HIT Award
Start-Up Lab

The idea started from Gabriele, a real producer of blueberries, who felt the need for a tool to speed up the blueberry harvesting process. In particular, we looked at the distribution chain of these small fruits, looking for a solution to shorten the distance between farmers and consumers, reducing the dependence of the former on large consortia. By combining the experience of those who work in the sector, with the skills in the field of artificial intelligence and seasoning everything with numerous market validations, we have come to give birth to the idea behind our project: a small machine that uses machine learning to do efficient and economic quality control.

The problem

A problem that we have found to be deeply felt by Italian farmers is the extreme slowness of the harvesting and quality control process, as regards blueberries. Even today, these small fruits are divided between good and bad manually by those who work in the fields, making business owners spend a lot of money and time. Furthermore, the average size of the land cultivated with blueberries in Italy is just 2 hectares, much lower than the American average, where industrial solutions are already applied in order to automate the harvesting process. For this reason, we needed not only to speed up this process, but also to create a machine that had reduced size and cost.

The solution

In the early design stages, we carried out a long validation process, concerning both the analysis of farmers' needs and the economic evaluation of the costs to be incurred. From here, we came up with the idea of a machine capable of exploiting artificial intelligence to recognize blueberries damaged from edible ones. In particular, the fruits collected in special baskets descend through a chute to a divider which is activated by sensors. The small size, ease of use and cost-effectiveness are the strengths of our solution, designed to be used directly by farmers. Furthermore, by standardizing and increasing the precision of quality control, it is possible to reduce food waste even during the very first step of the production chain.

  • Goldberry Project
  • Goldberry Machine
Project members
Giada Ottavian
CEO & Marketing
Gabriele Osler
Quality Manager
Trisha Kibaya Sewava
Business Developer
Mario Alberto Macchioni
Financial Manager
Meriem El Batoul Abdellaoui
Market Analyst
Leonardo Lucio Custode
Daniele Basso
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