Report on testing and Valorisation of the toolbox instruments

2 NOVASOIL INNOVATIVE BUSINESS MODELS FOR SOIL HEALTH Grant agreement ID: 101091268 Testing and Valorisation of the toolbox instruments Deliverable D 3.7 Project NOVASOIL Project title INNOVATIVE BUSINESS MODELS FOR SOIL HEALTH Work Package 3 Testing and development of a toolbox for incentives Deliverable 3.7 Period covered 01/02/2024-30/07/2025 Publication date 29/07/2025 Dissemination level PU Organisation name of lead beneficiary for this report New Bulgarian University Authors Dimitre Nikolov, Ekatherina Tzvetanova-Georgieva, Ivan Boevsky, Martin Banov, Krasimir Kostenarov, Plamem Dragnev Contributors EVENOR Ref. Ares(2025)9374077 - 31/10/2025 3 QUALITY ASSURANCE PROCEDURES This document has been reviewed by the NOVASOIL consortium according to the national reports and comments received. TABLE REVISION HISTORY DELIVERABLE Row Version Date Reviewers Description 1 V1.0 29/07/2025 NBU Draft version circulated by email 2 V1.1 30/07/2025 EVENOR Minor commentes in Summary and Conclusions 3 4 Project Consortium Nº Participant organisation name Countr y 1 EVENOR TECH SLU ES 2 LEIBNIZ-ZENTRUM FUER AGRARLANDSCHAFTSFORSCHUNG GE 3 ZEMNIEKU SAEIMA LV 4 NEW BULGARIAN UNIVERSITY BU 5 CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR 6 KOBENHAVNS UNIVERSITET DK 7 TECHNISCHE UNIVERSITAET MUENCHEN GE 8 ASSEMBLEE DES REGIONS EUROPEENNES FRUITIERES LEGUMIERES ET HORTICOLES FR 9 ISTITUTO DELTA ECOLOGIA APPLICATA SRL IT 10 UNIVERSITA DEGLI STUDI DI FERRARA IT 11 WAGENINGEN UNIVERSITY NL 12 CENTRE OF ESTONIAN RURAL RESEARCH AND KNOWLEDGEEESTI EE 13 UNIVERSIDAD POLITECNICA DE MADRID ES 14 UNIVERSITA DI PISA IT 15 ASOCIACION AGRARIA JOVENES AGRICULTORES DE SEVILLA ES 16 UNIVERSITY OF LEEDS GB 5 Table of contents List of figures .............................................................................................................................................. 7 List of tables ................................................................................................................................................ 8 List of abbreviations ............................................................................................................................. 10 Summary ...................................................................................................................................................... 11 1 Introduction ....................................................................................................................................... 11 1.1 Context of WP 3 objectives .................................................................................................. 11 1.2 Connection with the other WPs ................................................................................. 12 1.3 Purpose and scope of the document ...................................................................... 13 1.4 Process of development ................................................................................................. 14 2 Policy brief......................................................................................................................................... 14 3 Testing and valorization ........................................................................................................... 18 3.1 Methodology ................................................................................................................................. 18 3.2 Country analysis .......................................................................................................................... 21 3.2.1 Bulgaria case study ............................................................................................................ 21 3.2.2 Estonia case study ............................................................................................................26 3.2.3 Germany case study ......................................................................................................... 31 3.2.4 Italian case study 1 ............................................................................................................ 37 3.2.5 Italian case study 2 ........................................................................................................... 41 3.2.6 Italy case study 3 ............................................................................................................... 45 3.2.7 Latvia case study 1 ............................................................................................................ 47 3.2.8 Latvia case study 2 ............................................................................................................ 52 3.2.9 Spain case study 1..............................................................................................................56 3.2.10 Spain case study 2 ...........................................................................................................62 3.1 Integrated Analysis of Digital Tools by business model .................................... 68 3.1.1 Business model type: Value chain ........................................................................... 68 3.1.2 Business model type: Agricultural production/value chain ..................... 71 3.1.3 Business model type: Collective and value chain .......................................... 72 3.1.4 Business model type: Agricultural production ............................................... 73 3.1.5 Business model type: Forest management ..................................................... 74 4 Ecological and human impact of the soil health business models ............. 74 4.1 Methodology ................................................................................................................................ 74 4.2 Analysis of the results ............................................................................................................ 76 4.2.1 Bulgaria ................................................................................................................................... 76 4.2.2 Italy .............................................................................................................................................77 6 4.2.3 Italy 2 ........................................................................................................................................ 78 4.2.4 Spain ........................................................................................................................................ 79 4.2.5 Germany ................................................................................................................................ 80 4.3 Conclusion Based on CO₂ Emissions Across Countries and Production Systems ................................................................................................................................................... 81 5 Feedback from CoP ................................................................................................................... 82 5.1 Methodology ................................................................................................................................ 82 5.2 Analysis ............................................................................................................................................ 83 5.3. Conclusions ................................................................................................................................. 86 6 Conclusions .......................................................................................................................................... 88 Resources .................................................................................................................................................. 89 Acknowledgment ................................................................................................................................. 90 Annexes ....................................................................................................................................................... 91 Annex 1 ..................................................................................................................................................... 91 7 List of figures Figure 1 NOVASOIL digital toolbox ............................................................................................. 14 Figure 2. Result of the assessment of DT’s according “Environmental care” criteria ........................................................................................................................................................... 23 Figure 3. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria .................................................................................................................. 24 Figure 4. Result of the assessment of DT’s according “To protect food and health quality” criteria ........................................................................................................................ 25 Figure 5. Result of the assessment of DT’s according to Fostering knowledge ecosystem services .............................................................................................................................. 28 Figure 6. Result of the assessment of DT’s according “To improve the position of farmers in the food chain” criteria .........................................................................................29 Figure 7. Result of the assessment of DT’s ........................................................................... 30 Figure 8. Result of the assessment of DT’s according “Climate change” criteria ........................................................................................................................................................................... 33 Figure 9. Result of the assessment of DT’s according “Environmental care” criteria .......................................................................................................................................................... 34 Figure 10. Result of the assessment of DT’s according “Fostering knowledge” criteria ........................................................................................................................................................... 35 Figure 11. Result of the assessment of DT’s according “To ensure a fair income for farmers” criteria ...............................................................................................................................36 Figure 12. Result of the assessment of DT’s according “Environmental care” criteria ...........................................................................................................................................................39 Figure 13. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria .................................................................................................................. 40 Figure 14. Result of the assessment of DT’s according “Environmental care” criteria .......................................................................................................................................................... 43 Figure 15. Result of the assessment of DT’s according “protect food and health quality” criteria ....................................................................................................................................... 44 Figure 16. Result of the assessment of DT’s according “Environmental care” criteria .......................................................................................................................................................... 50 Figure 17. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria .................................................................................................................... 51 Figure 18. Result of the assessment of DT’s according “Environmental care” criteria ........................................................................................................................................................... 55 Figure 19. Result of the assessment of DT’s according “Climate Change” criteria ...........................................................................................................................................................................59 Figure 20. Result of the assessment of DT’s according “Environmental care” criteria .......................................................................................................................................................... 60 Figure 21. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria ................................................................................................................... 61 Figure 22. Result of the assessment of DT’s according “Environmental care” criteria ...........................................................................................................................................................65 Figure 23. Result of the assessment of DT’s according “Protecting food and health quality” criteria ....................................................................................................................... 67 8 List of tables Table 2: Estimate how DTA for every Barrier/factor will affect variable costs and income for your case study ............................................................................................................. 18 Table 3: List of criteria and short names ................................................................................. 20 Table 4: Rank by placing a number from 1 to 3 for each DT according to each pressure where 1 means it ranks highest and 3 - the lowest. ..................................... 21 Table 5: DTA analysis of social and/or economic barriers trough variable costs and income................................................................................................................................................ 22 Table 6: Ranking the DT’s according different pressures .............................................26 Table 7: Analysis of social and/or economic barriers trough variable costs and income .......................................................................................................................................................... 27 Table 8: Ranking the DT’s according to different pressures ........................................ 31 Table 9: DTA analysis of social and/or economic barriers trough variable costs and income................................................................................................................................................. 31 Table 10: Ranking the DT’saccording tog different pressures ................................... 37 Table 11: DTA analysis of social and/or economic barriers trough variable costs and income............................................................................................................................................... 38 Table 12: Ranking the DT’s according to different pressures .................................... 41 Table 13: DTA analysis of social and/or economic barriers trough variable costs and income............................................................................................................................................... 42 Table 14: Ranking the DT’s according different pressures .......................................... 45 Table 15: DTA analysis of social and/or economic barriers trough variable costs and income............................................................................................................................................... 46 Table 16: Ranking the DT’s according to different pressures .................................... 47 Table 17: DTA analysis of social and/or economic barriers trough variable costs and income............................................................................................................................................... 48 Table 18: Ranking the DT’s according different pressures ........................................... 52 Table 19: DTA analysis of social and/or economic barriers trough variable costs and income................................................................................................................................................ 53 Table 20: Ranking the DT’s according to different pressures ....................................56 Table 21: DTA analysis of social and/or economic barriers trough variable costs and income................................................................................................................................................ 57 Table 22: Ranking the DT’s according different pressures ..........................................62 Table 23: DTA analysis of social and/or economic barriers trough variable costs and income................................................................................................................................................63 Table 24: Ranking the DT’s according to different pressures ................................... 68 Table 25: Classification Scale for Carbon Footprint Impact in Agriculture (CO₂ Emissions per Hectare per Year) .................................................................................................. 75 Table 26: CO2 imact of different case studies and crops ............................................. 78 Table 27: List of the case studies ................................................................................................. 82 Table 28: Summary of the responses to “Is the proposed Toolbox easy to understand?” ........................................................................................................................................... 83 Table 29: Summary of the responses to “Do you find the Toolbox useful for soil health business models?” ............................................................................................................... 84 Table 30: Summary of the responses to “Do you understand the goal of the Toolbox?” .................................................................................................................................................... 84 9 Table 31: Summary of the responses to “Is the Toolbox generally easy and intuitive to use?” .................................................................................................................................... 85 Table 32: Average Usefulness Rating by Tool Across Each Business Model .... 85 10 List of abbreviations WP Working package EU European Union DT Digital tool AHP Analytic Hierarchy Process SWOT Analysis of strengths, weaknesses, threats, and opportunities DHK Tool 1 - Digital knowledge hub DTA Tool 2 – Digital for analysis for soil health business models DST Tool 3 – Digital support tool for soil health business models 17 production process. This case illustrates that even advanced, mechanized soil strategy can have relatively high emissions if nitrogen management is not optimized. In Bulgaria (Integrated production in the vineyards with vinery and rural tourizm, Value chain), the vineyard soil strategy represented shows a positive carbon balance, with a net sequestration rate of 0.4 tCO₂eq/ha/year. This places the farm within the low-emission or even climate-positive category, meaning it acts as a carbon sink rather than a source. This is a highly favorable outcome from a climate mitigation perspective. The following elements likely contribute to this positive performance: Perennial vegetation (vineyards) helps maintain continuous ground cover and carbon sequestration. No emissions are reported from land-use change, which avoids large upfront carbon losses. No forest area is impacted, and there’s no indication of deforestation or degradation. Presumably low levels of disturbance and biomass loss, since no values are reported there. In conclusion, while most farms operate within the same emission category, their performance in terms of carbon efficiency and sustainability differs greatly. Orchards like vineyards, as well as low-input crops such as alfalfa, demonstrate strong climate performance. In contrast, input-intensive crops like tomatoes or wheat grown under high nitrogen regimes show higher emissions both per hectare and per unit of output. Compared to farms in different BMs in Italy, Spain, and Germany, where emissions range from 1.35 to 5.33 tCO₂eq/ha/year, this vineyard clearly outperforms in terms of carbon efficiency. It joins the Bulgarian vineyard in the earlier analysis as an example of climate-smart viticulture, capable of both agricultural production and net carbon sequestration. 2.3. CoP evaluation of NOVASOIL toolbox The NOVASOIL Toolbox, consisting of three digital tools (DHK, DTA, and DST), was assessed across CoP in partner countries for clarity, usability, usefulness, and policy relevance. DHK is widely appreciated for its clear structure and informative content. Users value its strong foundation in soil health knowledge, particularly as an accessible entry point for farmers and practitioners. It is recognized as the most user-friendly tool, offering a smooth experience that can be further enhanced with improved content organization and clearer formatting. DTA stood out as the most valuable tool for soil health business models, especially in agricultural production. When accessible, it was praised for its ability to guide decision-making and optimize resource use. Stakeholders viewed these as solvable and were confident in the tool's strong long-term utility. DST was acknowledged for its advanced analytical capabilities and potential to support detailed field-level assessments. While more complex, it holds 18 strong promise for expert users and researchers, and with improved explanations and simplified language, it can be made more accessible to a broader audience. Across all tools, participants highlighted the benefit of integrating them into agricultural policy and education. They recommended their use in CAPrelated subsidy assessments, advisory services, and training programs, emphasizing the tools’ potential to improve digital literacy and soil stewardship across rural communities. The suggestion to implement pilot farms and demonstration projects further reflects confidence in the tools' realworld applicability. 3 Testing and valorization 3.1 Methodology To understand how the digital tools developed in task 3.1, task 3.3 and t 3.5 can help overcome the social and economic barriers to implementing soil health business models, a three-step methodology has been developed. This methodology begins with the identification of the main incentive for each case, as presented in the D3.4 Report on New Incentives Soil Health Business Models. It then proceeds to identify and evaluate the related opportunities using BOCR (Benefits, Opportunities, Costs, and Risks) analysis. From the full list of opportunities, only those with significant economic and social relevance—as identified by stakeholders—are selected. The lack of progress in applying these opportunities and achieving related economic and social development is considered a key barrier to improved soil health managementFor the testing and valorisation phase, stakeholders assess how the application of DTA could impact variable costs and income, thereby supporting the effort to overcome these barriers (table 2). Table 1: Estimate how DTA for every Barrier/factor will affect variable costs and income for your case study Influence on variable costs Influence on income Barriers/factor s Decreas e No impac t Increas e Decreas e No impac t Increas e Barrier 1 Barrier 2 … Barrier n Place “x” on every row once for variable costs and once for income. The second step in the methodology involves the evaluation of the following three digital instruments: 19 • DHK: Digital Hub of Knowledge • DTA: Digital Tool for Analysis • DST: Decision Support Tool These tools are assessed for their potential to support the delivery of various ecosystem services (such as carbon sequestration, clean water, clean air, biodiversity), based on a set of functions that reflect social preferences. The analysis begins by referring to the strategic criteria defined in Deliverable D3.4. Each partner, based on the specific characteristics of their business model and case, selects strategic objectives that align with the policy goals of the Common Agricultural Policy (CAP). These objectives are drawn from the 10 CAP objectives (2023–2027), listed below: 1. Ensure a fair income for farmers 2. Increase competitiveness 3. Improve the position of farmers in the food chain 4. Climate change action 5. Environmental care 6. Preserve landscapes and biodiversity 7. Support generational renewal 8. Promote vibrant rural areas 9. Protect food and health quality 10. Foster knowledge and innovation Depending on the business model, each case study selects 3 to 4 CAP objectives that are most relevant to their context. These CAP objectives are strongly interconnected with ecosystem services, and for this reason, relevant case studies and selected CAP goals are mapped against specific ecosystem services. 1. Climate change action is related to climate regulation and carbon storage ecosystem services. 2. Environmental care is linked to air quality, soil quality, and water quality ecosystem services. 3. Preserving landscapes and biodiversity is associated with landscape and scenery, as well as biodiversity ecosystem services. 4. Supporting generational renewal is connected to recreational access and improvements to physical and mental health ecosystem services. 5. Vibrant rural areas are related to the preservation of cultural heritage ecosystem service. 6. Protecting food and health quality is linked to quality and security products, and farm animal health and welfare ecosystem services. 20 Digital tools were assessed for their contribution to each CAP objective separately using multicriteria analysis, analytic hierarchy process (AHP) analyses that have been prepared for every case. • AHP In order to create the methodology of multicriteria analysis the assessment criteria have to be set. It is used 5 principles for sustainability in food and agriculture denoted in FAO (2014) article to determine the assessment criteria which also reflect social preferences. Each case has selected CAP objectives. In order to estimate how DTs can influence CAP objectives we will create an AHP questionnaire for every CAP objectives related with the case (table 3). Estimation goal: Assessment of the DTs according CAP objectives Table 2: List of criteria and short names Principles/criteria Short name Improving efficiency in the use of resources is crucial to sustainable agriculture Use of resources Sustainability requires direct action to conserve, protect and enhance natural resources Natural resources protection Agriculture that fails to protect and improve rural livelihoods, equity and social well-being is unsustainable Improve rural livelihoods Enhanced resilience of people, communities and ecosystems is key to sustainable agriculture Resilience of ecosystems Sustainable food and agriculture requires responsible and effective governance mechanisms Governance mechanisms Alternatives represent the objects of evaluation, which in our case are the three digital tools. • DHK: Digital Hub of Knowledge • DTA: Digital Tool for Analysis • DST: Decision Support Tool The third step of the methodology is the evaluation of the digital tools according to the confluence of different pressures. To achieve this, the 21 partners ranked the tools based on their specific case study and in relation to each individual confluence of pressure using the table 4. Table 3: Rank by placing a number from 1 to 3 for each DT according to each pressure where 1 means it ranks highest and 3 - the lowest. Answer every row. Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition Inadequate diets and unsustainable consumption patterns Land scarcity, degradation and soil depletion Water scarcity and pollution Loss of living resources and biodiversity Climate change Stagnation in agricultural research 3.2 Country analysis The upcoming analysis explored business models across partner countries. It will follow a common structure to ensure comparability, focusing on three main areas. 3.2.1 Bulgaria case study Business model name: Integrated production in the vineyards with vinery and rural tourizm Business model type: Value chain Business model type of the Bulgarian case is Value chain. It is related to management of the viticulture potential of the country and exercises control over the rights for planting new vineyards, replanting and eradication of vineyards. The effective functioning of the value chain in recent years leads to the improvement and stabilization of the sector, increasing the quality and competitiveness of Bulgarian wines, both on the domestic and foreign markets. The aim of the Program for local traditional and regional traditional products for the period 2021–2023 is to value the potential of local traditional and regional traditional products in the wine sector and strengthen their relationship with communities to develop the local economy and agricultural sector. Local traditional and regional traditional products give Bulgarian citizens and guests of the country a variety of tastes, quality, touch with culture and traditions and life of the local economy and communities. 22 Analysis of social and/or economic barriers DTA effects on variable costs and income for each barrier/factor is summarized below (table 5), resulting in the following key points: • Initial investment is perceived as a major cost-increasing factor (5 out of 6) and a potential income reducer (4 out of 6), making it the most critical short-term barrier to adoption. • While its impact on cost reduction is moderate, it is strongly associated with increased income (4 out of 6), highlighting its value as a strategic, long-term benefit. • Improvements in soil quality are universally seen as beneficial, with costs decreasing (5 votes) and income increasing (6 votes). Table 4: DTA analysis of social and/or economic barriers trough variable costs and income Barriers/factor s Influence on variable costs Influence on income Decreas e No impac t Increas e Decreas e No impac t Increas e Initial costs 0 1 5 4 1 1 Long term results in food security 3 2 1 0 2 4 Soil quality 5 0 1 0 0 6 Assessing of the toolbox tools to deliver Environmental care ecosystem service In the context of the business model "Integrated production in the vineyards with winery and rural tourism", and “Environmental care” ecosystem service the application of different tools for supporting soil health within sustainable agriculture shows varied strengths for. For improving resource efficiency in vineyard production management, DST (39.0%) are seen as most effective. Protection of soil and natural resources aligns closely with DTA (39.0%). Addressing unsustainable practices—such as neglecting soil management that impacts rural livelihoods—is where DST (53.7%) again take precedence. Enhancing resilience in the vineyard ecosystem, especially where tourism and production intersect, is best supported through a DHK (53.7%), promoting education on sustainable practices among farmers and visitors alike. For governance mechanisms—like land use planning or environmental compliance in the vineyard setting—DST (49.0%) play a critical role. DST are seen as the most valuable overall (37.7%)—especially for governance, resource efficiency, and addressing unsustainable practices in agriculture. DHK is especially important for building resilience in communities and 23 ecosystems, showing the value of shared learning and education. DTA has high influence in areas involving resource conservation but are generally rated lower than the other tools across most categories. The distribution of preferences shows that no single tool dominates all areas, indicating a need for a balanced, integrated approach that combines knowledge, analytics, and decision-making capabilities. Figure 2. Result of the assessment of DT’s according “Environmental care” criteria Assessing of the toolbox tools to delivery of CAP goal - To preserve landscapes and biodiversity and landscape and scenery and biodiversity ecosystem service In the context of the Bulgarian case study, business model (BM) "Integrated production in the vineyards with winery and rural tourism", aimed at preserving landscapes and biodiversity while supporting soil health, the data highlights a strong preference for DST in several key areas. These tools are especially valued for improving resource efficiency (53.9%), supporting sustainable governance (53.9%), and guiding direct conservation actions (49.0%). In contrast, when the focus shifts to social sustainability—such as protecting rural livelihoods—hubs of knowledge dominate (70.3%), emphasizing the importance of shared expertise and local engagement. DTA are most appreciated when enhancing ecosystem and community resilience (41.1%), suggesting their strength lies in monitoring and adapting to changes in complex vineyard environments. The final results reflect DST as the most effective (41.9%), followed by hubs of knowledge (31.4%) and digital tools (26.7%). 24 DST are essential for guiding soil health practices that align with landscape and biodiversity preservation, particularly in areas of governance, resource efficiency, and conservation planning. Hubs of Knowledge play a key role in fostering social well-being and sustainable livelihoods within vineyard communities. DTA are most effective in tracking ecological resilience and should be integrated for adaptive vineyard and tourism management. The varied preferences indicate that a synergistic approach—using all three tools in combination—can best support soil health and sustainable development in multifunctional landscapes like vineyards. Figure 3. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria Assessing the toolbox tools to delivery of CAP goal - To protect food and health quality and connected - quality and security products, and farm animal health and welfare ecosystem service In the context of the Bulgarian case study, BM "Integrated production in the vineyards with winery and rural tourism", focused on protecting food and health quality through soil health, the data reveals a leading role for DHK across most categories. Hubs of knowledge are especially emphasized in relation to social sustainability (62.3%) and responsible governance (42.9%), underlying the importance of shared learning and collective action in vineyard and rural development. DTA are most valuable for improving efficiency (31.2%) and are equally matched with hubs of knowledge in enhancing resilience (40.0%), pointing to their role in monitoring and adaptive vineyard practices. DST rank highest when it comes to optimizing resource use (49.0%) and are tied with hubs of knowledge in supporting governance (42.9%), proving 25 essential for data-driven planning and soil management strategies. Overall, the final evaluation ranks DHK as the most effective tool (44.7%), followed by DST (31.7%) and DTA (23.6%). DHK emerges as the most valuable tool for preserving food and health quality through soil health, particularly in supporting livelihoods, governance, and sustainability awareness. DST remain crucial for efficiency and strategic planning, while DTA add value in resilience-building and resource monitoring. These findings highlight the need for a complementary approach that integrates knowledge sharing, decision-making frameworks, and analytical tools for sustainable vineyard management and rural tourism development. Figure 4. Result of the assessment of DT’s according “To protect food and health quality” criteria Analysis of confluence of different pressures In the Bulgarian case study, BM "Integrated production in the vineyards with winery and rural tourism", addressing key pressures on soil health reveals varied strengths of the three tools—DHK, DTA, and DST. The DHK is considered most effective in tackling challenges like poverty, unsustainable consumption, soil depletion, and stagnation in research, pointing to the need for shared learning and community capacity-building. DTA are rated highest in understanding the complexities of inadequate diets, land degradation, and biodiversity loss, showcasing their role in providing precise data for informed interventions. Meanwhile, DST are particularly valuable in managing water scarcity and planning for research investment, showing their strength in technical and strategic decision-making. 26 Hubs of Knowledge are vital for raising awareness, improving education, and driving community-led action against poverty, soil decline, and weak research systems. DTA offer crucial insights for monitoring ecological pressures such as biodiversity loss and consumption trends. DST are key in managing water resources and guiding adaptive planning. A combined use of these tools is essential for holistic and effective soil health management within the integrated vineyard and tourism landscape. Table 5: Ranking the DT’s according different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 2 2 1 Inadequate diets and unsustainable consumption patterns 1 3 2 Land scarcity, degradation and soil depletion 2 3 1 Water scarcity and pollution 1 2 3 Loss of living resources and biodiversity 3 1 2 Climate change 1 2 2 Stagnation in agricultural research 1 2 3 3.2.2 Estonia case study Business model name: Crop production Business model type: Agricultural production ETKI is a state research and development institute in the area of governance of the Estonian Ministry of Rural Affairs. Among others, ETKI research impact of catch crops, tillage technologies and fertilizing on soil physical, chemical and biological properties. The crop production technologies and machinery use are analyzed to assess their impact on the environment and farms economy. ETKI cooperates with other organizations, which are developing digital maps based on soil properties. These tools help to choose crops on fields, show fields soil texture, carbon stock, moisture level or erosion level. The usability of these digital maps to develop new business models aiming at adding value to soil conservation should be investigated. Analysis of social and/or economic barriers Estimation how DTA for every Barrier/factor will affect variable costs and income for Estonian case study shows the following: • Initial costs of investment is perceived as a major cost-decreasing factor and a potential income reducer, making it the most critical short-term for DTA as a barrier to adoption. • While DTA impact on long term return is a decreasing factor for variable costs, it is strongly associated with increased income, highlighting its value as a strategic, long-term benefit. 33 Figure 8. Result of the assessment of DT’s according “Climate change” criteria Assessing of the toolbox tools to deliver Environmental care ecosystem service In the context of the German case study, business model " CO2-Land ", the application of different tools for supporting soil health within connection of Environmental care (ecosystem service) sustainable crop production shows varied strengths. DST is especially valued for improving resource efficiency (65.6%), natural resources protection (55.7%) and resilience of ecosystems (40.0%). In contrast, when the focus shifts to improve rural livelihoods (55.7%) and governance mechanisms (63.9%) DTA dominate. DHK is not preferred in connection within this ecosystem service. The final results reflect DST as the most effective (45.6%), DTA (39.3%), followed by DHK (15.1%). DST for business model "CO2-Land" is essential for Environmental care guiding use of resources that align with natural resources and resilience of ecosystems. DTA plays a key role in improvement rural livelihoods and governance mechanism. DHK is not preferable for Environmental care. 34 Figure 9. Result of the assessment of DT’s according “Environmental care” criteria Assessing of the toolbox tools to deliver Fostering knowledge ecosystem service In the context of the German case study, business model " CO2-Land ", the application of different tools for supporting soil health within connection of Fostering knowledge (ecosystem service) sustainable crop production shows varied strengths. The DHK emerges as the most effective overall (56.5%), particularly dominating in governance mechanisms (66.7%) and resilience of ecosystems (40%), where its strengths in stakeholder engagement, education, and capacity building are most impactful. It also plays a leading role in improving rural livelihoods (60%), highlighting its social relevance in fostering inclusive development and community well-being. The DST is particularly effective in resource use (72.3%) and ecosystem resilience (40%), supporting evidence-based agricultural planning and sustainable land use. It also contributes to the results (24.6%), reinforcing its operational importance, though slightly trailing the Hub in overall perception. The DTA ranks lower across most categories, with its highest impact in natural resources protection (17.4%) and governance mechanisms (16.7%). Despite its lower scores, its analytical value remains essential for monitoring and strategic feedback. 35 The combined insights confirm that no single tool is sufficient on its own. A complementary approach—leveraging the educational strength of the Hub, the planning power of DST, and the analytical capabilities of Digital Tools is necessary. Figure 10. Result of the assessment of DT’s according “Fostering knowledge” criteria Assessing of the toolbox tools to deliver To ensure a fair income for farmers ecosystem service The data presented highlights how the three toolbox tools contribute to the ecosystem service “To ensure a fair income for farmers”, emphasizing their varying strengths. The DST stands out in use of resources (53.9%) and contributes significantly to natural resources protection (14.3%) and governance mechanisms (16.7%), confirming its role in improving farm-level decision-making and optimizing productivity for income stability. The DTA is particularly effective in supporting resilience of ecosystems (53.9%), showcasing its ability to inform adaptive practices that indirectly stabilize income through environmental sustainability. It also plays a valuable role in use of resources (29.7%) and has a high overall performance (42.6%), underlining its importance in delivering evidence-based insights that enhance profitability. The DHK, while less dominant in most categories, plays a supportive role in governance mechanisms (16.7%) and ecosystem resilience (29.7%), promoting learning and capacity building—especially relevant for long-term income 36 security. Interestingly, both the DTA and the DST are equally favored (44.4%) in improving rural livelihoods, further reinforcing their practical impact on economic well-being. The result shows a relatively balanced appreciation for the DTA (42.6%) and DST (37.6%). Figure 11. Result of the assessment of DT’s according “To ensure a fair income for farmers” criteria Analysis of delivery of various ecosystem services which depends on a full set of functions defining social preferences and confluence of different pressures. In the context of the German case study, business model "CO2-Land", the application of different tools for supporting soil health within connection sustainable crop production shows similar influence of the three digital tools—DHK, DTA, and DST. The DHK is not considered as a most effective tool. DTA are rated highest in understanding the complexities Land scarcity, degradation. Meanwhile, DST is the most preferable for the rest 5 pressures: Poverty, inequalities, hunger and malnutrition, Inadequate diets, Water scarcity and pollution and Loss of living resources and biodiversity. 37 DHK is preferable for Climate change for the business model "Crop production". DTA is important to overcome the Land scarcity, degradation and soil depletion. The most important tool is DST which is key in following barriers: Poverty, inequalities, hunger and malnutrition, Inadequate diets and unsustainable consumption patterns, Water scarcity and pollution, Loss of living resources and biodiversity and Stagnation in agricultural research. Table 9: Ranking the DT’saccording tog different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 1 2 3 Inadequate diets and unsustainable consumption patterns 1 2 3 Land scarcity, degradation and soil depletion 2 3 1 Water scarcity and pollution 2 1 3 Loss of living resources and biodiversity 2 1 3 Climate change 3 1 2 Stagnation in agricultural research 1 2 3 3.2.4 Italian case study 1 Business model name: Multifunctional and sustainable local development of marginal areas Business model type: Collective and value chain The case study derives from an integrated supply chain project funded in the framework of EU’s Rural Development Policy, which involved research centers, private companies, farmers, and public administrations, to drive force of rural sustainable development through new cropping systems and management innovations. The internal and hilly areas of Tuscany Region are marginal areas characterized by conventional extensive agriculture and little agricultural value, because of several environmental and socio-economic constraints, which negatively affect crop productivity and environmental quality, leading to very low farmer income. In such contests, winter cerealbased cropping systems are prevailing, and soil degradation and the decrease of ecosystem service provision are currently of major concern. Soil erosion, nutrient leaching, reduction of C in soils, certainly represent the main critical issues in these areas. The key concept of the project was to redesign the existing farming systems through the introduction of perennial medicinal and aromatic crops with the conversion from conventional to organic agricultural models. At the same time, new supply chains of organic aromatic plants, with a high added value of final products have been developed, supporting the territorial multifunctional development of the area, through the integration processes between agriculture, processing and other economic activities. This case study will focus on learning from experiences in the project by exploring 38 the effectiveness of the actions made in terms of soil fertility and health improvement, productivity rising, resilience and landscape valorization. We will investigate the possibility of developing business models aiming at adding value to the agronomic management aimed at soil health conservation with innovative crop products through certification and production standards. Analysis of social and/or economic barriers Estimation how DTA for every Barrier/factor will affect variable costs and income for Italian case study shows the following: • DTA has no influence on variable costs for all three barriers. Only for Initial costs DTA can increase income at the BM Multifunctional and sustainable local development of marginal areas. Table 10: DTA analysis of social and/or economic barriers trough variable costs and income Influence on variable costs Influence on income Barriers/factor s Decreas e No impac t Increas e Decreas e No impac t Increas e Initial costs X x Biodiversity preservation X X Climate change x x Assessing of the toolbox tools to deliver Environmental care ecosystem service In the context of the Italian case study, business model "Multifunctional and sustainable local development of marginal areas", the application of different tools for supporting soil health within connection of Environmental care (ecosystem service) sustainable crop production shows varied strengths. DST and DTA have equal importance for the BM for improving use of resource (40.0%), natural resources protection (42.9%), improve rural livelihoods (33.3%), resilience of ecosystems (40.0%) and governance mechanisms (40.0%) DHK is not preferred in connection within this ecosystem service. The final results reflect DST and DTA as the most effective (40.4%), followed by DHK (19.2%). DST and DTA have for business model " Multifunctional and sustainable local development of marginal areas " equal essential for Environmental care. DHK is not preferable for Environmental care. 39 Figure 12. Result of the assessment of DT’s according “Environmental care” criteria Assessing of the toolbox tools to deliver To preserve landscapes and biodiversity ecosystem service In the context of the Italian case study, business model "Multifunctional and sustainable local development of marginal areas", the application of different tools for supporting soil health within connection To preserve landscapes and biodiversity (ecosystem service) sustainable crop production shows varied strengths. DST and DTA have equal importance for the BM for improving use of resource (40.0%), natural resources protection (40.0%), improve rural livelihoods (33.3%), resilience of ecosystems (42.9%) and governance mechanisms (40.0%) DHK is not preferred in connection within this ecosystem service. The final results reflect DST and DTA as the most effective (41.0%), followed by DHK (18.0%). DST and DTA have for business model " Multifunctional and sustainable local development of marginal areas " equal essential to preserve landscapes and biodiversity. DHK is not preferable to preserve landscapes and biodiversity. 40 Figure 13. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria Analysis of delivery of various ecosystem services which depends on a full set of functions defining social preferences and confluence of different pressures. In the context of the Italian case study, business model "Multifunctional and sustainable local development of marginal areas", the application of different tools for supporting soil health within connection sustainable crop production shows similar influence of the three digital tools—DHK, DTA, and DST. The DHK is t considered as a most effective tool for the following pressures: Land scarcity, degradation and soil depletion, Water scarcity and pollution, Loss of living resources and biodiversity and Climate change. DST is rated highest in understanding the complexities Land scarcity, degradation and Inadequate diets and unsustainable consumption patterns. Meanwhile, DTA is not preferable for overcoming the pressures. DHK is preferable for four pressures at the Italian case, business model "Multifunctional and sustainable local development of marginal areas". DST is important to overcome the Poverty, inequalities, hunger and malnutrition and Inadequate diets and unsustainable consumption patterns. DTA is not preferred for overcoming the pressures. 41 Table 11: Ranking the DT’s according to different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 1 2 3 Inadequate diets and unsustainable consumption patterns 1 2 3 Land scarcity, degradation and soil depletion 3 1 2 Water scarcity and pollution 3 1 2 Loss of living resources and biodiversity 3 1 2 Climate change 3 1 2 Stagnation in agricultural research 1 2 3 3.2.5 Italian case study 2 Business model name: Conventional and organic agriculture Business model type: Agricultural production The case study focuses on a series of long-term experiments (LTEs) carried out at large plots/field scale at the Centre for Agrienvironmental Research "Enrico Avanzi" of the University of Pisa. Two field experiments are focusing on the application of conservation agriculture techniques (i.e. reduced or no tillage, cover crops), whereas the third one dealt with organic vs conventional farming systems. The oldest field experiment started in 1986 and is comparing on around 2 ha continuous no-till vs annual moldboard ploughing 30 cm depth on durum wheat and pigeon bean crops. Effects on soil fertility (SOC, C stock, bulk density, total N, available P, pH) are regularly assessed at different depths (0–10, 10–30, 30–60 cm), besides with crop yield and nutrient uptake. The second LTE is comparing on 4 ha since 1993 the combination of 2 tillage levels (reduced tillage vs annual ploughing 30 cm depth), 4 N fertilization levels and 4 cover crop species (control, hairy vetch, radish, a mixture of the two) on a 4year arable crop rotation including durum wheat, sunflower and grain sorghum. Soil fertility issues, crop yield, weed abundance and composition are regularly assessed. In the third LTE, being carried out on 23 ha since 2001, an organic and a conventional management system are being compared on a 4year (conventional system: durum wheat–chickpea–common wheat and grain sorghum) or 8-year (organic system: common wheat–grain millet–grain sorghum–chickpea–hemmer wheat–alfalfa) arable crop rotation. Soil fertility, crop yield and rheological quality, weed abundance and composition, energy use efficiency, economic balance, are regularly assessed, thanks to the standard field plot size. Analysis of social and/or economic barriers 42 Estimation how DTA BM “Conventional and organic agriculture” for every Barrier/factor will affect variable costs and income for Italian case study shows the following: • DTA has decreasing influence on variable costs for four barriers: Long term results in food security, Biodiversity preservation, Regulation of water cycle and Soil quality. For the same barriers DTA increasing influence on income at the BM “Conventional and organic agriculture”. • DTA has no impact on the barrier long term return. Table 12: DTA analysis of social and/or economic barriers trough variable costs and income Influence on variable costs Influence on income Barriers/factor s Decreas e No impac t Increas e Decreas e No impac t Increas e Long term return X X Long term results in food security x X Biodiversity preservation X X Regulation of water cycle X X Soil quality X X Assessing of the toolbox tools to deliver Environmental care ecosystem service In the context of the Italian case study, business model “Conventional and organic agriculture”, the application of different tools for supporting soil health within connection of Environmental care (ecosystem service) sustainable crop production shows varied strengths. DST and DTA have equal importance for the BM for improving use of resource (40.0%), natural resources protection (40.0%), improve rural livelihoods (40.0%), resilience of ecosystems (40.0%) and governance mechanisms (46.2%) DHK is not preferred in connection within this ecosystem service. The results reflect DST and DTA as the most effective (40.4%), followed by DHK (19.1%). DST and DTA have for business model “Conventional and organic agriculture” equal essential for Environmental care. DHK is not preferable for Environmental care. 49 Soil quality x X Place “x” on every row once for variable costs and once for income. Assessing of the toolbox tools to deliver Environmental care ecosystem service In the context of the Crop Production and Animal Farming business model, the use of the three NOVASOIL toolbox tools is evaluated for their support of CAP objectives related to environmental care and the delivery of key ecosystem services such as air quality, soil quality, and water quality. For Use of Resources, DST demonstrates the highest effectiveness (65.7%), indicating its strength in optimizing input use and improving resource efficiency in agricultural practices. In Natural Resources Protection, the DST again stands out (75.0%), showing its significant role in safeguarding soil, water, and air quality through scenariobased planning and targeted interventions. For Improving Rural Livelihoods, the DHK leads (62.3%), emphasizing the importance of shared learning, education, and knowledge transfer for sustainable rural development. In terms of Resilience of Ecosystems, the DTA scores highest (45.8%), reflecting its capacity to model and support ecological adaptation and system stability. Regarding Governance Mechanisms, the DHK is most effective (63.3%), highlighting its contribution to policy understanding and compliance. In the Final Result, the DST achieves the strongest overall impact (45.39%), positioning it as the most valuable tool for integrating environmental, agronomic, and decision-making goals. This distribution indicates that DST are essential for operational and environmental outcomes, while the DHK excels in social dimensions like governance and community livelihoods. DTA are most effective in ecological modeling and resilience, but their overall contribution is more targeted. As in previous assessments, no single tool covers all areas fully demonstrating the need for integrated deployment across knowledge-sharing, analytical, and decision-support functionalities. 50 Figure 16. Result of the assessment of DT’s according “Environmental care” criteria Assessing the toolbox tools to delivery of CAP goal - To preserve landscapes and biodiversity CAP and landscape and scenery and biodiversity ecosystem services This assessment explores the effectiveness of the NOVASOIL toolbox tools in supporting biodiversity protection and landscape preservation within the context of sustainable agriculture. For Use of Resources, both the DHK and DTA share the highest effectiveness (44.4%), highlighting their value in promoting efficient, biodiversity-friendly resource use practices. In Natural Resources Protection, the DHK leads decisively (63.9%), showing its strength in supporting knowledge-based approaches to protecting soil, habitats, and ecological balance. For Improving Rural Livelihoods, the DHK again ranks highest (53.9%), emphasizing the importance of education and community engagement in preserving cultural landscapes and biodiversity-related economic opportunities. When assessing Resilience of Ecosystems, both the DHK and DTA are equally effective (45.5%), reflecting their joint potential in supporting ecosystem stability and landscape functionality. 51 Regarding Governance Mechanisms, the DST dominates (67.5%), showing it is the most effective tool for planning, compliance, and integration of biodiversity-focused policies into land management. In the Result, the DHK shows the highest overall impact (51.93%), demonstrating that knowledge-sharing, awareness, and stakeholder involvement are central to preserving landscapes and biodiversity. DHK emerges as the most effective tool in this assessment, especially in areas connected to biodiversity awareness, ecological knowledge, and community resilience. DST are essential for governance and structured planning, while DTA play a supportive role, particularly in ecosystem monitoring. Figure 17. Result of the assessment of DT’s according “To preserve landscapes and biodiversity” criteria Analysis of delivery of various ecosystem services which depends on a full set of functions defining social preferences and confluence of different pressures. In Latvian case study, BM “Crop production and animal farming” the application of the three NOVASOIL tools—DHK, DTA, and DST—demonstrates differentiated effectiveness in tackling a range of pressures impacting soil health and sustainability. The DTA is rated as the most effective in addressing poverty and malnutrition, climate change, and water scarcity and pollution, highlighting its strong 52 capacity for data-driven insights and targeted analysis. These tools support the diagnosis of complex environmental and socio-economic issues, enabling precise responses to challenges like water quality, changing weather patterns, and food insecurity. The DST emerges as the best solution for land degradation and unsustainable consumption, underscoring its importance in resource planning, land use optimization, and tactical decision-making to mitigate soil exhaustion and improve sustainability outcomes in food systems. The DHK is ranked highest in tackling biodiversity loss and stagnation in agricultural research, reflecting its critical role in raising awareness, fostering collaboration, and building capacity among stakeholders. It is especially effective when addressing pressures that require behavioral change, knowledge transfer, or stakeholder engagement. The DTA excels in quantifying and responding to environmental and social pressures through analytics. The DST provides strategic solutions for operational land and resource issues, while the DHK is essential for systemic learning and innovation. Their complementary use is crucial for building a soil health strategy that is both scientifically grounded and socially responsive. Table 17: Ranking the DT’s according different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 3 1 2 Inadequate diets and unsustainable consumption patterns 3 2 1 Land scarcity, degradation and soil depletion 2 3 1 Water scarcity and pollution 2 1 3 Loss of living resources and biodiversity 1 3 2 Climate change 3 1 2 Stagnation in agricultural research 1 2 3 3.2.8 Latvia case study 2 Business model name: The forest management Business model type: Forestry soils The forest management BM demonstration plots of the Pasaules dabas fonds (associate partner of WWF Latvia) have different owners, but their views on the forest are similar. Here, forest owners work for the benefit of the present values while retaining the ability to exploit the vast forest values of tomorrow. 53 The demonstration areas differ in size, forest stand and natural conditions. Through contractual agreements (cooperation) with forest owners on a voluntary basis, seminars and internships are organized for other forest owners, students, etc. to maintain the forest and not to cut down all trees, to manage the forest in an environmentally friendly way and also to achieve economic benefits. There are about 5-10 events per year with a total number of 200-300 participants. Analysis of social and/or economic barriers Estimation of how DTA influences variable costs and income for the Latvia forest management case study shows the following: • Long-term return is associated with a decrease in variable costs and an no impact in income, indicating that DTA may provide strategic benefits that reduce operational expenses. • Sustainable crop production has no impact on variable costs but is linked to an increase in income, suggesting that DTA may enhance profitability through improved practices without significantly altering cost structures. • Food demand also shows no impact on variable costs and an increase in income, reflecting that DTA may help forest managers or landowners respond to market opportunities and boost revenues without increasing input requirements. • Climate change is associated with an increase in variable costs with no impact in income, indicating a potential barrier. • Regulation of the water cycle has no impact on costs and income. • Soil quality improvements are associated with an increase in variable costs and an increase in income, meaning that while DTA implementation may require higher investment in forest soil maintenance, it can lead to higher returns over time. Table 18: DTA analysis of social and/or economic barriers trough variable costs and income Influence on variable costs Influence on income Barriers/factor s Decreas e No impac t Increas e Decreas e No impac t Increas e Long term return x x Sustainable crop production x x Food demand x x Climate change x x Regulation of water cycle x x 54 Soil quality x x Assessing of the toolbox tools to deliver Environmental care ecosystem service This assessment evaluates the effectiveness of the NOVASOIL toolbox tools in promoting environmental care and improving Air quality, Soil quality, and Water quality ecosystem services in agriculture. For Use of Resources, both the DHK and DTA are equally the most effective tools (45.5%), emphasizing their role in promoting efficient and sustainable use of agricultural inputs that impact soil and water quality. In Natural Resources Protection, DHK leads with a substantial margin (68.8%), indicating its key role in spreading knowledge and practices essential for safeguarding air, soil, and water ecosystems. For Improving Rural Livelihoods, both the DHK and the DST are equally impactful (42.9%), showing how education and decision support together enhance environmental awareness and economic resilience in rural areas. When it comes to Resilience of Ecosystems, the DHK is again the top performer (44.0%), highlighting its role in supporting the adaptive capacity of farming systems to protect ecosystem functions. In terms of Governance Mechanisms, both the DTA and DST share the highest influence (46.2%), reinforcing their importance in supporting compliance, policy implementation, and structured environmental planning. In the Final Result, the DHK scores the highest overall (49.91%), demonstrating that access to knowledge and awareness-building are fundamental to advancing environmental care in agriculture. The DHK is the strongest overall performer, especially for natural resources protection, ecosystem resilience, and community engagement. The DST complements this with strengths in livelihoods and governance, while the DTA proves valuable in resource use and governance planning. 55 Figure 18. Result of the assessment of DT’s according “Environmental care” criteria Analysis of delivery of various ecosystem services which depends on a full set of functions defining social preferences and confluence of different pressures. In Latvian case study, BM “The forest management” The DHK is rated most effective in four categories: poverty and malnutrition, inadequate diets and unsustainable consumption, biodiversity loss, and stagnation in agricultural research. This underscores its key role in education, awareness-raising, and stakeholder engagement. It is especially suited for pressures requiring knowledge dissemination, community involvement, and institutional learning. The DTA performs best in land scarcity and degradation, highlighting its capacity to quantify soil conditions, monitor degradation trends, and provide evidence for targeted intervention. It also consistently ranks second across several other categories, reinforcing its value as a supportive analytical tool in both ecological and socio-economic domains. The DST stands out in managing water scarcity and pollution and climate change, indicating its strength in technical planning, adaptive management, and scenario simulation. It is ideal for addressing complex, system-level challenges that require real-time decision-making and strategic action. The DHK leads in addressing social and institutional barriers to soil health, such as poverty, behavior, and knowledge gaps. The DTA provides robust 56 support for land and biodiversity-related pressures, while the DST is most effective in tackling environmental and infrastructural challenges. Table 19: Ranking the DT’s according to different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 1 3 2 Inadequate diets and unsustainable consumption patterns 1 2 3 Land scarcity, degradation and soil depletion 2 1 3 Water scarcity and pollution 2 3 1 Loss of living resources and biodiversity 1 3 2 Climate change 3 2 1 Stagnation in agricultural research 1 2 3 3.2.9 Spain case study 1 Business model name: Integrated production Business model type: Value chain With the integrated production program, sustainable agriculture in Andalusia has been promoted. The statistics offered by the regional government show that participation in this measure has been increasing over the past few years. Specifically, in the olive grove sector, there is a lot of competition. Recent research works highlighted the increase of soil organic carbon due to crop/land management. Analysis of social and/or economic barriers Estimation of how DTA influences variable costs and income for the Spain case study shows the following: • Long-term return is associated with an increase in variable costs and an increase in income, suggesting that DTA implementation requires higher investment but offers significant long-term financial benefits. • Sustainable crop production leads to a decrease in variable costs and an increase in income, indicating that DTA supports efficient and profitable practices aligned with integrated production systems. • Food demand has no impact on variable costs but results in an increase in income, meaning DTA enables producers to meet demand more effectively without increasing operational inputs. • Long-term results in food security result in a decrease in variable costs and an increase in income, highlighting that DTA contributes to 57 efficient practices that ensure food security and economic viability over time. • Biodiversity preservation is linked to an increase in variable costs and no impact in income, possibly due to the added costs of ecological practices that don’t immediately translate into financial gain. • Climate change is associated with a decrease in variable costs and an increase in income, showing DTA’s potential to promote resilience and adaptive strategies that are both cost-effective and economically rewarding. • Regulation of the water cycle also leads to a decrease in variable costs and an increase in income, reflecting the value of DTA in enhancing water efficiency and supporting productivity. • Soil quality improvements result in a decrease in variable costs and an increase in income, underlining DTA’s effectiveness in boosting soil health while improving financial outcomes. Table 20: DTA analysis of social and/or economic barriers trough variable costs and income Influence on variable costs Influence on income Barriers/factor s Decreas e No impac t Increas e Decreas e No impac t Increas e Long term return X X Sustainable crop production X X Food demand X X Long term results in food security X X Biodiversity preservation X X Climate change X X Regulation of water cycle X X Soil quality X X 58 Assessing of the Toolbox Tools to Deliver the CAP Goal “Climate Change” and Ecosystem Services – Climate Regulation and Carbon Storage This assessment explores how each of the NOVASOIL toolbox tools contributes to climate change mitigation and adaptation in agriculture, focusing on tools that support carbon storage and environmental resilience. For Use of Resources, DST is the most effective (56.8%), reflecting its strength in optimizing resource usage. In Natural Resources Protection, the DST again leads (53.2%), showing its role in protecting soil and organic matter critical for carbon retention and climate resilience. Regarding Improving Rural Livelihoods, DST shows the highest influence (60.8%), suggesting that climate-smart practices supported by DTA can improve economic stability in rural areas. In Resilience of Ecosystems, the DST performs strongest (56.0%), confirming its value in adapting agricultural systems to climate risks and enhancing ecosystem functionality. For Governance Mechanisms, the DHK is the top performer (69.0%), indicating the importance of education, information dissemination, and stakeholder engagement in climate-related policy and land-use planning. In the Final Result, the DST shows the highest overall impact (53.89%), making it the most effective tool for addressing climate change objectives and carbon-related ecosystem services in agriculture. DST emerges as the leading instrument for tackling climate change, excelling in resource management, ecosystem resilience, and rural adaptation. DHK complements this by supporting governance and awareness efforts. 65 In Natural Resources Protection, the DTA and DST again share the highest score (47.1%), indicating their usefulness in managing and conserving environmental assets essential for ecosystem services. Regarding Improving Rural Livelihoods, both tools maintain equal top effectiveness (47.1%), highlighting how environmentally sustainable practices can also support income generation and community well-being. For Resilience of Ecosystems, the DTA and DST are once more tied (47.1%), demonstrating their strength in promoting systems that adapt to and recover from environmental stressors. In the area of Governance Mechanisms, the DST leads clearly (66.4%), reinforcing its essential role in supporting policy implementation, regulatory compliance, and structured planning for environmental goals. For the Final Result, the DST achieves the highest overall score (52.21%), confirming its status as the most effective and versatile tool for advancing environmental care and enhancing ecosystem services. The DST consistently shows high impact, especially in governance and overall effectiveness. While the DTA matches its performance in many environmental categories, the DST emerges as the most comprehensive solution. Figure 22. Result of the assessment of DT’s according “Environmental care” criteria 66 Assessing of the toolbox tools to delivery of CAP goal Protecting food and health quality and the quality and security products, and farm animal health and welfare ecosystem services. This assessment evaluates how the NOVASOIL toolbox tools contribute to food safety, health standards, and the sustainability of animal production systems. For Use of Resources, DST is the most effective (62.8%), indicating its capacity to guide efficient, health-conscious input use in both crop and livestock systems. In Natural Resources Protection, DST also leads (62.8%), reinforcing its role in maintaining the environmental conditions necessary for healthy food and animal systems. Regarding Improving Rural Livelihoods, the DST ranks highest (57.5%), showing that aligning health and quality standards with production benefits farmers economically. For Resilience of Ecosystems, the DST performs best (62.8%), supporting resilient, high-quality production systems that ensure long-term food and animal welfare security. In terms of Governance Mechanisms, both the DTA and the DST are equally effective (46.2%), highlighting their importance in monitoring, compliance, and certification related to food quality and animal welfare. For the Final Result, the DST once again achieves the highest score (57.19%), confirming its comprehensive contribution to food and health quality goals. The DST is the dominant performer across all key areas, making it the most impactful tool for promoting food safety, product quality, and animal welfare. Its decision-oriented functionalities help align on-farm practices with high standards for both human and animal health. The DTA complements this in governance-related aspects. 67 Figure 23. Result of the assessment of DT’s according “Protecting food and health quality” criteria Analysis of delivery of various ecosystem services which depends on a full set of functions defining social preferences and confluence of different pressures. The DHK is ranked first in only two categories: climate change and stagnation in agricultural research. This highlights its value in long-term processes that require education, capacity building, and knowledge transfer—areas where behavior change, innovation, and shared learning are essential. However, in five out of seven pressures, DHK ranks third, suggesting that while it is critical for institutional and cultural transformation, it is less effective in addressing urgent or technical issues such as land degradation or water scarcity. The DTA is ranked first in two categories: water scarcity and pollution and loss of biodiversity. These results reflect its strength in environmental monitoring, diagnostics, and data-driven insight, especially in areas where precision and ecological understanding are needed. It also ranks second in two other categories, confirming its stable role across most pressures. However, it scores third in three categories, indicating it is not always the primary tool when strategic planning or social intervention is needed. 68 The DST shows the strongest overall performance, being ranked first in three categories: poverty and malnutrition, inadequate diets, and land degradation. It consistently ranks second in the remaining four areas. This underscores its role as the most balanced and action-oriented tool, capable of supporting both social and environmental challenges through strategic decision-making, planning, and implementation. DHK is particularly effective where practical solutions and operational choices are critical. Each NOVASOIL tool plays a complementary role. The DST is the leading performer, providing practical and strategic value across most soil health pressures. The DTA is essential for ecological understanding and environmental assessment. The DHK contributes most in areas that require systemic change through learning and innovation. Table 23: Ranking the DT’s according to different pressures Pressures Hub of knowledge Digital tool for analysis Decision support tool Poverty, inequalities, hunger and malnutrition 3 2 1 Inadequate diets and unsustainable consumption patterns 2 3 1 Land scarcity, degradation and soil depletion 3 2 1 Water scarcity and pollution 3 1 2 Loss of living resources and biodiversity 3 1 2 Climate change 1 3 2 Stagnation in agricultural research 1 3 2 3.1 Integrated Analysis of Digital Tools by business model types 3.1.1 Business model type: Value chain Analysis of the usefulness of DTA in relation to social and economic barriers The implementation of Digital Tool 2 (DTA) across Bulgaria, Latvia, and Spain reveals a consistent pattern of transformation in Value chain business model. While each country presents context-specific nuances, a common trajectory 69 can be observed in how DTA influences operational cost structures, income dynamics, and long-term sustainability. Initial investment is widely perceived as a significant short-term barrier. In Bulgaria and Latvia, it is viewed as a cost-increasing factor with the potential to reduce income during early adoption. However, in some cases such as in Spain, DTA also contributes to mitigating this financial hurdle. The effect of DTA on variable costs varies across countries and specific goals. In certain contexts, such as biodiversity preservation or climate adaptation, its implementation may lead to increased variable costs due to the adoption of more complex or ecologically sensitive practices. Conversely, in areas like water cycle regulation, sustainable crop production, and soil quality improvements, DTA often leads to a reduction in variable costs. This is especially prominent in Spain, where its efficiency-enhancing capabilities are more extensively utilized. Across all countries, the use of DTA is consistently associated with increased income, particularly when focused on soil health, climate-resilient practices, and sustainable production systems. In Bulgaria and Spain, improved soil quality translates directly into higher revenues. DTA also enables producers to respond more effectively to food demand without a proportional increase in input, which strengthens profitability. Not all benefits result in immediate financial gain. In Latvia, long-term outcomes related to food security are often perceived as neutral or even negative in terms of short-term income. Soil quality improvements consistently emerge as a point of convergence, where DTA not only supports agronomic performance but also yields clear financial benefits, especially in Spain. Climate adaptation practices, supported by the tool, promote economic resilience and operational stability. Similarly, water management efficiency is notably improved through DTA, particularly in regions facing scarcity (Spain), which enhances both productivity and profitability. Biodiversity-friendly practices, while not always linked to short-term income gains, position producers advantageously in light of evolving regulatory and consumer expectations. These practices align with broader sustainability goals, adding reputational and strategic value to the business model. We can conclude that the most substantial value of DTA lies in its long-term strategic contribution. Despite short-term barriers, the tool supports a gradual and transformative shift toward more resilient, data-driven, and profitable agricultural systems. The value chain business model shaped by DTA is centered on sustainable intensification, where producers aim to achieve higher productivity with optimized resource use. This model prioritizes longterm profitability, often requiring upfront investments that yield benefits over time. It enhances producers' responsiveness to market demand. Furthermore, it integrates environmental considerations, including biodiversity, climate adaptation, and soil health, as essential components of the production system. Analysis of the contribution of the digital tools to the delivery of various ecosystem services 70 Across Bulgaria, Latvia, and Spain, DST shape a modern value chain business model that integrates ecological, operational, and social dimensions. Despite national variations in priorities and tool effectiveness, a clear and structured model emerges, built upon three core technological pillars: DST, Hubs of Knowledge, and DTA. In all countries, DST is seen as strategic enablers that optimize resource use, strengthen governance, and enhance resilience. They are not isolated solutions but function most effectively when integrated with knowledgesharing platforms and data-driven analytical tools. DST are consistently recognized as the central instrument for driving operational efficiency, governance, and environmental planning. In Spain and Latvia, they dominate most categories including biodiversity, climate resilience, and structured decision-making. In Bulgaria, they are most effective in addressing unsustainable agricultural practices and guiding conservation planning. Hubs of Knowledge play a pivotal role in governance, awareness, and community livelihoods. Across all contexts, they support stakeholder engagement and long-term capacity building. This is especially emphasized in Bulgaria and Latvia, where they are seen as critical for social cohesion and sustainability culture. DTA provide targeted impact in areas such as resource monitoring, ecological modeling, and resilience tracking. Though generally rated lower than DST and DHK, they offer essential feedback loops that make strategic and educational tools more responsive and adaptive. Key similarities that are found across the value chain business models are: Integrated Use Required: No single tool is sufficient. All three countries emphasize the need for a synergistic combination of DST, DHK, and DTA to address the full spectrum of value chain challenges—from production to ecosystem management and community well-being. Strategic Planning & Governance: DST are universally linked to improved governance and long-term planning. This suggests their centrality in value chain leadership and risk management. Multifunctional Landscape Application: Especially in Bulgaria and Spain, the tools are valued for managing complex systems like vineyards and rural tourism, supporting both ecological outcomes and economic livelihoods. While Bulgaria presents a more balanced perception of all tools (with slightly higher value on Hubs of Knowledge), Spain (both assessments) consistently identifies DST as the dominant force across nearly all impact categories. Latvia places greater emphasis on knowledge and community-oriented tools, viewing Digital Tools more as a supporting feature. In Spain, climate adaptation, biodiversity protection, and ecosystem resilience are leading concerns. Bulgaria emphasizes soil health, resource conservation, 71 and sustainable livelihoods. Latvia focuses on governance, biodiversity awareness, and community resilience. DST are not only technological solutions but act as structural anchors of a modern value chain business model. Their integration with knowledge platforms and analytical technologies supports a holistic transformation of agriculture and land management, addressing environmental, operational, and social demands simultaneously. While national contexts influence the emphasis placed on each tool, the universal recommendation is integration, complementarity, and strategic deployment across all phases of the value chain. Analysis of the toolbox for delivery of various ecosystem services according to the social preferences In all countries, the value chain model is structured around: DST as the core mechanism for planning, governance, and aligning land use with strategic goals. DTA as enablers of data-driven insights, especially for tracking environmental pressures. Hubs of Knowledge as social catalysts that facilitate education, innovation, and stakeholder engagement. All contexts confirm that ecosystem services require integration of these tools. No single tool is sufficient on its own. Their synergy ensures that ecological goals (e.g., soil restoration, biodiversity) are matched with social value (e.g., livelihoods, education) and economic sustainability. Spain prioritizes DST for implementation, food safety, and operational impact. Latvia emphasizes Digital Tools for pressure-response analytics and Hubs for system learning. Bulgaria balances all three, highlighting their combined value for vineyard landscapes and rural tourism. 3.1.2 Business model type: Agricultural production/value chain Analysis of the usefulness of DTA in relation to social and economic barriers Long term return, Sustainable crop production, Food demand and Biodiversity preservation are barriers for which DT 2 has no influence on variable costs in a CO2-Land business model. From these four barriers Long term return and Sustainable crop production impose over increasing income. The rest two have no income impact. While DTA impact on Soil quality is decreasing factor for variable costs, it is strongly associated with increased income, highlighting its value as a strategic, long-term benefit. DTA has influence on Climate change as decreasing variable costs and income increasing. Analysis of the contribution of digital tools to the delivery of various ecosystem services DST are essential for Climate change guiding use of resources that align with improvement rural livelihoods and resilience of ecosystems. DTA plays a key 72 role in improvement natural resource protection and governance mechanism. DHK is not preferable for Climate change. DST for business model "CO2-Land" is essential for Environmental care guiding use of resources that align with natural resources and resilience of ecosystems. DTA plays a key role in improvement rural livelihoods and governance mechanism. DHK is not preferable for Climate change. DST for business model "CO2-Land" is essential for Environmental care guiding use of resources that align with natural resources and resilience of ecosystems. DTA plays a key role in improvement rural livelihoods and governance mechanism. DHK is not preferable for Climate change. Analysis of the toolbox for delivery of various ecosystem services according to the social preferences DHK is preferable for Climate change for the business model "Agricultural production/value chain". DTA is important to overcome the Land scarcity, degradation and soil depletion. The most important tool is DST which is key in following barriers: Poverty, inequalities, hunger and malnutrition, Inadequate diets and unsustainable consumption patterns, Water scarcity and pollution, Loss of living resources and biodiversity and Stagnation in agricultural research. 3.1.3 Business model type: Collective and value chain Analysis of the usefulness of DTA in relation to social and economic barriers The two Italian case studies — Multifunctional and Sustainable Local Development of Marginal Areas and District of the Sands — highlight differing socio-economic dynamics under the collective and value chain business model. In the first case, the DST does not influence variable costs but can contribute to increased income through initial investments. In contrast, the District of the Sands demonstrates that sustainable crop production raises both variable costs and income, suggesting long-term profitability. However, some measures, such as climate change mitigation, increase costs while reducing income. Other services, like biodiversity preservation and water cycle regulation, tend to improve income despite higher costs, indicating a mixed economic impact depending on the type of service implemented. Analysis of the contribution of digital tools to the delivery of various ecosystem services Ecosystem service delivery varies across tools and contexts. In the multifunctional development model, both the DST and the DTA are essential for supporting environmental care and the preservation of landscapes and biodiversity. The DHK, while not preferred for environmental outcomes, is valuable in addressing social pressures, such as poverty, inequality, malnutrition, and unsustainable consumption patterns. In the District of the Sands, the Hub plays a critical role in managing social, behavioral, and 73 informational challenges, whereas the Digital Tool is more suited for ecological monitoring and addressing systemic environmental issues. The DST, meanwhile, is particularly effective in operational domains such as land degradation and water management. Analysis of the toolbox for delivery of various ecosystem services according to the social preferences The analysis of ecosystem service delivery, which considers the full range of social preferences and the interaction of multiple pressures, reveals differing strengths among the tools. In the case of the Multifunctional and Sustainable Local Development of Marginal Areas, the DHK is particularly effective in addressing four key social and environmental pressures. The DST is instrumental in tackling issues such as poverty, inequality, hunger, malnutrition, and unsustainable consumption patterns. In contrast, the DTA is less effective for these specific challenges. In the District of the Sands case, the DHK plays a central role in confronting social, behavioral, and knowledgebased pressures, while the Digital Tool proves essential for ecological monitoring and diagnosing systemic issues like biodiversity loss. The DST remains a valuable resource for dealing with operational and resource-based challenges, including land degradation and water management. 3.1.4 Business model type: Agricultural production Analysis of the usefulness of DTA in relation to social and economic barriers DTA has decreasing influence on variable costs for four barriers: Long term results in food security, Biodiversity preservation, Regulation of water cycle and Soil quality. For the same barriers DTA increasing influence on income at the BM “Conventional and organic agriculture”. DTA has no impact on the barrier long term return. Analysis of the contribution of digital tools to the delivery of various ecosystem services DST and DTA have for business model “Conventional and organic agriculture” equal essential for Environmental care. DHK is not preferable for Environmental care. DST and DTA have for business model “Conventional and organic agriculture” equal essential for Environmental care. DHK is not preferable for Environmental care. Analysis of the toolbox for delivery of various ecosystem services according to the social preferences DHK is preferable for four pressures at the Italian case, business model "Conventional and organic agriculture". DST is important to overcome the Poverty, inequalities, hunger and malnutrition and Inadequate diets and 74 unsustainable consumption patterns. DTA is not preferred for overcoming the pressures. 3.1.5 Business model type: Forest management Analysis of the usefulness of DTA in relation to social and economic barriers The long-term return is associated with a decrease in variable costs and no impact on income, indicating that DTA may offer strategic benefits by reducing operational expenses. In the case of sustainable crop production, there is no change in variable costs but an increase in income, suggesting that DTA can enhance profitability through better practices without significantly altering cost structures. Similarly, food demand shows no effect on variable costs but a positive impact on income, implying that DTA may help forest managers or landowners capitalize on market opportunities without increasing input requirements. Conversely, climate change presents a potential barrier, as it is linked to increased variable costs without income benefits. The regulation of the water cycle appears neutral, with no impact on either costs or income. Finally, soil quality improvements lead to increased variable costs and increased income, indicating that while DTA may require greater investment in forest soil maintenance, it can yield higher returns over time. Analysis of the contribution of digital tools to the delivery of various ecosystem services The DHK is the strongest overall performer, especially for natural resources protection, ecosystem resilience, and community engagement. The DST complements this with strengths in livelihoods and governance, while the DTA proves valuable in resource use and governance planning. A combined approach ensures comprehensive support for air, soil, and water quality within the CAP framework Analysis of the toolbox for delivery of various ecosystem services according to the social preferences DHK leads in addressing social and institutional barriers to soil health, such as poverty, behavior, and knowledge gaps. The DTA provides robust support for land and biodiversity-related pressures, while the DST is most effective in tackling environmental and infrastructural challenges. 4 Ecological and human impact of the soil health business models 4.1 Methodology The study aims to evaluate both the ecological and human impacts of business models focused on improving soil health by conducting a Life-Cycle Analysis (LCA). Тhe environmental and human impact are considered as one combined dimension. For the assessment, we use the carbon footprint 81 CO₂-eq/ha, upstream emissions from inputs (fertilizers, pesticides, seeds): 907 kg CO₂-eq/ha, machinery emissions: 252 kg CO₂-eq/ha This places the system in the medium carbon impact category (1–4 tons CO₂eq/ha/year), reflecting moderate environmental pressure, primarily due to nitrogen-related emissions and upstream production of fertilizers and agrochemicals. 4.3 Conclusion Based on CO₂ Emissions Across Countries and Production Systems The Life Cycle Assessment (LCA) results from five different farms across Italy, Spain, Germany, and Bulgaria highlight the central role of agricultural practices in shaping carbon emissions per hectare. Despite diverse crops, climates, and farm structures, all systems fall within the medium carbon impact category—defined as 1 to 4 tons CO₂-equivalent per hectare per year. However, the drivers of emissions and the efficiency of systems vary widely. Italy – Farm 1 (Multiple Crops), BM type Collective and value chain Among the four crops analyzed, alfalfa stands out with the lowest emissions (2.32 t CO₂-eq/ha) due to its low-input, no-till, and rainfed system with no nitrogen fertilizer. In contrast, tomato production reaches 5.33 t CO₂-eq/ha, placing it in the high impact category, primarily because of intensive input use—particularly fertilizers and pesticides. Maize (3.37 t) and wheat (3.69 t) remain in the medium category but are relatively high due to N₂O emissions and lack of carbon sequestration. Italy – Farm 2 (Wheat, Conventional vs. Organic), BM type Collective and value chain Both the conventional (1.35 t CO₂-eq/ha) and organic (1.70 t CO₂-eq/ha) systems fall into the medium impact range, but organic emits ~26% more. Despite the absence of synthetic inputs, the organic model produces more N₂O due to manure-related nitrogen losses. Moreover, lower yield in the organic system results in a higher emission intensity per ton of product (415 vs. 306 kg CO₂-eq/t). Spain – Olive Production, BM type Value chain The Spanish olive system also falls into the medium impact category at 1.67 t CO₂-eq/ha/year. While irrigation and fertilization are applied, overall emissions remain moderate. However, losses of soil organic carbon (1.17 t CO₂-eq/ha) are the largest contributor, revealing a risk to long-term sustainability if soil health is not maintained. Germany – Wheat (No-Till System), BM type Agricultural production/value chain 82 Despite reduced tillage and residue incorporation, the German wheat system emits 2.90 t CO₂-eq/ha/year, mostly due to high nitrogen-related emissions and upstream input production. This illustrates that even modern, mechanized systems with conservation practices can have notably high emissions if nitrogen efficiency is low. Bulgaria – Vineyard, BM type Value chain In contrast to all other farms, the Bulgarian vineyard exhibits a net negative carbon footprint from land-use change, sequestering 3.7 t CO₂-eq/ha/year, making it a carbon sink. This is due to perennial vegetation, lack of irrigation, and high organic matter input (manure), suggesting strong potential for carbon-neutral or even climate-positive agriculture under the right conditions. While all systems are within the medium emissions range (1–4 t CO₂-eq/ha), they vary greatly in efficiency and climate impact per unit of output. Systems like alfalfa and vineyards show strong carbon performance, while crops like tomato and high-input wheat demonstrate greater emissions per hectare and per ton. This highlights the importance of tailoring management practices—especially regarding nitrogen and soil carbon—to minimize the carbon footprint of agriculture while maintaining productivity. 5 Feedback from CoP 5.1 Methodology For the analysis of the feedback from CoP was created a instruction that gives information to CoP about the digital solutions in NOVASOIL toolbox, summary of the results from testing and valorisation considering national specificities, business models and case studies. The CoP members in each NOVASOIL partner country fulfilled a short survey for evaluation NOVASOIL toolbox. WP3 will collect internal feedback of the solutions and case studies evaluated in NOVASOIL reporting on perceived usefulness of the soil health business models, cost of implementation in relation to the characteristics of the different land uses (e.g. agriculture, forestry, urban areas), delivering suggestions of final refinements as well as policy relevant feedback. Each case study in NOVASOIL project and respective partners will be responsible for delivering the information required for the feedback from CoP. The list of the case studies are as follows: Table 26: List of the case studies № Country Name Business model type 1 Spain Integrated production Value chain 2 Spain Organic wine in Rueda, Spain (Rueda) Value chain 3 Bulgaria Integrated production in the vineyards with vinery and rural tourism Value chain 83 4 Italy District of the Sands - Emilia-Romagna Collective and value chain 5 Italy A model for multifunctional and sustainable local development of marginal areas - Tuscany Region Collective and value chain 6 Italy CiRAA LTEs on conventional and organic agriculture Agricultural production 7 Latvia Crop production and animal farming Value chain 8 Germany CO2-Land Agricultural production/valu e chain 9 Latvia Forestry Within the document, we have aggregated and analyzed the information received from partners during the valorization process of the digital tools. This information is first systematized by a type of business model. Second, for each business model, we provide: 1. Analysis of the usefulness of DTA in relation to social and economic barriers; 2. Analysis of the contribution of digital tools from the toolbox to the delivery of various ecosystem services 3. Analysis of the toolbox for delivery of various ecosystem services according to social preferences. The CoP members in each NOVASOIL partner country have to fulfil the survey for NOVASOIL toolbox evaluation (Annex 1). 5.2 Analysis The purpose of the internal feedback is to gather in-depth insight of the solutions and case studies assessed within NOVASOIL, focusing on the perceived value and practical relevance of the soil health business models and proposed digital solutions. It will evaluate the cost and feasibility of implementation, considering the specific characteristics of different land uses—such as agriculture, forestry, and urban environments. The insights will provide targeted, policy-relevant recommendations to support future uptake and integration into land management strategies. The survey was answered by CoP in Bulgaria, Estonia, Italy (Emilia Romagna Region), Italy (Tuscany Region), Spain, France, and Germany. Table 28 gives a summary of the responses to “Is the proposed Toolbox easy to understand?” Table 27: Summary of the responses to “Is the proposed Toolbox easy to understand?” Country / Region DHK DTA DST Italy – Emilia-Romagna Yes Yes No 84 Italy – Tuscany Yes (No answer) No Bulgaria Yes No No Estonia Yes No No Germany Yes No access No France Yes Yes Yes DHK is generally well understood across all countries, with all respondents answering "Yes". DTA received mixed feedback, with several countries (Bulgaria, Estonia, and no access in Germany) indicating difficulty or inability to evaluate it, a problem that have been resolved. DST is the most frequently rated as "Not easy to understand", with only France giving it full approval. Table 29 is a summarized table of the responses to – “Do you find the Toolbox useful for soil health business models?” Table 28: Summary of the responses to “Do you find the Toolbox useful for soil health business models?” Country / Region DHK DTA DST Italy – Emilia-Romagna Yes Yes Yes Italy – Tuscany No (No answer) No Bulgaria Yes Yes Yes Estonia Yes and No No – unclear purpose Maybe – depending on data availability Germany Yes No access No France Yes Yes Yes DHK is seen as useful by most countries, though Estonia expresses mixed opinions and Italy (Tuscany) rated it as not useful. DTA received positive feedback from France, Italy (Emilia-Romagna), and Bulgaria, but negative or unclear responses from Estonia, and no access reported by Germany. DST was viewed as useful by most, but Italy (Tuscany) and Germany found it not useful, and Estonia was undecided, depending on data availability. Table 30 gives a summary of the responses to the question – “Do you understand the goal of the Toolbox?” Table 29: Summary of the responses to “Do you understand the goal of the Toolbox?” Country / Region DHK DTA DST Italy – EmiliaRomagna Yes Yes Yes Italy – Tuscany No (No answer) Yes Bulgaria Yes No No 85 Estonia Yes – “Helps promote soil health BMs” No – tool unclear, issues Yes, but clarification needed Germany Yes No access No France Yes Yes Yes DHK is generally well understood, except by Italy (Tuscany). DTA received critical feedback from Estonia and was not understood by Bulgaria. DST was least understood in Bulgaria and Germany, and Estonia suggested it needs to offer more actionable guidance. Overall, while the general goals of the Toolbox are clear to most, DTA and DST require improvements in clarity, guidance, and user orientation, especially for technical or less digitally fluent audiences. Table 31 gives a summary of the responses to question – “Is the Toolbox generally easy and intuitive to use?” Table 30: Summary of the responses to “Is the Toolbox generally easy and intuitive to use?” Country / Region DHK DTA DST Italy – EmiliaRomagna Yes Yes No Italy – Tuscany No (No answer) No Bulgaria Yes No No Estonia Yes (needs translation) No (multiple usability issues) No (needs major clarification) Germany No No access Yes France Yes No No DHK is generally seen as the most user-friendly, although France and Germany reported usability issues, and Estonia emphasized the need for language localization. DTA received the most negative feedback, especially regarding technical glitches (log-in, data loss, unclear results grid). DST is viewed as unclear and unintuitive by most respondents, with France, Bulgaria, Estonia, and Italy (Tuscany) all noting difficulties; only Germany found it intuitive. These findings highlight a clear need to improve interface usability, provide clearer terminology, localize content, and ensure functional reliability, especially for DTA and DST. Table 32 gives Average Usefulness Rating by Tool Across Each Business Model from question 6 Table 31: Average Usefulness Rating by Tool Across Each Business Model Business Model DHK DTA DST 86 Value chain 2.33 3.67 2.8 Collective and value chain 2.67 3.33 2.8 Agricultural production 2.83 4 3.4 Agricultural prod/value chain 2.67 4 3 Forestry 2.17 3.33 3 DTA shows the highest average usefulness across all business models, especially in agricultural contexts (4.00 in both “Agricultural production” and “Agri-prod/value chain”). This confirms that DTA is the most effective tool for cost optimization in soil-related decisions when well understood. DST performs consistently in the medium range, especially for agricultural production (3.40), reflecting a good fit with crop-level decisions. However, its performance is slightly weaker in collective and value chain contexts, indicating a need for better contextual guidance and clarity. DHK remains the least effective across all models, with the lowest score in forestry (2.17). This suggests that while DHK provides foundational knowledge, it is perceived as less directly actionable, especially for specialized applications like forestry. Enhancing its relevance through tailored content or interactive elements could increase its utility. Here is the summary of the comments from question 7 from the survey: DTA and DST are promising but require simplification, better interface design, and farmer-oriented language. DHK needs clearer content classification, better navigation, and more direct value for decision-making. There is a strong consensus on the value of integrating the toolbox into policy, education, and practical demonstration projects. Several countries call for capacity building and user support, highlighting the digital divide as a barrier to wider adoption. 5.3. Conclusions The NOVASOIL Toolbox, comprising three digital tools (DHK, DTA, and DST), was evaluated across several countries to assess its clarity, usability, practical value, and policy relevance. Overall, the feedback highlights the promising potential of these tools to support soil health practices, while also offering valuable suggestions for refinement and broader adoption. Understanding and Clarity DHK is widely understood and valued for its solid foundational content. Stakeholders across different countries appreciated its informative character, although some noted the need for more tailored guidance for specific sectors 87 like forestry and horticulture. DTA, while recognized as highly beneficial in supporting soil-health decision-making, received mixed feedback on clarity— mainly due to its complexity and access limitations reported in some countries, problems that have been resolved. DST was less well understood, especially by those with less technical expertise. It was noted that the tool contains complex terminology and detailed data requirements that may overwhelm some users. With better contextual explanations and useroriented design, both DTA and DST have strong potential to become more accessible and impactful. Usability and Accessibility DHK stands out as the most user-friendly of the three, although improvements in content navigation, classification, and format labeling would make it even more effective. DTA, despite being highly valued when accessible, was hampered by technical issues such as login difficulties, loss of data, and unclear result displays - problems that have been resolved. DST was often considered too advanced for general users, due to its data-heavy interface and technical language. Across the board, users suggested enhancing usability through simpler interfaces, clearer instructions, multilingual support, and more intuitive navigation. Addressing these points will significantly improve the user experience, particularly for farmers and practitioners with limited digital skills. Usefulness for Soil Health Business Models DTA emerged as the most practically useful tool, receiving the highest average usefulness ratings across all business model categories—especially in agricultural production contexts. This reflects its strong alignment with decision-making needs in soil management, provided that access and understanding barriers are addressed. DST demonstrated moderate effectiveness, particularly at the field level, though it was seen as less suited for broader value chain or forestry applications. DHK, while informative, was rated lower in terms of direct applicability, indicating a need to link its content more closely with on-the-ground decision-making. These findings show that all three tools offer distinct strengths, and with targeted improvements, they can serve as complementary components in a comprehensive soil health support system. Policy and Implementation Potential There is a strong consensus across participating countries on the strategic importance of incorporating the Toolbox into national and EU-level agricultural policies. Recommendations included using the tools to inform CAP-related subsidies, feasibility studies for farmers, and evaluations of advisory services. Additionally, there was a shared call for embedding the tools in agricultural education and professional training to foster digital literacy and long-term soil stewardship. Pilot projects, demonstration farms, and policy alignment were suggested as key steps to scale the tools and support uptake. Final Reflection 88 The NOVASOIL Toolbox offers a robust digital framework to advance soil health through evidence-based decision-making. While the tools show strong promise, especially DTA, achieving widespread adoption will require further refinement. Key areas for improvement include simplifying user interfaces, offering clearer contextual guidance, supporting capacity-building efforts, and ensuring full integration with policy frameworks. With these adjustments, the Toolbox is well-positioned to evolve from a promising innovation to a widely used, scalable solution for sustainable soil management across Europe. 6 Conclusions The testing and valorisation of the NOVASOIL toolbox across multiple European contexts provide clear evidence that digital solutions can significantly contribute to overcoming barriers in soil health business models. Main conclusions: 1. Complementary role of tools: The three instruments serve different but complementary functions. DTA excels in economic optimisation, DST in strategic and operational planning, and DHK in knowledge transfer and social engagement. Their integrated use is essential to maximise impact. 2. Economic and environmental synergies: Case studies demonstrated that SHBMs can reduce costs and increase income while delivering positive ecological outcomes. Vineyards in Bulgaria and olive systems in Spain illustrate how soil-oriented practices can achieve climatesmart outcomes when properly managed. 3. Cross-country variability: Results confirm that context matters — input-intensive systems (e.g., tomatoes in Italy) face higher CO₂ footprints, while perennial or low-input systems offer better sustainability performance. This underlines the need for tailored SHBMs adapted to national and regional conditions. 4. Stakeholder acceptance: CoP feedback confirms that the NOVASOIL tools are perceived as useful and relevant for practice, but greater efforts are needed to simplify interfaces, improve digital literacy, and provide demonstration projects to accelerate adoption. 5. Policy relevance: The tools have strong potential to be integrated into CAP monitoring frameworks, eco-schemes, and carbon farming schemes. Their use could improve transparency, support evidencebased policy, and strengthen farmer engagement in soil stewardship. The NOVASOIL toolbox is a practical and scalable innovation that can bridge science, policy, and practice. By combining economic, ecological, and social perspectives, it offers a solid foundation for building resilient, climate-positive, and inclusive soil health business models across Europe. 89 Resources 1. Nikolov D., Tzvetanova E., Boevsky I., Banov M., Kostenarov K., Todorova K. (2023b) NOVASOIL D3.2 Preliminary version of the knowledge hub for soil health business models 2. Nikolov D., Tzvetanova E., Boevsky I., Banov M., Kostenarov K., Marinova, Ts. (2023a) NOVASOIL D3.1 – Report on mapping existing incentives for sustainable soil health business models 3. Garrett, L. and Neves, B. (2016) Incentives for Ecosystem Services: Spectrum. Food and Agriculture Organization of the United Nations, Rome, Italy 4. Compagno, L., D’Urso, D., Latora, A. G., Trapani, N. (2013). The ValueAnalytic Hierarchy Process: A Lean Multi Criteria Decision Support Method. Manufacturing Modelling, Management and Control, 7(1), 875880. Doi: https://doi.org/10.3182/20130619-3-RU-3018.00573 5. Nikolov D., Tzvetanova E., Boevsky I., Banov M., Kostenarov K., Todorova K. (2024b) NOVASOIL D 3.5 Report on final version of the knowledge hub for soil health business models 6. Nikolov D., Tzvetanova E., Boevsky I., Banov M., Kostenarov K., Bankova V. (2025) NOVASOIL D 3.8 Report on final version of tools for analysis of the soil health business models 90 Acknowledgment