FARMLAND

The increasing demand for efficiency and transparency in Nigeria’s livestock sector has highlighted the need for digital solutions that connect farmers, buyers, and agricultural experts in real time. This project, titled “Design and Development of a Web-Based Livestock Management and Sales Platform” focuses on creating a functional and user-friendly online platform that digitises livestock management, marketing, and consultancy services. The system was developed using a combination of HTML, CSS, and JavaScript for the frontend design, while Django (Python) served as the backend framework and PostgreSQL as the database management system. The platform allows farmers (administrators) to list available livestock, manage bookings, update records, and provide consultancy advice, while buyers (users) can browse livestock listings, add animals to cart, view detailed information, and request consultations. Additional modules, such as a blog for farming guides and a testimonial section, were integrated to enhance engagement and credibility. An Agile development methodology was adopted to ensure iterative design, testing, and improvement throughout the development cycle. The system was deployed on the Render cloud hosting platform, providing online accessibility and scalability for real-world application. Testing results confirmed that the system effectively supports livestock transactions, simplifies communication between stakeholders, and provides a reliable database for record management. Overall, the project demonstrates how information and communication technology (ICT) can enhance market access, transparency, and knowledge sharing in Nigeria’s livestock industry. It contributes to digital agriculture research and provides a scalable model for future integration of payment gateways, analytics, and mobile platforms. Keywords: Web-based system, Livestock management, Digital agriculture, Django, ICT, E-commerce, Render hosting.

This study focused on isolating and identifying fungal species associated with agricultural farmland soil in UNIBEN. Soil samples were collected in sterile plastic ziplock bags from selected agricultural farmlands in Benin City, Edo State, and were subsequently transported to the laboratory for fungal identification. The identification of fungal isolates was conducted using cultural and morphological methods. The results indicated that total fungal counts of soil samples collected from the selected farmlands ranged from 5.70±0.42 to 12.50±1.56. The highest fungal counts were observed in Farm 2 (12.50±1.56), followed by Farm 5 (8.70±0.71), while Farm 4 exhibited the lowest count at 5.70±0.42. The identified fungal isolates included Aspergillus niger, Trichoderma sp., Penicillium sp., Rhizopus arrhizus, and Mucor mucedo. The percentages of occurrence for these fungal isolates varied from 7.14% to 28.57%. Aspergillus niger had the highest occurrence rate at 28.57%, followed by Trichoderma sp. and Penicillium sp., each at 21.43%, while Rhizopus arrhizus had the lowest occurrence at 7.14%. This study emphasizes the importance of understanding the dynamics of fungal populations within these agricultural soils to inform management strategies aimed at enhancing soil health. By monitoring these microbial communities, farmers at these sites can adopt more effective agronomic practices that capitalize on beneficial fungi while minimizing the impact of pathogenic species.