Journal of Agripreneurship and Sustainable Development

PROFITABILITY ANALYSIS OF RICE PRODUCTION IN OBI LOCAL GOVERNMENT AREA, NASARAWA STATE

Zaknayiba, D. B., Mamman, B. D., Anzaku, P. T. — Sun, 04 Oct 2026 00:00:00 +0100

The study analyzed the profitability of rice production in Obi Local Government Area, Nasarawa State. Multistage sampling was used to 40 rice farmers. Descriptive analysis tools and Gross Margin analysis were used to achieved the objectives of the study. The findings of the study showed that most (87.5%) of the respondents were in their active years. The result shows that 80% of the respondents were male, 62.5% of the respondents were small scale farmers with farm size between the ranged of 1-2 hectares. The result of the profitability analysis showed that the return per hectare was ₦210,000 and the total cost was ₦66,662.6. The net farm income obtained was ₦143,337.4 and return on investment was ₦3.2. This implies that one naira invested in the rice enterprise could yield up to ₦3.2 naira in returns. The result of the findings revealed that stealing of the products in the farm and pest and diseases outbreak to be the most militating factors against rice production in the study area. In Conclusion findings revealed that rice production was profitable enterprise in the study area. The following recommendations were made based on the findings: Farmers should be provided with adequate credit facilities at a reasonable interest rate in order to enhance rice farmers output that will translate to increase farm family income. Farmers should utilize farm inputs that can increase their profitability level in the study area and Government and non-government organization (NGOS) should enhance extension service so that farmers can have access to latest information on how to utilize inputs.

DETERMINANTS OF RICE FARMERS' PARTICIPATION IN FERTILIZER SUBSIDY PROGRAM: A CASE STUDY FROM THE BAGUINEDA IRRIGATED PERIMETER, MALI

Maiga, B. T., Walls, H., Maiga, B. T., Matita, M. — Sun, 04 Oct 2026 00:00:00 +0100

The study examine the determinants of rice farmers' participation in fertilizer subsidy program in the Baguineda Irrigated Perimeter of Mali. Data were collected from 384 rice farmers, including 234 non-beneficiaries and 150 beneficiaries of the subsidized fertilizer. The results reveal that 48% of males benefit from the fertiliser subsidy. In contrast, only 2% of females benefit from the fertiliser subsidy. Thus, men participate more than women in the fertiliser subsidy policy in the Baguineda irrigated area. The result revealed that 19.54% of rice farmers with a basic level of education benefit from the fertiliser subsidy, compared to 17.55% of rice farmers with no education in the Baguineda irrigated area. The results of the Mann Whitney U test indicate that the quantitative variables (cultivated area, yield per hectare, number of years of experience in agriculture, number of years of experience in rice cultivation, and income from rice sales) are significantly correlated with participation status in the fertiliser subsidy policy in the Baguineda irrigated area were statistically significant at 1%. The result revealed that area cultivated and yield had a positive and significant influence on the status of participation in the fertilizer subsidy policy in the Baguineda Irrigated Perimeter at P<0.001. A Logit model was used for the data analysis. The results indicate that factors such as cultivated area and yield have a significant positive influence on program participation, while training in agricultural production technique has a significant negative influence. Based on these results, the study recommends agricultural land development and strategies for increasing agricultural production, providing targeted training to farmers on various cultivation techniques and promoting participation in agricultural input subsidy policy with the aim of improving agricultural productivity.

AGRICULTURAL EXTENSION EFFECTIVENESS AND ADOPTION OF REGENERATIVE AGRICULTURE PRACTICES AMONG CASSAVA FARMERS IN SOUTHWEST, NIGERIA

Sun, 04 Oct 2026 00:00:00 +0100

The study was carried out to examine the agricultural extension effectiveness and adoption of regenerative agriculture practices among cassava farmers in Southwest, Nigeria. Cross sectional data were collected with the use of well-structured questionnaire across 320 active cassava farmers selected using a multistage sampling procedure. Descriptive Statistics (DS), Recursive Bivariate Probit (RBT) and Regression with Endogenous Treatment Effect Regression (METEM) were used for data analysis. Descriptive results showed that 75% of respondents (234) adopted RAPs while 65.1% (203) had access to extension services. Among adopters, 67.1% were male compared to 85.1% among non-adopters, with adopters having a mean age of 45.9 years, 15.6 years farming experience and 5.43 ha farm size compared to non-adopters with 15.2 years mean age, 8.9 years’ experience and 3.38 ha farm size. 89.7% of RAPs adopters belonged to farmers' associations and 77.8% attended Farmers Field School, with adopters located closer to ADP offices (1.75 km vs 5.67 km for non-adopters). Farmers with extension access were younger (43.7 vs 49.8 years), had 14.8 years’ experience and 28.7 tons previous output, while those without access had 16.9 years’ experience and 34.5 tons output. The Recursive Bivariate Probit estimate revealed that education (0.0426, p<0.10), farm size (0.1636, p<0.01), farm ownership (0.2035, p<0.10), access to credit (0.2401, p<0.05) and previous cassava yield positively and significantly influenced RAPs adoption, while cultural resistance (-0.1749, p<0.01) had a significant negative association. Access to agricultural extension was significantly determined by age (-0.1688, p<0.05) which reduced access, household size (0.0713, p<0.01) and reduction in distance to ADP office which increased access. The Regression with Endogenous Treatment Effect Model showed that association membership, primary occupation as farming, access to credit, years of education, farm size and access to extension services had positive and significant association with cassava yield. Access to extension itself was found to decrease with age and increase with household size and farm size. Overall, RAPs adoption was greatly influenced by extension access, and both are jointly influenced by farm size, credit access, household size, education, FFS attendance and proximity to ADP office.

ORGANIC FARMING AND MODERN TECHNIQUES IN INSECT PEST CONTROL: A REVIEW

Zainab, M. K., Shahad, M. G. — Sun, 04 Oct 2026 00:00:00 +0100

The review explores recent advancements in agricultural pest control and their role in achieving sustainable agriculture that reduces reliance on traditional chemical pesticides. It focuses on the concept of organic farming as a system that utilizes natural methods to maintain soil fertility, protect the environment, and produce safe food free from chemical pollutants. The research also reviewed a range of modern pest control technologies, including the use of pheromones to disrupt insect behavior, prevent reproduction and repellents that limit pest spread in agricultural fields. It further examines sterilization methods using radiation or chemicals to reduce insect reproduction, as well as feeding inhibitors that prevent insects from benefiting from the host plant. The research also discusses insect development inhibitors and growth regulators that interfere with the insect's vital processes and prevent the completion of its life cycle. It highlights the importance of integrated pest management (IPM), which combines biological, mechanical, and chemical methods in a balanced manner. Finally, it touches upon precision agriculture, which utilizes satellites and drones to monitor insect infestations and pinpoint their exact locations. The research concluded by emphasizing that integrating modern technologies with the principles of organic farming represents a promising trend for achieving food security and reducing environmental and health damage resulting from the excessive use of chemical pesticides.

EFFECTS OF SAND DREDGING ON PHYTOPLANKTON DIVERSITY AND TROPHIC STRUCTURE OF THE OBIOKPOK NSIT RIVER, NIGER DELTA, NIGERIA

Obot, O. I., Afia, O. E. — Sun, 04 Oct 2026 00:00:00 +0100

The study assessed the influence of sand dredging on phytoplankton diversity and water quality in the Obiokpok Nsit River, Akwa Ibom State, Nigeria. Monthly sampling was conducted from August 2023 to January 2024 across three stations representing different dredging intensities: upstream (undredged), midstream (moderately dredged), and downstream (intensively dredged). Physicochemical parameters were measured using standard methods, while phytoplankton samples were collected using plankton nets and identified microscopically. Significant spatial variations (p < 0.05) were observed in several environmental parameters, with dredged stations showing reduced transparency and dissolved oxygen but elevated turbidity, total suspended solids, and phosphate concentrations. A total of 1,684 phytoplankton individuals belonging to five taxonomic classes were recorded, with Cyanophyceae dominating the assemblage (83.14%). Taxonomic richness was highest at the upstream station (20 taxa) and lowest at the moderately dredged station (15 taxa). Canonical correspondence analysis indicated that nutrient enrichment and suspended solids were the major environmental drivers influencing phytoplankton distribution. The results demonstrate that sand dredging alters water quality conditions and shifts phytoplankton community structure toward disturbance tolerant taxa, potentially affecting the trophic integrity of the river ecosystem. These findings highlight the need for effective regulation and environmental monitoring of dredging activities in tropical freshwater systems.

DIGITAL LEADERSHIP IN AGRI-BUSINESS: HOW AI-DRIVEN HR PRACTICES SHAPE ORGANIZATIONAL CULTURE AND AGRIPRENEUR SUCCESS

Eyong, A. — Sun, 04 Oct 2026 00:00:00 +0100

The study investigated the role of digital leadership in agri-business, examining how AI-driven HR practices shape organizational culture and agripreneur success. A cross-sectional survey design was employed, with data collected from 138 agribusiness operators using a structured questionnaire. Descriptive statistics, Pearson correlation, and multiple regression analysis were utilized for data analysis. The findings revealed a significant positive relationship between AI-driven HR practices and organizational culture, with skills mapping and workforce analytics demonstrating the strongest correlation (r = 0.498, p < 0.001). Digital leadership significantly predicted agripreneur success, accounting for 47.2% of the variance in business outcomes, with talent development focus emerging as the strongest predictor (β = 0.284, p < 0.001). The study concludes that AI-driven HR practices and digital leadership are powerful mechanisms for building adaptive organizational cultures and enhancing agripreneur success. It is recommended that agribusinesses implement skills mapping and workforce analytics, and that leaders prioritize talent development strategies to drive sustainable business growth.

DETERMINANTS OF ECONOMIC EFFICIENCY IN GINGER PRODUCTION IN DELTA STATE, NIGERIA

Nwadiolu, R., Ewododhe, A. C. A., Kpeyegbeyi, J. I. — Sun, 04 Oct 2026 00:00:00 +0100

The study examined the determinants of economic efficiency in ginger production in Delta State, Nigeria. It assessed the level of economic efficiency among ginger farmers and identify key socio-economic and farm-specific factors influencing their performance. Data were collected from a cross-section of ginger farmers through structured questionnaires. Descriptive statistics, stochastic frontier analysis, and cost, and multiple regression techniques were employed for analysis. The findings showed that ginger farmers in the study area operated at varying levels of economic efficiency, with the majority performing below the optimal production frontier, indicating the presence of inefficiencies in resource use. Factors such as age (0.021), access to credit (-0.410), level of education (-0.315), farming experience (-0.228), and access to extension services (-0.372) were found to significantly influence economic efficiency. The model explained explained 84% of inefficiency variation, implying strong explanatory power. Additionally, constraints such as high cost of inputs ( = 3.84), lack of credit (= 3.81), pest and disease challenges (= 3.48), inadequate infrastructure (= 3.36 ), and lack of credit (= 3.04) were identified as major barriers to achieving optimal efficiency. The study concluded that improving farmers’ access to financial services, strengthening agricultural extension systems, and promoting the use of improved inputs and technologies were critical to enhancing economic efficiency in ginger production. It is recommended that policymakers and relevant stakeholders implement targeted interventions to address these constraints and improve the productivity and income of ginger farmers in the study area.

PROSPECTS OF PRECISION AGRICULTURE FOR EFFECTIVE COCOA PRODUCTION IN DEVELOPING COUNTRIES (A GLOBAL REVIEW)

Agboola, L.O., Adesida, F.A., Adelusi, A. A., Awodumila, D. J. — Sun, 04 Oct 2026 00:00:00 +0100

Precision Agriculture (PA) is a new idea in agricultural production which is enhancing a stimulating concept controlling natural resources and noticing modern ecological farming-based data processing. It is bringing agriculture into the technological and computer age. It comprises innovations such as Geographic Information System (GIS), Satellite Remote Sensing and Global Positioning System (GPS). For instance, with the current establishment of the NigeriaSat- 1, an earth remote sensing satellite for the meteorological, mineral deposit, danger observation and administration motives, Nigeria now connects the association of countries that have approach to the chances provided by Satellite Remote Sensing in transforming their agriculture. This paper aims to describe precision agriculture, emphasizes its characteristics and explains how cocoa farmers can utilize them for commercial production. Past reviews revealed that the extent of operation of precision agriculture for effective cocoa production in developing countries is low which has led to the necessity to train cocoa farmers on the benefits to be derived in using precision agriculture. This paper concludes that the introduction of precision farming into the agricultural sector of developing countries will be of immense benefits in making efficient use of equipment for cocoa production and reducing the risks involved in farm management which will result to more cocoa yield and cocoa farmers will have more profit returns. This paper recommends the need to educate and encourage cocoa farmers on the use of labour relieving technologies such as mechanization to reduce excessive spending on labour and to improve the quality and quantity of cocoa products.

SECURING AGRICULTURAL LABOUR PRODUCTIVITY: AN AI-DRIVEN FRAMEWORK FOR ADDRESSING TRAUMA-INDUCED ABSENTEEISM IN AGRIPRENEUR-LED ENTERPRISES IN SOUTHWEST CAMEROON

Eyong, A. — Sun, 04 Oct 2026 00:00:00 +0100

The main aim of this study was to develop and empirically test an AI-driven framework for identifying, predicting and mitigating trauma-induced absenteeism among agricultural workers in agripreneur-led enterprises in Southwest Cameroon. Data were collected from 288 agricultural workers using structured questionnaires incorporating the PCL-5 and WPAI instruments, semi-structured interviews, and attendance record reviews. Quantitative data were analysed using descriptive statistics and logistic regression, while Random Forest, Support Vector Machine, and Gradient Boosting Machine algorithms were deployed to develop the predictive framework. The findings revealed alarming prevalence of trauma exposure (81.9%), with 68.4% of workers meeting criteria for probable PTSD and 47.9% experiencing trauma-induced absenteeism. Logistic regression confirmed that trauma exposure significantly increased absenteeism likelihood (AOR = 3.82, p < .001), alongside job demands, social support, and access to psychosocial services as significant determinants. The Random Forest model demonstrated excellent predictive accuracy (82.6%, AUC = 0.89), substantially outperforming traditional approaches. The study concludes that AI-driven frameworks can effectively predict trauma-induced absenteeism and enable proactive workforce interventions. Key recommendations include adopting trauma-informed practices, implementing AI-powered predictive tools for early identification of at-risk workers, and integrating psychosocial support into agricultural policies to safeguard productivity in conflict-affected regions.

DETERMINANTS OF AGRO-BASED MANUFACTURING FIRMS' DECISION TO EXPORT TO DIFFERENT DESTINATIONS

Aker, I. E., Adu, V. M. — Sun, 04 Oct 2026 00:00:00 +0100

The study analysed the determinants influencing agro-based manufacturing firms’ decisions to export to different destinations. A simple random sampling technique was employed to select 127 firms from a population of 186 accessible agro-based exporting firms in Nigeria. Primary data were collected using structured questionnaires and analysed using Multinomial Logistic Regression (MLR). Results of the Multinomial Logistic Regression revealed that export to the EU and the USA was consistently and significantly determined by firm size (0.103, p=0.000), education (0.132, p=0.050), experience (0.089, p=0.050), management characteristics (0.573, p=0.000), export marketing strategy (-1.692, p=0.000) and domestic market characteristics (-1.272, p=0.000). Export to Asian countries showed that export sales (0.0929, p=0.071), firm size (-0.1950, p=0.053), education (0.0889, p=0.014), age of the firm (0.2394, p=0.001), export market characteristics (-2.0812, p=0.000) and foreign market characteristics (-0.0438, p=0.000) are the prime and significant determinants of agro-based export to Asia. Export to East Africa was influenced by export sales (0.946), education (0.060), management characteristics (0.396), export marketing strategy (1.185) and domestic market characteristics (-1.514) while export to North African destinations is influenced by education (1.112), age of firm (0.184), firm characteristics (3.003), export marketing strategy (1.1843) and domestic market characteristics (-2.150). The study concluded that, export decisions are primarily driven by firm-specific capabilities and market conditions. Managerial education and management characteristics were consistently significant across all destinations, highlighting the importance of human capital in export performance. The study recommends policies aimed at strengthening firm capacity and improving trade relations, particularly with developed markets like the EU member countries.