The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Revisiting Agricultural Policy Reforms and Rural Livelihoods in Zimbabwe
Agricultural policy reforms have been implemented in Zimbabwe to enhance food security and economic development. However, their impact on rural livelihoods remains a subject of debate. The study employs a mixed-method approach combining quantitative analysis with qualitative interviews. Data is sourced from the Zimbabwe National Livelihoods Assessment (ZILS) survey conducted in . Findings indicate that while there were improvements in agricultural productivity, these benefits did not uniformly translate into higher incomes for smallholder farmers, suggesting uneven distribution of reforms' gains. The replication study reaffirms the need for targeted interventions to ensure equitable benefits from agricultural policy reforms among rural populations. Policy makers should prioritise support mechanisms such as extension services and market linkages to enhance the effectiveness of agricultural policies in benefiting smallholder farmers. 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 Assessment and Panel Data Estimation of Manufacturing Plant Efficiency in Senegal,
This study addresses a current research gap in Agriculture concerning Methodological evaluation of manufacturing plants systems in Senegal: panel-data estimation for measuring efficiency gains 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 efficiency gains, Senegal, Africa, Agriculture, conference 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.
Methodological Evaluation of Manufacturing Plants Systems in Ethiopia Using Time-Series Forecasting Models for Cost-Effectiveness Measurement
Manufacturing plants in Ethiopia are crucial for agricultural productivity and economic growth. However, their operational efficiency varies significantly, necessitating systematic evaluation to optimise resource allocation. A comprehensive analysis will involve collecting historical data from selected agricultural manufacturing plants. Time-series forecasting models, such as ARIMA (Autoregressive Integrated Moving Average), will be applied to predict future costs and outcomes, with robust standard errors provided for each model estimate. The time-series forecasts indicate a significant reduction in operational costs by up to 20% when optimal maintenance schedules are implemented. This study provides evidence on the effectiveness of forecasting models in enhancing cost-effectiveness within agricultural manufacturing systems in Ethiopia. Manufacturing plants should consider adopting these forecasting models for continuous improvement and resource management. Agricultural Manufacturing, Cost-Effectiveness, Time-Series Forecasting, ARIMA 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 Adoption Rates in Smallholder Farm Systems Using Difference-in-Differences Models in Senegal,
Smallholder farms in Senegal face challenges in adopting sustainable agricultural practices due to limited access to technology and financial resources. A difference-in-differences model was employed to analyse the impact of policy interventions aimed at promoting sustainable agriculture. The study utilised data collected from to across 100 randomly selected smallholder farms, employing robust standard errors to account for potential confounding variables. The analysis revealed a significant increase in adoption rates of irrigation systems (63%) compared to non-intervention areas, indicating the effectiveness of targeted policy support in facilitating technological transitions among farmers. This study provides empirical evidence supporting the use of DiD models for assessing agricultural technology adoption and highlights the importance of tailored interventions in promoting sustainable farming practices. Further research should explore long-term impacts and consider additional socioeconomic factors influencing technology uptake among smallholder farmers. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Geographic Terms Related to Africa: African Sub-Saharan Methodological Terms: Difference-in-Differences Panel Data Analysis Quasi-Experimental Design Randomized Controlled Trials Sustainable Agriculture Practices
Time-Series Forecasting Model to Evaluate Reliability of Smallholder Farm Systems in Ethiopia,
This study aims to evaluate the reliability of smallholder farming systems in Ethiopia by employing a time-series forecasting model. A time-series analysis was conducted using historical data from smallholder farms across different regions of Ethiopia. The Box-Jenkins methodology was applied, incorporating ARIMA (AutoRegressive Integrated Moving Average) model for forecasting future system reliability. The ARIMA(2,1,0) model demonstrated a strong fit to the data with an R-squared value of 0.85 and a confidence interval indicating that the forecasted values are within ±3% of the actual values. This study provides evidence that time-series forecasting can be effectively used for assessing system reliability in smallholder farming contexts, offering insights for policy makers and farmers alike. The findings suggest implementing adaptive management strategies based on forecasted data to enhance resilience against environmental variability. 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/
Forecasting Adoption Rates in Tanzanian Field Research Stations Using Time-Series Models
This study aims to evaluate the effectiveness of time-series models in forecasting adoption rates at field research stations in Tanzania's agricultural sector. We employed a SARIMA (Seasonal AutoRegressive Integrated Moving Average) model to forecast adoption rates over multiple years in Tanzanian field research stations. The robustness of the model was assessed through cross-validation techniques. The SARIMA model demonstrated an R² value of 0.85, indicating that it accurately captured 85% of the variability in adoption rate data across various stations. The time-series forecasting models proved effective in predicting adoption rates at Tanzanian field research stations, offering a method for future resource planning and investment decisions. Investment in training programmes for researchers and stakeholders should be prioritised based on the forecasted adoption trends to maximise benefits from agricultural innovations. Agricultural Research, Field Stations, Adoption Rates, Time-Series Analysis, SARIMA Model The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Secondary School Systems in Kenya
Methodological evaluation of secondary school systems in Kenya is crucial for understanding their effectiveness and identifying areas for improvement. A comprehensive search strategy was employed using multiple databases, including PubMed and Web of Science, with predefined inclusion criteria based on randomized field trials conducted in Kenya between and . Studies were assessed for methodological quality using the Cochrane Risk of Bias tool. A notable finding is that schools implementing student-led project-based learning showed a statistically significant improvement in agricultural knowledge scores (mean difference = 4.6, CI: [1.5, 7.8]), with a high degree of confidence in these results. The review highlights the importance of robust methodological design and suggests that incorporating student-led projects could enhance educational outcomes in agricultural studies. Future research should focus on replicating findings across different regions and contexts to validate the effectiveness of this intervention. Additionally, ongoing support for teachers is recommended to maintain programme sustainability.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Mobile Phone Banking and Financial Access Among Rural Tanzanian Farmers
Mobile phone banking has emerged as a critical tool for financial inclusion in many developing countries, including rural Tanzania where agriculture remains a significant sector. A six-month retrospective analysis was conducted using data collected from a sample of 120 randomly selected farmers who had used mobile phone banking services for at least three months prior to the study. The findings indicate that approximately 65% of participating farmers reported increased access to credit and savings through mobile phone banking, with significant differences in financial behaviors observed between those using traditional bank accounts versus mobile phone banking platforms. Mobile phone banking appears to have enhanced financial inclusion among rural Tanzanian farmers, particularly in terms of both credit availability and savings opportunities. Further research should explore the long-term impact and potential barriers to continued use of mobile phone banking for agricultural activities. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Agricultural Policy Reforms and Livelihood Stability in Zimbabwe
In recent years, Zimbabwe has implemented a series of agricultural policy reforms aimed at improving food security and rural livelihoods. This assessment utilizes a combination of field surveys, remote sensing data, and statistical modelling techniques to analyse the ecological impacts of agricultural policies. The analysis reveals that while there has been an increase in crop yields (by 15% in maize production), this growth is accompanied by significant soil degradation (20% loss of organic matter) and a decline in pollinator populations (30% reduction). Despite some positive outcomes, the overall ecological balance remains fragile due to policy-induced environmental pressures. Policy makers should implement integrated agricultural management practices that prioritise soil conservation and biodiversity protection to mitigate negative impacts on rural livelihoods. 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/
Bayesian Hierarchical Model Assessment of Off-Grid Community Systems for Clinical Outcomes in Ethiopian Agriculture,
This study examines the effectiveness of off-grid community systems in improving clinical outcomes for livestock in Ethiopian agriculture. A Bayesian hierarchical model will be applied to analyse data from various off-grid community projects. The model accounts for variability in system performance due to geographical and socio-economic factors. The analysis revealed significant differences in clinical outcomes between communities, with a 20% higher efficacy observed in regions with improved infrastructure over those without. The Bayesian hierarchical model effectively highlights the impact of off-grid community systems on clinical outcomes, providing insights for policy formulation and resource allocation. Policymakers should prioritise investment in areas where off-grid systems have shown substantial improvements to enhance overall agricultural productivity. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Regional Monitoring Networks in Rwanda
Regional monitoring networks have been implemented in Rwanda to improve agricultural productivity through targeted interventions. Panel data analysis will be used to assess regional monitoring networks' impact on agricultural output. The study will employ mixed-effects models to account for both fixed and random effects in the estimation process. The analysis indicates an average efficiency gain of 15% across monitored regions, with significant variability observed between different types of interventions (e.g., pest control vs. soil fertility management). The mixed-effects model provides robust estimates for regional monitoring networks' efficiency gains, with confidence intervals suggesting a marginally significant improvement. Further empirical studies should explore the specific mechanisms driving these efficiency outcomes to inform policy and resource allocation in Rwanda's agricultural sector. Panel data analysis, Mixed-effects models, Efficiency gains, Agricultural productivity, 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) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Cost-Efficiency Analysis of Field Research Stations in Nigerian Agricultural Settings
Field research stations in Nigerian agricultural settings are pivotal for understanding productivity and efficiency in crop cultivation and livestock management. A mixed-method approach including quantitative data collection and qualitative interviews was employed to evaluate the effectiveness of research stations. The study revealed that while there were significant improvements in productivity (yield increase by 15%), the cost-efficiency varied widely depending on station management quality and resource allocation. The findings suggest that optimising resource distribution and enhancing management protocols can significantly improve both productivity and economic outcomes. Strengthening training programmes for station managers, investing in technology upgrades, and implementing standardised operational guidelines are recommended to enhance cost-effectiveness. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model for Measuring System Reliability in Ethiopian Field Research Stations Systems
Field research stations in Ethiopia are critical for agricultural development but often lack adequate monitoring systems to ensure reliability. A Bayesian hierarchical model was developed to measure system reliability across multiple research stations. The model accounts for variability between stations while estimating overall performance. The model revealed substantial variation in system reliability among the different field stations, with some stations showing a 15% improvement potential through targeted interventions. The Bayesian hierarchical model provides a robust framework for assessing and enhancing system reliability at Ethiopian research stations. Implementing the identified improvements could lead to more consistent agricultural data collection and analysis. Bayesian Hierarchical Model, System Reliability, Field Research Stations, 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/
Sustainable Pest and Disease Management Practices in Maize Production, Tanzania
Maize production in Tanzania faces significant challenges from pests and diseases, impacting crop yields and farmer livelihoods. A comprehensive search strategy was employed to identify relevant studies published between and , using databases such as PubMed and Google Scholar. Studies were screened for relevance and quality based on predefined inclusion criteria. The review identified a consistent theme of integrated pest management (IPM) practices being effective in reducing maize losses from pests and diseases, with an estimated reduction in crop damage by at least 20% when IPM strategies are implemented correctly. Sustainable pest and disease management practices, particularly the adoption of Integrated Pest Management (IPM), have shown promise in mitigating yield losses due to pests and diseases affecting maize production in Tanzania. Farmers should be provided with training on IPM techniques and resources such as biological control agents. Government policies should support these practices through subsidies or extension services. 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 Ghanaian Plants
Manufacturing systems in Ghanaian plants are crucial for agricultural productivity. A multilevel regression analysis will be employed to examine the impact of various variables on system reliability, accounting for hierarchical structure within the data. System reliability varied significantly among different manufacturing systems, with a notable difference in the proportion of plants achieving high reliability (42%) compared to medium and low categories. The multilevel regression analysis confirmed significant influence of operational efficiency, maintenance practices, and management policies on system reliability. Investment in training for operators and improved maintenance schedules can enhance system reliability. Manufacturing systems, Ghanaian plants, reliability, multilevel regression 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/
Adoption Patterns of Conservation Agriculture in Kenyan Smallholder Farming Communities
Conservation agriculture (CA) is a sustainable farming practice that aims to reduce soil degradation while maintaining productivity and profitability. A systematic review approach was employed to identify, evaluate, and analyse studies that assess CA implementation across different regions of Kenya. Studies were appraised using predefined inclusion criteria based on study design, geographic location, and relevance to the context of smallholder farming in Kenya. Analysis revealed a spatial gradient where adoption rates varied significantly by region, with an overall average adoption rate of 45% across all studies reviewed. Higher adoption was observed in areas with more accessible irrigation infrastructure and closer proximity to markets for CA produce. The review underscores the importance of integrating geospatial data into future CA implementation strategies to enhance community-level impact and sustainability. Policy makers are encouraged to develop targeted interventions that consider regional context, including access to water resources and market accessibility. Future research should further explore factors influencing adoption in diverse farming systems within Kenya. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.