Precision Agriculture & Smart Farming Technology in Türkiye

This hub organizes precision agriculture and smart farming options available for sourcing from Türkiye. It connects field variability and operational goals to GPS guidance, autosteer, section control, variable-rate application, soil and crop mapping, yield monitoring, remote sensing, connected implements, and decision workflows. Hardware compatibility, data quality, agronomic support, subscription terms, and claimed return on investment must be verified for the target farm.

Precision agricultureVariable rateYield maps

Companies mapped through the research dataset

Company links use the same canonical topic IDs as this page and keep researched mappings distinct from legacy editorial inference.

5 companies

Orbiba Robotics

1 product

Orbiba Robotics develops a modular autonomous field-robot platform for mechanical crop operations, transport, targeted treatment and field imaging. The product is represented as a pilot-stage system rather than a fully proven mass-market machine.

İstanbul 2 independent publishers

Doktar

5 products

Doktar develops software, sensing and analytics products for digitising field operations, precision measurement and data-informed agricultural decision-making. The profile records its İstanbul technology presence separately from its current global headquarters.

İstanbul 1 independent publisher

Agrovisio

4 products

Agrovisio develops satellite- and AI-assisted services for crop monitoring, contract farming, agricultural risk assessment and environmental accounting. Its Ankara presence is represented as a Türkiye office rather than its global headquarters.

Ankara 1 independent publisher

Esular

3 products

Esular develops agricultural IoT sensing, irrigation control and greenhouse automation components connected to cloud and mobile management workflows.

İstanbul 1 independent publisher

TABİT Akıllı Tarım Teknolojileri A.Ş.

1 product

TABİT develops farmer communication, digital advisory and AI-supported agricultural services and operates a practical technology-training campus. The company was founded in 2004 and is identified in the Ministry's digital-agriculture ecosystem.

İstanbul / Aydın field campus 1 independent publisher

Türkiye precision agriculture sourcing

Evaluate smart farming by the decision it improves

Avoid buying disconnected technology. Define the baseline, workflow, operator, data path, and measurable result:

Field boundaries, crops, machinery fleet, guidance accuracy, correction service, terminal, CAN/ISOBUS, implement compatibility, and retrofit constraints
Soil sampling, satellite or drone layers, yield maps, prescriptions, variable-rate seeding, fertilizer, spraying, and irrigation workflows
Data capture, calibration, transfer, ownership, export, API access, offline operation, user permissions, cybersecurity, and retention
Training, agronomic interpretation, seasonal support, service coverage, recurring fees, baseline KPIs, trial design, and payback review

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Precision agriculture sourcing questions

Which precision agriculture system should a farm start with?

Start with a costly or inconsistent operation and a measurable baseline. Guidance and section control often address overlap; sensing or variable-rate tools require reliable maps, calibration, agronomic rules, compatible machinery, and a plan to act on the data.

How should smart-farming ROI claims be checked?

Ask for the baseline, assumptions, affected hectares and operations, input and labor prices, accuracy, adoption rate, recurring fees, downtime, training cost, trial method, and a sensitivity range—not one headline payback number.