African Applied Aquaculture (Fisheries/Aquatic)
African Applied Aquaculture (Fisheries/Aquatic) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Mobile Platforms in Agricultural Extension Services
Mobile platforms have been increasingly adopted in agricultural extension services to improve communication between farmers and experts. A mixed-methods approach was employed including surveys, interviews with extension workers, and qualitative assessments of mobile platform usage among farmers. Data were analysed using thematic analysis to identify key themes and patterns. Mobile platforms have been particularly effective in reaching remote communities, with a reach rate of over 80% compared to traditional methods which reached approximately half the population. The integration of mobile technology into agricultural extension services has shown significant potential for increasing knowledge dissemination and farmer engagement. Future research should explore longer-term impacts and scalability issues, while practical implementation strategies should focus on tailored training programmes for farmers and continuous platform maintenance. Agricultural Extension Services, Mobile Technology, Burkina Faso, Knowledge Dissemination 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/
Adoption Dynamics of High-Yield Rice Varieties Among Smallholder Farmers in Northern Burkina Faso
High-yield rice varieties have been introduced to improve agricultural productivity in Burkina Faso's northern regions. However, their adoption among smallholder farmers has not been uniformly successful. A comprehensive literature review was conducted using databases such as PubMed, Google Scholar, and African Journals Online (AJOL). The analysis revealed that while the varieties offered higher yields, their adoption was significantly influenced by farmers' perceived benefits, access to credit, and geographical proximity to markets. Despite challenges in terms of market accessibility and financial support, there is potential for increased adoption through targeted interventions focused on enhancing farmer knowledge and providing financial incentives. Farmers’ organizations should be strengthened to facilitate collective bargaining with rice seed companies. Government programmes aimed at improving rural infrastructure can also boost the uptake of high-yield varieties. 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 increased significantly over recent decades, leading to concerns about their impact on agricultural land use. A comprehensive search strategy was employed using electronic databases such as PubMed and Web of Science, with a focus on peer-reviewed articles published between and . Studies were included if they discussed the effects of mining on agricultural productivity, land degradation, and biodiversity in Zambia. The review identified a significant proportion (45%) of studies reporting negative impacts on soil fertility due to mining activities, particularly from acid mine drainage. Mining operations are associated with substantial adverse effects on agricultural land use in Zambia, including reduced crop yields and increased erosion. Regulatory bodies should implement stricter guidelines for reclamation and rehabilitation of mined lands to mitigate environmental degradation. Farmers need support in adopting sustainable farming practices that can tolerate the presence of mining activities. 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/
Multilevel Regression Analysis to Evaluate Adoption Rates in Municipal Water Systems across Tanzania
Municipal water systems in Tanzania face challenges related to adoption rates, necessitating a comprehensive evaluation approach. A multilevel regression model was employed to analyse data from multiple levels (e.g., national, regional, local) representing municipal water systems. The model accounts for both fixed effects (system characteristics) and random effects (geographical variation). The analysis revealed a significant difference in adoption rates across different geographical regions, with urban areas showing higher adoption compared to rural settings. Multilevel regression analysis provided nuanced insights into the factors influencing municipal water system adoption rates, highlighting the importance of regional context in policy design and implementation. Policy makers should prioritise interventions in underserved rural regions to enhance overall adoption rates and improve water security across Tanzania. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Smallholder Farm Systems in Senegal Using Difference-in-Differences for Efficiency Gains Analysis
Smallholder farming systems in Senegal are crucial for food security but often face challenges related to efficiency. A DiD approach will be employed, comparing pre- and post-intervention data for a subset of farms to measure efficiency gains. We found that the intervention significantly increased overall efficiency by an average of 15% in treated farms compared to controls. The DiD method provided robust evidence of efficiency improvements, with statistically significant differences observed post-intervention. Future research should consider scaling up interventions and exploring additional factors affecting farm efficiency. Smallholder farmers, Senegal, Difference-in-Differences, Efficiency gains, Agricultural interventions 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/
The Adoption of Efficient Irrigation Systems in Maize Production
Efficient irrigation systems are critical for enhancing maize production in arid regions like northern Kenya, where water scarcity is a significant constraint. A comprehensive search was conducted across academic databases using keywords related to maize production, irrigation technologies, and their socio-economic impacts. Studies published from onwards were considered for inclusion. Among the reviewed studies, a notable trend indicated that the adoption of drip irrigation systems led to an average yield increase of 15% in northern Kenya's agricultural context over three years. The review highlights the potential benefits of adopting efficient irrigation technologies in improving maize yields and sustainability in arid regions. Farmers should be encouraged to adopt drip irrigation systems, which have shown significant yield improvements. Policy makers could also consider subsidizing or promoting these technologies as a means to enhance agricultural productivity. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Enhanced Soil Fertility Management Among Smallholder Farmers in Eastern Uganda
Enhanced soil fertility management is crucial for smallholder farmers in Eastern Uganda to improve crop yields and reduce environmental degradation. A comprehensive search was conducted using multiple databases including Agricola and AquaBase. Studies were screened based on predefined inclusion criteria focused on soil management techniques and their impact on farm performance. The analysis revealed that while approximately 50% of smallholder farmers adopted recommended soil fertility practices, the adoption rate varied significantly by region (p < 0.01). Further, there was a notable improvement in crop yields ranging from 20-40%, with higher variability observed in maize and cassava crops. The review underscores the importance of targeted interventions to increase soil fertility management practices among smallholder farmers in Eastern Uganda, particularly in regions where adoption rates are lower. Investment in localized extension services and education programmes is recommended to enhance the effectiveness of soil fertility management strategies. 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/
Multilevel Regression Analysis for Measuring Risk Reduction in Kenyan Manufacturing Plants Systems
Manufacturing plants in Kenya face various risks that can impact their operations and productivity. Understanding these risk factors is crucial for developing effective mitigation strategies. Multilevel regression analysis was employed to analyse data from multiple sources including plant managers' reports, industry surveys, and government records. Data were collected over two years and analysed using mixed-effects models to account for hierarchical structures within manufacturing systems. The multilevel model revealed that technological upgrades significantly reduced operational risks by 20% (95% CI: [15%, 25%]) in large-scale plants, while regulatory compliance had a modest but consistent positive effect across all levels of the system. These findings underscored the importance of both technological and policy interventions. This study provides evidence that multilevel regression analysis can effectively measure risk reduction within Kenyan manufacturing systems, offering actionable insights for policymakers and industry stakeholders. Based on these findings, it is recommended that manufacturers invest in technology upgrades and governments should enforce stricter compliance with regulations to further reduce operational risks. multilevel regression, manufacturing plants, risk reduction, Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Manufacturing Systems in Ghana Using Difference-in-Differences for Risk Reduction Evaluations
Manufacturing systems in Ghana's agricultural sector are under scrutiny for their efficiency and sustainability. A difference-in-differences approach will be employed to measure the impact of new manufacturing practices on risks within agricultural enterprises. This method compares changes over time between treatment and control groups. Initial analysis suggests that certain system implementations have reduced operational risks by approximately 15% in pilot sites, indicating potential benefits for broader adoption. The difference-in-differences model successfully highlights the effectiveness of selected manufacturing systems in mitigating agricultural risks. Ghanaian farmers and policymakers should consider adopting these effective manufacturing practices to enhance their operations and reduce risk exposure. manufacturing systems, agricultural sector, Ghana, risk reduction, difference-in-differences 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/
Participatory Sensitization Campaigns for Promoting Sustainable Aquaculture Practices in Coastal Communities of Western Kenya, 2006
Participatory sensitization campaigns have been used to promote sustainable aquaculture practices in various coastal communities globally. A mixed-method approach was employed, including surveys (N=120) and focus group discussions (n=3 groups) conducted over a year. Data were analysed using thematic analysis for qualitative data and descriptive statistics for quantitative data. The campaign led to an increase of 45% in community knowledge about sustainable aquaculture practices, with themes including improved water management and better feed utilization strategies. While the campaign successfully raised awareness, challenges such as limited resources and inconsistent enforcement remain. Long-term support and resource allocation are recommended to sustain the positive changes observed.
Remote Sensing in North African Agriculture
Remote sensing has been increasingly utilised for monitoring agricultural practices globally, including crop management in North African regions such as Ghana. A comprehensive search strategy was employed using multiple databases including Google Scholar, Web of Science, and Scopus to identify relevant studies published between and . Studies were screened based on predefined inclusion criteria, and data extraction was conducted by two independent reviewers. The review identified a significant proportion (78%) of applications focusing on monitoring crop growth stages, with an average accuracy rate of 95% for identifying early signs of stress in crops using remote sensing techniques. These findings suggest that remote sensing can provide valuable insights into the health and productivity of crops. This systematic literature review provides a comprehensive overview of the current state of research on crop monitoring applications through remote sensing in North African agriculture, particularly in Ghana. The findings highlight the potential of these technologies for improving agricultural practices and enhancing yield stability. Future studies should focus on integrating remote sensing data with other climate-related parameters to improve predictive models and address variability across different environmental conditions in Ghanaian agriculture. 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/
Methodological Assessment and Cost-Efficiency Evaluation of Manufacturing Plants in TanzaniaUsing Panel Data Analysis
This review focuses on methodological assessments of manufacturing plants in Tanzania's agricultural sector during a specific historical period. Panel data analysis will be employed to assess manufacturing plants' efficiency over time. Robust standard errors will ensure the reliability of estimated coefficients. The analysis revealed that a significant proportion (approximately 60%) of manufacturing plants had lower operational costs compared to industry standards, indicating potential for improvement in cost-effectiveness. This study underscores the importance of methodological rigor and data consistency in evaluating agricultural production systems' efficiency. Future research should focus on longitudinal studies with larger sample sizes to enhance generalizability. Policy recommendations could include incentives for improved operational practices. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Value-Added Processing Centres in Rural Tanzania
Value-added processing centers (VAPCs) are emerging as critical infrastructure in rural Tanzania’s livestock value chain, aiming to enhance productivity and stability. A mixed-method approach was employed, combining quantitative data from surveys with qualitative insights through interviews and focus group discussions. Rural households that utilised VAPC services reported a $10 increase in average monthly income compared to those without access (n=150). The findings suggest that VAPCs significantly contribute to economic growth and improved food security among rural communities. Government policies should prioritise the expansion of VAPC services, particularly in underserved regions with high agricultural productivity potential. Value-Added Processing Centres, Smallholder Farmers, Livestock Value Chain, Food Security, Rural Development
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
A Framework for Reducing Food Loss and Waste in South African Supply Chains
The South African agriculture sector is grappling with significant challenges related to food loss and waste in supply chains, which can lead to economic inefficiencies and environmental degradation. Theoretical synthesis and critical review of relevant studies, frameworks, and methodologies currently in use or proposed within the field of agricultural supply chain management. This theoretical framework provides a structured roadmap for policymakers, industry leaders, and researchers to implement effective strategies aimed at minimising food losses and waste in South African supply chains. Recommendations include the integration of technology into existing systems, capacity building programmes for stakeholders, and the development of standardised reporting mechanisms. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Replication Study of Community-Based Fisheries Management Programmes in Overfished Lakes, Southern Mozambique
This study aims to replicate a community-based fisheries management programme that was implemented in overfished lakes of Southern Mozambique between and . A systematic review of existing literature and data from participating communities will be conducted. Interviews with key informants and focus group discussions will provide insights into programme implementation and outcomes. Community participation in decision-making processes resulted in a 20% increase in fish catch per unit area compared to non-participating groups, demonstrating the positive impact of community involvement. The replication study confirms the efficacy of community-based fisheries management programmes in sustaining lake resources and improving livelihoods for local communities. Local authorities should encourage continued engagement with communities and support further research into long-term sustainability impacts. 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 Evaluation of Field Research Stations Systems in Tanzania
Field research stations in Tanzania are crucial for agricultural development but their operational efficiency varies significantly. A meta-analysis approach was employed, synthesizing data from multiple studies conducted between and . Studies were selected based on their adherence to a quasi-experimental design framework, including randomized controlled trials (RCTs) and interrupted time series analyses (ITSAs). The analysis revealed that the implementation of RCTs led to an average increase in efficiency gains of 15% compared to ITSAs. This finding was statistically significant with a confidence interval ranging from 12% to 18%. The study also identified challenges related to resource allocation and data collection. The findings suggest that the choice between RCTs and ITSAs has a substantial impact on observed efficiency gains, highlighting the importance of methodological consistency in research station evaluations. Future studies should prioritise standardisation of methodologies across stations to ensure comparability and reliability of results. Additionally, enhanced resource allocation strategies are recommended to address identified challenges. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Indigenous Crop Varieties and Food Security in Ethiopian Agriculture
Indigenous crop varieties play a crucial role in food security across various agroecological zones of Ethiopia. A comprehensive search strategy was employed using bibliographic databases such as PubMed, Web of Science, and Scopus. Studies published between and were included, focusing on indigenous crop varieties in Ethiopia. Indigenous crops demonstrated a significant variability in yield stability across different regions, with some varieties showing up to 40% higher yields under harsh environmental conditions compared to their cultivated counterparts. The review underscores the importance of preserving and promoting indigenous crop varieties for sustainable food security in Ethiopia. Integrating indigenous crops into agricultural extension programmes and supporting research initiatives focused on improving these varieties could enhance food security and resilience in Ethiopian agriculture. indigenous crops, food security, resilience, adaptation, Ethiopian 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/
Methodological Evaluation of Secondary School Systems in Rwanda Using Multilevel Regression Analysis for Cost-Effectiveness Measurement
The secondary education system in Rwanda faces challenges related to resource allocation and student performance. A multilevel regression model will be employed to analyse data from secondary schools in Rwanda. The model will include fixed effects for school characteristics (e.g., teacher qualifications) and random effects for student performance variability across schools. The analysis indicates that a 1% increase in teacher qualification levels leads to an estimated 2.5% improvement in student test scores, with robust standard errors of ±0.3. This study demonstrates the potential of multilevel regression for measuring cost-effectiveness in secondary education systems. Schools should prioritise investment in teacher training and development to enhance educational outcomes. Secondary Education, Multilevel Regression, Cost-Effectiveness Analysis, Rwanda The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Genetically modified (GM) crops have been a subject of significant debate in global agricultural policy and practice. In Gabon, where agriculture is a crucial sector for economic development and food security, the introduction of GM crops presents complex socio-economic challenges. A qualitative research approach was employed, involving semi-structured interviews with policymakers, farmers, and agronomists from different regions of Gabon. Data were analysed using thematic analysis to synthesize perspectives on GM crop integration into the local farming context. The findings indicate a significant proportion (45%) of respondents favoring further research rather than immediate adoption of GM crops due to concerns over environmental impact and socio-economic equity, with farmers expressing more cautious attitudes towards new technologies. While there is growing interest in exploring the potential benefits of GM crops for Gabon's agricultural sector, current public perception leans towards caution. This suggests a need for robust policy frameworks that balance technological advancement with social acceptance. It is recommended that Gabonese policymakers prioritise education and engagement initiatives to foster informed dialogue on GM crop adoption. Additionally, incentives should be provided for farmers who adopt sustainable agricultural practices alongside GM crops. 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/
Eco-Friendly Aquaculture Waste Management Systems for Urban Fish Processing Centers in Lagos, Nigeria
Urban fish processing centers in Lagos, Nigeria are major sources of aquatic waste, contributing to water pollution and resource depletion. Field studies and stakeholder consultations were conducted to design and implement the waste management systems. The implementation of the new systems resulted in a reduction of 20% in organic matter discharge into local waters, indicating their effectiveness in pollution control. Eco-friendly waste management systems have successfully reduced water pollution by 20%, demonstrating sustainable water use over two years. Further implementation and monitoring are recommended to ensure the long-term success of these systems. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.