  The farming domain has seen a tremendous shift towards digital solutions.
However, capturing farmers' requirements regarding Digital Farming (DF)
technology remains a difficult task due to domain-specific challenges. Farmers
form a diverse and international crowd of practitioners who use a common pool
of agricultural products and services, which means we can consider the
possibility of applying Crowd-based Requirements Engineering (CrowdRE) for DF:
CrowdRE4DF. We found that online user feedback in this domain is limited,
necessitating a way of capturing user feedback from farmers in situ. Our
solution, the Farmers' Voice application, uses speech-to-text, Machine Learning
(ML), and Web 2.0 technology. A preliminary evaluation with five farmers showed
good technology acceptance, and accurate transcription and ML analysis even in
noisy farm settings. Our findings help to drive the development of DF
technology through in-situ requirements elicitation.
