Workshop on “Determining the Roadmap for the Use of Artificial Intelligence and Technology in Hazelnut Farming”
The workshop we held on December 9-10, 2024, featured sessions on “Technology and Artificial Intelligence in Global Agriculture,” “Soil, Plant Nutrition, and Water,” “Cloud Architecture and Artificial Intelligence Session,” “Disease and Pest Control and Hazelnut Yield Studies Session,” and “Harvest, Post-Harvest, and Processing Loss Reduction Session.” A total of 21 presentations were made. The workshop was attended by 455 participants from universities, research institutes, industry, and producers.
Walnut farming holds strategic importance in our country’s agricultural production and has a wide-ranging impact, from local development to international trade. Issues encountered in agricultural production, such as climate change, labor shortages, and productivity, necessitate new solutions and approaches. In this context, the integration of artificial intelligence and advanced technologies into agricultural processes plays a vital role in enhancing sustainability and competitiveness.
Today, at this workshop, experts from different disciplines, academics, industry representatives, and farmers have come together to develop a shared vision with the aim of ensuring the effective use of artificial intelligence and technology in hazelnut farming, identifying the obstacles facing this field, and offering feasible solutions. The discussions held and proposals developed during the workshop serve as an important guide for determining the roadmap that will shape our country’s agricultural future.
Since hazelnut production ranks first among Turkey’s agricultural revenues, its strategic planning and management, increasing its productivity and income, and ensuring sustainable agriculture and food security are of great importance. Presentations made for this purpose emphasized the need to develop an AI-based spatial decision support system using findings obtained in the field and in the laboratory through climate data, satellite images, and agricultural data, as well as current methods such as machine learning and deep learning, for sustainable hazelnut farming in the process of adapting to climate change.
This declaration summarizes the outputs obtained during the workshop and presents the key recommendations agreed upon by the participants. Our goal is to develop a pioneering approach in this field by making the most efficient use of the opportunities offered by artificial intelligence and technology in hazelnut farming and to share an important example of sustainable agriculture. To this end, the key areas that will support technological transformation in hazelnut farming were discussed in detail at our workshop. The results of the working groups are summarized as follows:
Data Processing in Hazelnut Farming
Establishing a reliable, comprehensive, and up-to-date data infrastructure is of vital importance for making the right decisions in hazelnut farming. In this context:
- It has been emphasized that sensor-based systems should be widely adopted to collect data on soil, weather, plant health, and productivity;
- A central platform should be established to process the collected data and create an information sharing network that farmers can easily access;
- National standards should be developed to ensure data security and privacy.
The Use of Automation and Robotic Systems in Hazelnut Farming
The use of automation and robotic systems holds great potential for reducing labor requirements and optimizing production processes in hazelnut farming. In this context:
- Developing robotic systems that can be used in harvesting, pruning, and maintenance processes and offering them to farmers at affordable prices,
- Promoting smart irrigation and fertilization systems,
- Encouraging domestic and national automation solutions will strengthen technological independence in agricultural production.
Increasing Hazelnut Yields with Artificial Intelligence and Sustainable Hazelnut Farming
Artificial intelligence-based applications play a critical role in increasing productivity and ensuring environmental sustainability in hazelnut production. In this context:
- Developing AI-supported early warning systems to combat diseases and pests,
- Creating yield prediction models based on hazelnut harvest data and optimizing production processes,
- Supporting sustainable agricultural practices that adapt to climate change with artificial intelligence has been recommended.
- Creating hazelnut farming and artificial intelligence education programs starting at the middle school level for sustainable hazelnut farming.
In conclusion, the outcomes of our workshop provide an important starting point for creating a concrete roadmap for the use of artificial intelligence and technological applications in walnut farming. The consensus is as follows:
- Strengthening cooperation among all stakeholders,
- Increasing the share of artificial intelligence use in agriculture,
- Digitizing data collection and processing processes and creating digital data libraries,
- Accelerating the transformation of academic studies into applications,
- Developing training and incentive mechanisms to increase farmers’ adaptation to technology.
This final report aims to guide a technology-based transformation process in hazelnut farming and further advance Turkey’s leading position in agricultural production. Increasing yield per unit area in hazelnut farming fields, producing high-quality hazelnut seedlings suitable for changing climate conditions, renewing hazelnut orchards that have lost their productive life, and, where possible, carrying out terracing work based on scientific foresight, reducing production costs by transitioning to innovative mechanized farming for hazelnut cultivation, and producing high value-added products using both edible and inedible parts of the hazelnut. Ways to achieve these goals and strategies should be sought by integrating artificial intelligence and technology, and projects in this regard should be given more support.
We respectfully announce this to the public.
