This blog post is based on the 30th Practice Abstract from the second batch of Farmtopia Practice Abstracts.
Precision agriculture is often seen as something designed for large farms with expensive equipment and complex digital infrastructure. RAMASphere, developed through the Farmtopia project, demonstrates a different approach: small and medium farms can introduce precision farming gradually, starting with their most pressing needs and investing in technology step by step.
The approach was tested on Kievo, an 11-hectare family farm growing vines and cereals in the Ovche Pole region of North Macedonia, where drought, erosion-prone soils and hot summers create challenging conditions for farming.
The challenge: making precision farming accessible
Small and medium farms often rely on uniform fertilisation, calendar-based spraying and conventional irrigation. While these practices are familiar, they can result in inputs being applied where and when they are not needed.
For a farm with limited resources, the cost of unnecessary fertiliser, plant protection products or irrigation can quickly add up. At the same time, investing in a complete precision farming system from the start may simply be too expensive or complex.
RAMASphere addresses this challenge through a step-by-step digitalisation model, allowing farmers to begin with advisory support and gradually introduce technology where it provides a clear benefit.
Creating a digital model of the farm
At the centre of the approach is RAMAS, AgFutura’s digital advisory platform.
The process begins with a Farm Capacity Assessment, which maps the farm’s parcels and identifies its specific needs. The farm can then select the advisory programmes most relevant to its production, including:
- seeding;
- soil management;
- nutrition;
- plant protection;
- irrigation;
- and harvesting.
Each parcel becomes part of a digital farm model, allowing an agronomist to support the farmer remotely.
As part of the Farmtopia pilot, RAMAS was upgraded with the Farmtopia Data Integration Module, which brings together additional weather, satellite and pest-risk information. This gives the advisor a broader set of data for assessing field conditions and providing recommendations.
Technology is added where it makes sense
Rather than requiring the farmer to purchase a complete precision farming setup, RAMASphere follows a gradual investment approach. At Kievo, targeted investments were introduced after identifying the farm’s needs. These included:
- solar energy for irrigation;
- and a GPS autosteering system.
The aim was to ensure that new equipment supported the advisory recommendations and could be used precisely where it provided value.
This creates a practical cycle: assess the farm → identify the need → test the approach → invest where it pays off → expand gradually.
What did the pilot demonstrate? The Kievo pilot showed measurable improvements in several areas.
- More targeted crop protection: Zone-based fertilisation and risk-based spraying replaced more uniform approaches. In the vineyard, the number of spray applications fell from 9 to 6, a reduction of approximately 33%. Farm-wide pesticide use decreased by 15%.
- Improved cereal production: The pilot cereals reached approximately 2.85 tonnes per hectare, representing an increase of 22% compared with the baseline. The results indicate the potential of combining more precise nutrition and plant protection decisions with field-specific advisory support.
- Lower running costs: Solar-powered irrigation and optimised farm operations contributed to estimated savings of approximately €1,965 per year, exceeding the project’s target of €1,500.
- Faster decision-making: With remote digital advisory support, recommendations could reach the farmer within hours rather than days. Farmer satisfaction was also reported as being above the project target.
A practical model for small farms
One of the main lessons from RAMASphere is that precision farming does not have to mean transforming the entire farm at once. A small farm can begin with a capacity assessment and soil analysis, introduce one advisory programme and then evaluate the results. Equipment can be added when there is a clear operational or financial reason to do so.
This approach can also benefit advisors and cooperatives. A single advisory team can potentially support multiple farms remotely, making digital advisory services more scalable without requiring each farmer to build their own technical expertise.
Practical recommendations: For farmers interested in introducing precision farming, the RAMASphere approach suggests:
- Start with a Farm Capacity Assessment to understand the farm’s actual needs.
- Carry out soil analysis and establish a reliable baseline.
- Choose the advisory programmes that address the most important challenges first.
- Introduce technology gradually rather than investing in a complete system immediately.
- Test whether an investment provides measurable benefits before expanding it.
- Combine farmer experience with digital information and agronomic advice.
- For advisors and cooperatives, consider remote support models that allow one team to assist multiple farms.
The key is to make digitalisation work for the farm’s specific needs, rather than adopting technology simply because it is available.
Precision farming does not have to start big: RAMASphere demonstrates that precision farming can be introduced progressively, even on a small family farm.
The experience of Kievo shows how digital advisory services, integrated weather and satellite information, targeted investments and renewable energy can work together to reduce input use, improve production and lower operating costs.
For small and medium farms, the message is simple: start with the problem, test the solution and invest where the results justify it.
Conceptual workflow of the RAMAS platform
About this Practice Abstract
Official title: RAMAS: An Integrated Digital Advisory Platform for Step-by-Step Precision Farming on Small and Medium Farms (RAMASphere SIP)
Publisher: AgFutura Technologies (AGFT)
Authors: Mario Petkovski; Filip Kamchev; Jovana Milosavljeva; Angela Zhivachka
Contact: darko.jancheski@agfutura.com