Women Farmers in Bewoenum: Post-Harvest Loss Training and Real-Time Storage Monitoring

In Bewoenum, a group of women farmers completed a two-day training hosted by AIDA on reducing post-harvest losses and improving on-farm storage decisions. Many of the participants have farmed land their families have worked for generations. The sessions focused on practical changes to storage, handling, and crop care — decisions that affect income and food availability at the household level.

Learning to read the data

Participants were introduced to AIDA's real-time monitoring tools: temperature and humidity sensors and early spoilage alerts. The training went beyond device operation. Farmers learned to interpret the signals and act on them — the decisions that determine whether a harvest holds or fails before it reaches market.

"Before this training, I didn't know that leaving tomatoes in certain conditions could ruin them so quickly," said one participant. "Now I feel confident I can protect my crops and sell them at the right time."

Soil, rotation, and local knowledge

The training also covered on-farm practices: soil fertility management, crop rotation schedules, and organic input methods. The sessions drew on both agronomic research and the knowledge participants already hold — about local crop varieties, seasonal patterns, and storage conditions specific to their region. That combination is deliberate. Indigenous knowledge of local failure modes contains information sensor data alone cannot replicate.

Outcomes

The goal is specific: give farmers information that lets them act before losses occur. That means connecting what the monitoring system reports to what a farmer can do — in time, with enough confidence to change the decision.

"This training has opened my eyes," said another participant. "I now know how to care for my crops so they last longer, and how to make sure my family and community benefit from them."

AIDA is extending this program to additional communities across Ghana, connecting farmers to real-time storage data, spoilage alerts, and post-harvest decision support that makes loss predictable and preventable.