DATA COLLECTION

 

Insights from the Field: Data Collection for the Banana Assist Project

Data collection is a cornerstone of any successful research or development project. For the Banana Assist project, our team embarked on an insightful journey to gather critical information that will shape our mobile application for diagnosing Panama disease and supporting banana farmers and other stakeholders. Here’s a glimpse into our fieldwork experience and the key takeaways.

Where We Collected Data

1. Kawanda Agricultural Research Institute: At the heart of agricultural innovation in Uganda, Kawanda Agricultural Research Institute was an essential stop on our journey. Here, we engaged with leading researchers who shared valuable insights about the prevalence, spread, and management of Panama disease.

2. Senai Laboratory, Busega: At Senai Laboratory, we explored the scientific processes behind banana disease detection and variety identification. We observed how pathogens like those causing Panama disease are analyzed microscopically and learned about advanced detection techniques. Additionally, we gained insights into how banana varieties are enhanced through lab-based methods such as tissue culture, aimed at improving resilience and yield. This experience deepened our understanding of the technical aspects of disease management and variety development, providing valuable knowledge for the Banana Assist project.

3. College of Agriculture and Environmental Studies (CAES) Makerere University: Our visit to CAES provided us with a broader academic perspective on banana farming practices, disease impacts, and the socio-economic challenges farmers face. Discussions with experts and students at the college enriched our understanding of the real-world implications of Panama disease.

How We Collected the Data

Our data collection process was methodical and immersive, combining diverse approaches to ensure a comprehensive understanding of Panama disease:

1. Interviews with Experts
   We conducted in-depth interviews with agronomists, researchers, pathologists, entomologists and laboratory technicians. Their expertise helped us understand the lifecycle of the disease, its symptoms, and potential interventions.

2. Field Visits to Banana Plantations
   Visiting banana fields allowed us to observe Panama disease firsthand. We documented visible symptoms, noted how it spreads, and spoke with farmers about their experiences and challenges in managing the disease.

3. Practical Demonstrations
   In the lab and field, we observed diagnostic processes and treatments. This hands-on exposure helped us gather technical details that will inform the AI models we are developing for disease detection.

4. Questionnaires
   We distributed structured questionnaires to experts to gather diverse perspectives on the disease, crop yield prediction, and advisory information. This helped us capture insights from a broader audience.

5. Document Analysis
   We reviewed scientific publications like articles, research papers among others to understand existing knowledge on Panama disease, including its causes, spread, and control measures as well as yield prediction. This provided a strong foundation for our work.

Lessons Learned

1. Collaboration is Key
   Engaging with experts, institutions, and farmers provided a holistic understanding of the problem. Each stakeholder brought unique insights that complemented the others.

2. The Power of Fieldwork
   Seeing the disease in action gave us a new appreciation for the challenges banana farmers face. This experience motivated us to design a practical and user-friendly solution.

3. Context Drives Innovation
   Our app isn’t just about diagnosing a disease; it’s about understanding its impact and creating tools that empower farmers to take control of their crops and livelihoods.

Images of banana plants affected by panama disease

Images in field