REGIONAL ACTION PLAN TO TRANSFORM THE REGIONAL INDUSTRIAL SPECIALIZATION IN PF IN S3 DRIVING FORCE

D.T3.1.5 MATE PP6 - Hungary

Version 1

09.06.2022

PDF version you can download here.

Introduction - the national guidelines on Precision Agriculture

Hungarian Government launched the Digital Success Program in 2015 to provide benefit for citizen and business from digitalization. Several programs were initiated within the DSP for example: Digital Education Strategy of Hungary, Digital Export Development Strategy of Hungary, Digital Startup Strategy of Hungary, Digital Child Protection Strategy of Hungary. Among these actions DAS - Digital Agriculture Strategy of Hungary is the most relevant to the Transfarm4.0 project.

DAS developed in 2016 by the members of the ICT Association of Hungary (IVSZ) in collaboration with experts and related organizations, and later the Hungarian Government involved it (DAS2.0) to the Digital Welfare Program. DAS aimed to improve the profitability, reduce the environmental impact and increase sustainability of the Hungarian agriculture according to the digitalization, robotisation through agricultural innovations in machinery. The main goals of the DAS are to (i) improve yield and quality according to more efficient while reducing waste (ii) reducing the risk of production according to DSS and (iii) reducing the sales risk. The authors of the DAS (government, non-governmental organizations, actors of the digital “ecosystem”) aimed to widen the application of PF solutions in the following areas: arable crop production, animal husbandry, horticulture, viticulture, fishing and forestry1 . Development of the DAS1.0 was done in 3 phases and 6 steps2 , where the first phase authors evaluated the present situation and opportunities in the context of the national vision of agriculture. The second phase based on the national vision of e-agriculture, the action plan, and on the monitoring and assessment plan. The last third phase was the development of the Digital Agriculture Strategy. According to the methodology designed, there are 5 areas which collaboration improves the efficiency: production, farm, production chain, specialist system and government. The final document provided by the IVSZ was introduced in press (06.19.2016) and at several events. Compared to the DAS1.0 the later version (DAS2.0) defined 5 pillars (in stead of the 5) namely: production, farm and production chain as main elements.

DAS is an important component of Hungary’s Food Industry Concept 2017-2050 which goals were introduced in the D.T1.1.2 Precision farming policy economic review analysis. DAS was supported by several other actions for example the Digital Agrarian Academy aimed to improve the knowledge of the farmers and interested audience in digital agricultural solutions. This project is supported by the Government according to the Innovációs és Technológiai Minisztérium, illetve a Digitális Jólét Nonprofit Kft..

According to the DAS higher education has high importance to introduce digital solutions and the benefit of PF to both the young generation and those who already run a farm. For this reason, MATE, together with several other Hungarian universities, participated in the renewal of Hungarian higher education in accordance with Government Decision 1785/2016. (XII.16.) on the adoption of the "Change of Pace in Higher Education Medium-Term Policy Strategy 2016". This process reached a decisive milestone on 1st February 2021, when the integration of higher education and research at our university was completed by the integration of eleven research institutes and several business organizations, and the new foundation model of maintaining came into being. The main goal of the Digital Welfare Program (DWP) is to ensure that the development of curricula is carried out by the best professional workshops and colleagues available in Hungary - taking into account the specialization aspirations of the government concerning agricultural higher education. This goal can only be fully achieved in cooperation with several universities, including the three model change universities agreed on 1 April by the DWP. According to this Hungarian University of Agriculture and Life Sciences (MATE), the Széchenyi István University (SZE) and the University of Veterinary Medicine Budapest (ÁOTE) joint to a consortium to the development of the DAA curriculum.

Digital Agrarian Academy has the following modules3 :

• E-learning: Within the framework of the Digital Agrarian Academy, continuously expanding educational materials were prepared for those interested. There are currently 30 topics available in the 9 modules below. Additions were made to each topic for producers in the surrounding Carpathian Basin countries. The curriculum is constantly being developed based on changes in technology and user feedback, opinions and needs.
• Knowledge base / Definitions where those expressions are explained which linked to the precision agriculture.
• Digital Demonstration Farms: Understanding digital solutions is the most effective in practice, during operation. Lectures, exhibitions, and knowledge bases help a lot, but a good solution that works well and the honest experiences associated with it provide the most support for an informed decision. Demonstration farms will play a major role in training the farmers. In the framework of the Digital Agricultural Academy, the Digital Demonstration Farms would be selected.
• Digital Service Provider Database Survey: The purpose of creating a digital service provider database is to provide the “students” of the Digital Agricultural Academy with a unified structure about which service provider to turn to if they are looking for a special service provider to facilitate digitization or to build a complex system. The purpose of the database is to help farmers find the best service provider for them to help them implement digital solutions
• Digital public services: This catalog of digital services and online databases operated by the public sector in the agricultural sector. The list is constantly being updated and expanded.

	Topics of DAA (Hungarian)	Topics of DAA (titles in English)*
I.	Farm menedzsment modul	Farm management module
1	Agrár digitális alapismeretek	Basics of digital agriculture
2	Digitális farm menedzsment	Digital farm management
3	Digitális technológia és jog	Digital technology and law
4	Agrár adat felhasználás	Use of agricultural data
5	Digitális megoldások a vidékfejlesztésben	Digital solutions in rural development
II.	Szántóföld modul	Arable plant production module
6	Precíziós szántóföldi növénytermesztés	Precision crop production
7	Precíziós növényvédelem	Precision plant protection
8	Gyakorlati Talajtan gazdálkodóknak	Practical Soil Science for Farmers
9	Talajerőgazdálkodás a gyakorlatban	Soil resource management in practice
III.	Állattenyésztés modul	Livestock module
10	Precíziós állattenyésztés	Precision animal husbandry
11	Precíziós állattenyésztés (szarvasmarha, baromfi)	Precision farming (cattle, poultry)
12	Precíziós méhészet	Precision apiary
13	Precíziós aquakultúra	Precision aquaculture
14	Állategészségügy	Animal health
15	Takarmány	Forage
IV.	Kertészet modul	Horticulture module
16	Precíziós kertészet, zöldég, szántóföldi és üvegház	Precision horticulture, vegetables, arable crops and greenhouses
17	Kertészet gyümölcs	Horticulture, fruit growing
V.	Szőlészet modul	Viticulture module
18	Precíziós szőlészet	Precision viticulture
VI.	Erdészet modul	Forestry module
19	Precíziós erdészet	Precision forestry
VII.	Precíziós gépek modul	Precision machinery module
20	Precíziós gépek üzemeltetése	Operation of precision machinery
21	Robotok a mezőgazdaságban	Robots in agriculture
22	Prediktív gép karbantartás és szervizelés	Predictive machine maintenance and service
VIII.	Távérzékelés modul	Remote sensing module
23	Drón használat	Use of drone
24	Monitoring drón	Monitoring drone
25	Munkavégzésre alkalmas drónok (permetező drón)	Drones suitable for work (spraying drone)
26	Műholdas távérzékelés	Satellite-based remote sensing
IX.	Digitális Termelői Piac modul	Digital Producer Market Module
27	E-kereskedelem és sharing economy az agráriumban	E-commerce and sharing economy in agriculture
28	Élelmiszeripar, minőségbiztosítás (digitális nyomonkövetési rendszerek)	Food industry, quality assurance (digital tracking systems)
29	Életmód, táplálkozás	Lifestyle, nutrition
30	Elsődleges termelői feldolgozás higiéniája	Hygiene of primary producer processing

*Learning materials of the Digital Agrarian Academy is in Hungarian language, here we provide the English translation of the titles only

What is the Intelligent Specialization Strategy (RIS3)?

“Conceived within the reformed Cohesion policy of the European Commission, Smart Specialisation is a place-based approach characterised by the identification of strategic areas for intervention based both on the analysis of the strengths and potential of the economy and on an Entrepreneurial Discovery Process (EDP) with wide stakeholder involvement. It is outward-looking and embraces a broad view of innovation including but certainly not limited to technology-driven approaches, supported by effective monitoring mechanisms.” 4

According to the European Commission Smart Specialization Platform Hungary has two S3 thematic platforms:

• Artificial Intelligence and Human Machine Interface (AI & HMI)
• SME integration to Industry 4.0

The main S3 priorities are:

• Clean and renewable energies
• Healthy local food
• Inclusive and sustainable society
• Healthy society and wellbeing
• Agricultural innovation
• Sustainable environment
• ICT and information services
• Advanced technologies in the vehicle and other machine industries

Concerning the Transfarm4.0 there are 3 priorities Agricultural innovation, Sustainable environment, and Advanced technologies in the vehicle and other machine industries.

According to the Smart Specialisation Platform5 these priorities described as:

• Agricultural innovation: The aim of the priority is to advance and establish the innovations facilitating sectoral renewal from the agricultural knowledge centres through producer undertakings to individuals, with the aim of enhancing the innovation potential of the sector. Such complex agribusiness developments should be implemented that represent an opportunity to use innovative R&D solutions in crop production and protection technologies, in addition to animal production and veterinary medicine.
• Sustainable environment: The priority is aimed at promoting the sustainability of the environment and natural resource management (e.g. environmental biotechnology) through the research and development of modern technologies and the implementation of the environmental industry and sectoral innovation. In addition to the advanced innovative water treatment technologies and waste water treatment and waste management, priority will be given to the non‐pipe technologies.
• Advanced technologies in the vehicle and other machine industries: This is a priority which covers several segments of the machine industry RDI, whose priority (but non‐ exclusive) objective is to develop the vehicle industry from the development of vehicle components to the different branches of machine production (including, but not limited to, agricultural, food processing, precision and household machinery).

National Smart Specialization Strategy of Hungary

Hungarian S3 objectives are introduced in the National Smart Specialisation Strategy published in November 20146 and in July 20217 . Earlier version includes a situation analysis details the general situation of Hungary, in more particular society, sustainability, GDP and added value. Within the RDI status it introduces the results from 2014, where Hungary was considered as a moderately innovative country. As one of the main factors of innovation higher education research organizations were analyzed. Results showed that health science, natural sciences and technical sciences are the most important areas. Linked to the Transfarm4.0 project the agricultural science showed lower importance with 9% of the distribution of the R&D expenditures of higher education by areas of science. Concerning the collaboration between higher education research institutions and companies the highest was in the area of agricultural sciences, as more than 50% of the projects are carried out in collaboration. Hungarian Academy of Sciences is one of the major actor in research and development in this way its role was also evaluated. According to the distribution of expenditures in the major research projects of the HAS by areas of science material sciences within the technical sciences and the physical and biological sciences within the natural sciences have the highest shares, while cultivation, horticulture, forestry and hunting received only a minor share (0.8%) of the expenditures, while according to the distribution of expenditures in the major research projects of the HAS by sectors, agriculture forestry and fishing received higher (4.2%) share. Results of the National Smart Specialisation Strategy showed that the large companies spend 30% more on research and development than the micro, small and medium sized enterprises. The expenditure was different according to the sectors: expenditure per researcher was the highest in manufacture of pharmaceuticals, medical chemical and botanical products. Linked to the Transfarm4.0 project it is important to highlight manufacture of machinery and equipment had high expenditure too. Report showed the proportion of the innovative companies are the highest (more than 70% of the companies were considered as innovative) in the manufacture of pharmaceuticals, medical chemical and botanical products, while less than 40% was in the case of manufacture of machinery and equipment. The report introduces the international outlook and international trends and among others the relations with the neighboring countries. SWOT analysis details the Strengths Weaknesses Opportunities Threats concerning the (i) education, training, research background, (ii) research and innovation environment, organisations, infrastructure and services, and (iii) financing. The report introduces governance structure within this the national processes before the National Smart Specialisation Strategies and the S3 stakeholders. Both triple helix and quadruple helix grouping of actors were designed, according to the following structure of the actors:

Science

• Higher education institutions
  • Universities
  • Colleges
• Research institutes
  • Academic and sectoral (public or private) research institutes
• Knowledge centres
  • Science o Higher education institutions ▪ Universities ▪ Colleges o Research institutes ▪ Academic and sectoral (public or private) research institutes o Knowledge centres

Government

• Government and local government organisations
  • Ministries
  • National government offices
  • County governments
  • County government offices
  • Local governments of cities of county rank

Economy

• • Innovative enterprises
  • Large enterprises
  • SMEs (including micro, start‐up and spinoff businesses)
  • Non‐profit companies
• Technology transfer organizations and accredited clusters
  • Innovation and technology transfer offices
  • Clusters

Civil organisations

• • Trade associations
  • Interest representation bodies (e.g. national and county chambers of commerce and industry)
  • Other non‐profit organisations

National priorities in the phase (2014-2021) divided into sectorial priorities and horizontal ones.

The sectorial priorities are:

Healthy society and wellbeing

• understanding diseases, early diagnosis, advanced medical and instrumental therapies, clinical methods, pharmaceutical, research and development, innovative health industry and health, tourism solutions

Advanced technologies in the vehicle and other machine industries

• machine industry RDI, advanced production technology systems, advanced materials and technologies (technical materials science, materials technology, nanotechnology, mechatronics and electronics))

Clean and renewable energies

• green energy – renewables and bio‐energy, nuclear energy, energy efficiency

Sustainable environment

• natural resource management, advanced environmental technologies

Healthy local food

• food processing, locally produced and processed food of high added value

Agricultural innovation

• agriculture, forestry, hunting, aquaculture and water management, horticultural technologies, agricultural biotechnology

The horizontal priorities are:

ICT (infocommunication technologies) & Services

• infocommunication technologies in support of the sectoral priorities, infocommunication technologies and services

Inclusive and sustainable society, viable environment

• education and training, health‐conscious education and, prevention, awareness raising, promoting entrepreneurial skills, development of cooperation, networking, organization and management development, social innovation, connection to local and regional development programmes, regional development, tourism

National selected priorities - selected from a first stage of prioritization - in the latest version of the S3 (2021-2027) introduced according to a priority description, identification of the target sectors, areas for development, and priority objectives. National economic priorities

• Cutting-edge technologies
• Health priority
• Digitisation of the economy priority
• Energy, climate priority
• Service priority
• Resource-efficient economy priority
• Agriculture, food priority
• Creative industries priority

These selected priorities are supported by the following horizontal priorities:

• Training, education
• Public sector and university innovation priority

The opportunities for the PA proposed in the S3 Hungary -2021-2027 highlighted the smart agri-food priorites

In relation to the Trasfarm4.0 project cutting-edge technologies and agriculture, food national selected priorities have the closest relevance. Former one aims to develop – among others- cutting-edge technologies such artificial intelligence, big data, and AI-based data analysis. These technological innovations are in line with the aims of the Transfarm4.0 project pilot actions where data evaluation innovations support the growers to make arable crop cultivation, fruit growing or viticultural decisions. In our relation, these innovations would help the growers to reduce environmental impact, to increase the yield and improve the quality. In more particular, decision support system would provide benefit in planting, sowing, nutrient supply, plant protection (spraying), harvest, canopy management. In the agriculture, laborshortage is a more frequent difficulty in many sectors. In viticulture pruning, canopy management, cover crop maintenance and harvest are the main operations where mechanization, automatisation, robotics, and decision support systems are useful innovations. According to the S3 strategy the target groups of this priority are the universities, research institutes, businesses, non-profit sector.

The main objectives of this priority are the following ones, all would be linked to PA: