HomeBlogBlog postsHow Drones and AI Can Help Small Farms Make Faster Crop Decisions: Farmtopia’s 18th Practice Abstract

How Drones and AI Can Help Small Farms Make Faster Crop Decisions: Farmtopia’s 18th Practice Abstract

This blog post is based on the 18th Practice Abstract from the second batch of Farmtopia Practice Abstracts.

For small industrial hemp farms, knowing what is happening across a field can be difficult. Traditional soil and leaf sampling provides useful information, but it is based on individual sampling points, requires repeated fieldwork and can take time before laboratory results are available. When information arrives too late, farmers may miss the best opportunity to adjust irrigation or fertilisation. Differences within a field can also remain hidden when the same treatment is applied across the entire area.

Farmtopia’s SIP explored how drone and satellite technologies, sensors and artificial intelligence can provide farmers with more detailed and timely information about their fields. 

Combining different sources of information

Hempsight combines several types of data to assess soil quality and monitor crop development.

The system uses:

  • Drone-based hyperspectral imaging
  • Satellite observations
  • Soil-moisture sensors
  • Targeted soil and leaf laboratory samples
  • AI-based data analysis

These different sources are processed to create maps showing crop condition, the distribution of macro- and microelements, water requirements and emerging areas of crop stress.

Instead of receiving only individual sampling results, farmers can see how conditions vary across their fields and use this information to target interventions.

From field maps to farm decisions

The information generated by Hempsight is designed to support practical decisions.

Farmers can use the maps to identify areas that may require additional irrigation or fertilisation, as well as zones that need closer scouting.

The service is available on a pay-per-use basis, meaning that farms do not necessarily need to purchase their own specialised drones, hyperspectral cameras or data-processing infrastructure.

This approach can be particularly relevant for smaller farms, where investing in specialised equipment may not be economically viable.

What happened during the pilot?

During the first piloting phase at Šironija Farm in Lithuania, intermediate results compared with the pre-ADS baseline showed:

  • 15% reduction in irrigation costs, from €400 to €340 per hectare per year
  • 10% reduction in agrochemical inputs, from 2.0 to 1.8 tonnes per hectare per year
  • 3% increase in productivity, from 0.40 to 0.41 tonnes per hectare per year

The farmer also used nutrient and irrigation maps to target interventions more precisely rather than treating the entire field uniformly.

During the following cultivation period, a test area that received additional nitrogen produced a visibly better harvest, providing further practical feedback on the use of the recommendations.

The pilot also showed how earlier identification of water and nutrient stress can support faster decisions and more targeted field planning.

These results should be understood as pilot observations rather than effects that can be attributed solely to the Hempsight system, as farm performance can also be influenced by weather, crop conditions, management decisions and other factors.

How can small farms use the approach?

Farmers interested in this type of technology do not necessarily need to start by purchasing their own equipment.

A pay-per-use service can provide access to drone and hyperspectral capabilities without the initial investment in specialised hardware.

For routine monitoring, satellite data can provide regular observations. Hyperspectral drone flights can then be scheduled around important decision points, such as:

  • Early crop establishment
  • After irrigation or fertilisation
  • Periods of rapid crop growth
  • When water or nutrient stress is suspected

Farmers can prioritise fields with significant spatial variability or recurring nutrient and moisture problems.

Where possible, receiving zone maps quickly after a flight can help ensure that the information remains useful for timely field interventions.

Sharing the service can make it more accessible

The cost of specialised monitoring can still be a barrier for individual small farms.

Neighbouring farms, cooperatives and advisory organisations could therefore share the service and coordinate flights across several holdings.

This can make advanced crop monitoring more accessible while spreading the cost of the service across multiple users.

Towards more targeted crop management

The Hempsight pilot demonstrates how combining remote sensing, field measurements and AI can provide a more detailed picture of what is happening within a crop field.

For small farms, the value is not simply in collecting more data. It is in turning those data into maps and recommendations that can support timely, targeted decisions on irrigation, fertilisation and crop monitoring.

Explore Hempsight: The Hempsight platform provides further information about the digital solution: Hempsight platform

Based on Farmtopia Practice Abstract 18

This blog post was created from Practice Abstract 18: “Drones Over Crop Fields: Faster Soil and Crop Decisions for Small Farms”, part of the second batch of Farmtopia Practice Abstracts.

Publisher: UAB “Beta Via”
Author: Sonata Adomaviciute-Grabusove

Contact: sonata@betavia.lt

Democratizing Digital Farming for All – FARMTOPIA’S PATH TO EMPOWERING SMALL FARMS WITH DIGITAL TECHNOLOGIES

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