REGIONAL ACTION PLAN SLOVENIA

D.T3.1.5 UM, AE-ROBO May 2022

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Precision agriculture

Precision agriculture (PA), through the use of innovative technologies, is a farm management concept that can be used to increase long-term efficiency, manage uncontrolled change and reduce negative impacts on the environment. PA uses new technologies and innovations, combined with site-specific agronomic expertise. Pa maximizes production efficiency and increases the quality of agricultural produce without increasing environmental burdens. A is defined as an integrated approach to agriculture, which is not only synonymous with precision agriculture technologies (PATs) but is also a systems approach to the whole agricultural production. PA has been developed through the expertise of different disciplines.

The main (overarching) objective is to reduce decision uncertainty in agricultural work processes by focusing on better understanding users and managing uncontrolled change. Suppose variability in the field is a significant source of uncertainty. In that case, it is essential to manage appropriate PA processes that can respond to variable factors at the level of spatial and temporal distribution.

The formation of the PA cycle is further defined by Comparetti (2011), who defines PA methods in the following stages (shown in the following diagram):

• Data collection (measurement of spatially variable soil, crop, or yield parameters within the field and monitoring of local weather conditions)
• Interpretation (integration and mapping of input/output applications with different models)
• Application (application of variable inputs based on the results of data processing)

Fig 1: The precision agriculture cycle.

Precision agriculture technologies, through sophisticated analysis of production resources, create significant opportunities to improve the efficiency of farming operations while contributing to solutions for sustainable agriculture and the environment. The availability of new technologies - farm machinery automation, geospatial tools, sensor and information systems, and others - enables precision farm management. In addition to generating accurate and integrated data sources needed for spatial variability decisions, PATs contribute to data diagnostics that link mapped field locations to the most appropriate decisions on sowing, fertilizer inputs, irrigation, crop protection products, crops, etc. They make it easier to manage inventories and account for costs by automatically recording input usage and tracking data

There is no single typology of PATs. However, it can be defined as follows.

• GPS (global positioning system)
• Geographic information system (GIS)
• Sensor systems
• Variable rate technology (VRT)
• Yield mapping (YM)
• IoT (Internet of things)

In the diagram below, we have outlined some of the basic components of precision agriculture technologies.

Fig. 2: The basic components of precision agriculture technologies.

Precision agriculture has enjoyed a remarkable expansion and popularity in some parts of the world, especially where more intensive farming practices are present. Farms use advanced machinery in a wide range of agricultural sectors. The North American market plays a leading role in PA. The European, Asian, and South American markets also have a significant share. Europe's innovative potential in PA is great and an important lever for agricultural prosperity. In Europe, precision agriculture market was worth USD 2.21 billion in 2021 and projected to grow at a CAGR of 13.2%, to reach USD 3.18 billion by 2026.

Characteristics of Slovenian agriculture

Slovenia is one of Europe's smaller countries, both in terms of land area and population. According to the OECD typology, Slovenia has intermediate (27.2%) and rural regions (72.8%). More than half of Slovenia's land territory is covered by forests, and 34% of its land area is predominantly agricultural. Slovenia is characterized by a dispersed and sparse population and a large number of small settlements. In Slovenia, agriculture with hunting, forestry and fishing contributes 2.3% (2019) to total value-added and 6.9% (2019) to full employment. The share of employment in agriculture is a declining trend and thus decreases year on year.

In Slovenia, decreasing the number of agricultural holdings continues, while the average size of a farming holding increases yearly. On average, a large agricultural holding in Slovenia cultivates 7.0 ha of agricultural land and manages an average of 5.6 ha of forest. Compared to the EU-28, Slovenia still has a very unfavorable size structure of agricultural holdings. The average age of farm owner (manager agricultural holding) in Slovenia amounted to 57 years (2016), which indicates a markedly unfavorable age structure in agriculture. In 2019, 745 companies were operating in the food processing industry, employing 14,627 people. Value-added was EUR 604 million and value-added per employee was EUR 41,270 EUR. Grassland is the most predominant area (84%). Then arable (9%), orchards (intensive and extensive - 4%), vineyards (1.4%), and vegetables (0.7%).

Income in Slovenian agriculture is among the lowest in the EU and represents only around 20% of comparable income in the whole economy. Non-agricultural sources of income are decisive for farming on low-income farms, which can represent a significant part of the income on small farms. Such a poor income situation is the unfavorable structure of Slovenian agriculture with an average of small farms, a large share of land in LFAs, a large percentage of absolute grassland, a large share of non-specialized and self-sufficient farms. Existing processes of Slovenian restructuring agriculture in the direction of increasing income are too slow. Subsidies (direct and LFA payments) are a significant factor in Slovenia, at least partly improving the lower-income situation. Specific agricultural sectors (arable crops, other permanent crops, mixed farming, other grazing livestock), economic farm size (up to EUR 50,000 standard income), and farm location (in LFAs) would generate negative value-added if they did not receive subsidies. Uncertainty about incomes and low productivity leads farms to stagnate investment and, in the long term, to lose competitiveness. Instability is a significant problem in Slovenian agriculture. Fluctuations in prices and/or agricultural volumes can cause liquidity problems for farmers. Uncertainty about incomes and low productivity leads farms to stagnate investment and, in the long term, to lose competitiveness. Uncertainty also causes stagnation or even contraction of agricultural production.

Multiple factors affect the competitiveness and productivity of Slovenian farms; 73.7 % of farms are located in less-favored areas (of which 73.3% - are mountain areas, 10.8% - are areas with natural handicaps, 15.9% - specific constraints), climate change (storms, frost, drought, floods, strong wind, ...) and role of technology (state of machinery/equipment, digitalization, knowledge and innovations in relation to precision agriculture technologies).

There is a strong divide between productivity indicators between EU-27 countries and Slovenia; on average, the divide in EU countries is caused by the introduction of new technologies that substitute the workload. In Slovenia majority of the work is done by manual labour (avg. size 7 ha), and lacking new technology. Farms located in mountain areas face special challenges, shorter vegetation periods and lower income per farmland. Due to the limitations, these farms primarily focus on animal production. An additional factor that limits the possibilities on these farms are the inclinations of farmland that require expensive special-purpose machinery.

Promoting knowledge, innovation, and digitalisation in agriculture in Slovenia

There are several research and training institutions working in the field of Slovenian agriculture and forestry institutions. Public services have been working for decades for the advancement of agriculture and forestry, for better performance of professional tasks in agriculture (livestock farming, crop production, forestry, genetic). Access to formal as well as non-formal education is good. Identified needs and necessary actions in this area:

• Strengthening capacity building and knowledge transfer.
• Strengthening cooperation between the research sphere, consultants, and end-users.
• Strengthening research and development, innovation in agriculture, forestry, and food.
• Retrieved from agricultural advice.
• Digitalisation in agriculture, food, forestry, and rural areas.
• Strengthening digital competences.

Analysis of the factors impacting on the adoption or non-adoption of precision agriculture technologies

The awareness and implementation of new technologies in agriculture, which also includes PA, is reflected in numerous factors in a specific smaller area, such as on a farm, at national or even international level. Based on the literature reviewed, the table below shows the most influential factors.

Factor	Description
The personality and family structure of the farm owner	Age, education, computer usage, skills
Features of the farm	Farm size, farm type, ownership, specialization
Social interactions	Local cultures, local cooperation, human relations – attitude of trusted friends
Economic factors	Return on investment time, the possibility of rental technologies, technology costs
Policy support	Legislation, measures, strategic plans, vision
Supporting institutions and firms	Numbers of supporting institutions and firms
Multidisciplinary cooperation	Active participation of all stakeholders in PA
Features of the technology	Availability of technologies, easiness of use, systems compatibility

SWOT analysis of precision agriculture in Slovenia

With the help of the SWOT analysis, we summarized the current situation and guidelines for the development of precision agriculture in Slovenia in four aspects (advantages, opportunities, dangers, shortcomings). The purpose of the analysis is primarily to assist decision-makers in strategic decisions regarding precision agriculture in the future and to assist in further research in this area. The SWOT analysis included summaries of the state of EU and Slovenian policy measures, characteristics, and structure of Slovenian agriculture, as well as the results of a survey obtained in this project (Transfarm 4.0) on the topic of precision agriculture.