Implemented in:


Primary users:

Food system component(s):

Food system activity/ies:

Type(s) of digital intervention:

More information

Using advanced machine learning algorithms and big data analytics, this application will predict the yield and risk of crops and varieties.


The project will use data from hundreds of on-farm and experimental sites as well as a network of seed companies to develop machine learning models that predict the performance of seed varieties in particular conditions in order to advise maize farmers in Mexico on what to plant.

Estimated number of active users:

  • At inception: 100
  • At time of last report: 100

Evidence of impact

The impact of this invention was widely recognised by a number of accelerator project and European incubators. A spin-off company was formed that deals with commercial application of the service and it received support from the Serbian Innovation Fund, BlockStart H2020 accelerator, as well as Climate KIC, as it was shown to positively contribute to the eco-friendliness of farming. There are already a few major companies that have started to use the technology, and they will support the platform maintenance, so that the services could be offered to a wider range of smallholder farmers as well.

➥ Economic impact: 

Increased yield, Reduced production cost

➥ Environmental impact: 

Increased efficiency in agro chemical use

➥ Social impact: 

I do not know

➥ Technical impact: 

Improved information dissemination

➥ Impact on overall efficiency

Increased efficiency by 26-50%