Abstract

Tanzania's agricultural sector is pivotal to its economy and food security, yet farmers continue to face multifaceted challenges that hinder productivity and sustainable development. While quantitative data from the National Sample Census of Agriculture (NSCA), conducted every five years by the National Bureau of Statistics (NBS), provide valuable insights, the open-ended responses within these surveys remain an underutilized resources for understanding farmers lived experiences. this research aims to systematically analyze these qualitative responses to identify and categorize the predominant challenges faced by Tanzania farmers. Employing advanced text analysis techniques, including natural language processing (NLP), topic modeling, and sentiment analysis, the research will extract recurring themes and sentiments from the textual data. the findings are expected to offer nuanced insights into issues such as access to inputs, market constraints, climate- related challenges, and institutional support deficiencies. By illuminating these perspectives, the research paper seeks to inform policymakers and stakeholders in designing targeted interventions that address the specific needs and concerns of the farming community.