This cluster occupies the central position in the network connecting all the rest, because the scientific articles selected for this analysis focus mainly on clean energy production in agriculture. Therefore, it can be seen that there are numerous small nodes connected to the three main nodes of renewable energy, sustainability and agriculture. These in combination explain the research attempts to change agricultural production to a more sustainable system in terms of energy and water use, and also to reduce the greenhouse gas emissions share of agriculture, as this main node of the red cluster is exactly in the centre. Hence, all renewable energy applied in agriculture is always researched in terms of being environmentally friendly.
4.1.2.2 Funding organisations co-authorship network
Through the density visualisation in VOSviewer, the funding organisations of the international literature are visualized in a coloured network, whereby red colour indicates areas with high concentration of publications (Fig. 4).
Following the National Natural Science Foundation of China, the European Union (represented mainly by the nodes European Commission, Horizon 2020 framework program and 7th framework program) concentrates a large number of funded publications on fossil-energy-free agriculture. Since the EU arises as a key actor in funding research on fossil-energy-free agriculture, in the next phase, we focus our analysis on the papers produced by H2020-funded projects4 to investigate the quality of the produced knowledge in these projects.
4.2 Focus on EU results
4.2.1 Statistical indicators
Our search in the CORDIS database according to the aforementioned methodology yielded 156 research projects out of which 37 were funded under the H2020 framework5 and had published peer-reviewed articles. The results are presented in detail in Table 2.
Table 2
Analysis of the selected research projects
Total number of selected research projects acquired from CORDIS database
|
156
|
H2020 Projects
|
95
|
H2020 Projects that produced papers (peer-reviewed & conference papers)
|
40
|
H2020 Projects that produced peer-reviewed papers
|
37
|
Different Action types specify H2020 objectives including Research and innovation actions (RIA)6, Innovation actions (IA)7, Coordination and support actions (CSA)8, European Research Council (ERC)9, Marie Skłodowska-Curie Actions10, SME Instruments11 and Fast track to innovation (FTI)12. Regarding the action type of the 37 analysed projects, most are funded by RIA (14), and by IA (13), followed by seven CSA, one SME-2, one ERC-STG and one ERA-NET – Cofund. This result is presented in Fig. 5. The full list of research projects identified in CORDIS is available in ANNEX IV.
By examining the scientific papers produced by the aforementioned projects, we acquired 345 peer-reviewed articles to be analysed further. The final numbers are presented in detail in Table 3.
Table 3
Analysis of the scientific papers derived from the chosen research projects
Papers derived with funding number and project name from Scopus
|
507
|
Irrelevant papers found
|
78
|
Conference papers
|
81
|
N/A Papers
|
3
|
Peer reviewed papers to be analysed
|
345
|
In their majority, these papers stem from RIA (220), followed by IA (85), CSA (25), ERA-NET – Cofund (13), ERC-STG (2) and SME-2 (1) projects. The results are presented in Fig. 6. In ANNEX V, the full list of the research papers identified from the 37 research projects is presented. This result seems reasonable, as indeed RIA projects are dedicated to basic and applied research trying to bring novel ideas to prototyping, while IA projects focus more on demonstrating existing technologies, optimising them and bringing them closer to commercialization. On the other hand, CSA projects do not focus directly on research results but attempt to develop the conditions for specific scientific themes to become more known and integrated into real life, by developing mainly policy and data analysis papers. ERA-NET, ERC-STG and SME-2 funding programmes are not represented with a large number of projects, which leads to a small number of published papers as well.
4.2.2 Lexicographic focus to explore the quality of the produced knowledge
Next, the results of the dictionary-based text analysis of the European corpus of literature are presented. For each paper, the content analysis software counted how many keywords from each dictionary are present. This resulted in a percentage allocated to each type of knowledge (normative, techno-economic, transformative or systems knowledge) within each paper, as well as an average percentage among all papers. This analysis, presented in Fig. 7, shows that research papers on fossil-energy-free agriculture are dominated by techno-economic knowledge, which averagely accounts for 58.5% of all dictionary words found in the papers and, therefore, outperforms the other categories altogether. Systems knowledge averagely accounts for 20.7%, normative knowledge for 12.5%, and transformative knowledge for 8.3% of the detected dictionary words.
A deeper examination of the content analysis results further reveals the dominance of TEK, even horizontally across the other knowledge types. Each knowledge type comprises four sub-categories, which represent different aspects of the main theme. For example, transformative knowledge consists of four elements: policy and decision-making; participation; motivation; communication & education. Figure 8 shows in detail the relative presence of the sub-categories in the analysed papers. We may observe that for each knowledge type the sub-categories that are more relevant to the dominant techno-economic paradigm are the most prominent: ‘efficiency’ in NK, ‘market’ and ‘technology’ in TEK, ‘policy and decision making’ in TK and ‘function and process’ in SK. On the contrary, the least numerous sub-categories (less than 2% of total dictionary words) are ‘justice and ethics’ in NK, ‘resilience’ in SK, ‘motivation’ and ‘communication and education’ in TK. Thus, the most transformative dimensions of each knowledge type are the most under-represented.
This finding suggests that the EU funded research products in fossil-energy-free agriculture have followed a rather reductionist, technocratic and mono-disciplinary approach that suits the production of techno-economic knowledge and have hardly embraced a more transdisciplinary and transformative paradigm. The dominant approach underestimates the complexity and wickedness of sustainability problems by reducing them to efficiency problems and obscuring aspects of their characteristics which are “collectively emergent, culturally mediated, politically driven, and/or partly unknown” (Markusson et al. 2022, p. 2).
4.2.3 Focus on transformative papers and projects
Among the H2020-derived papers, which have been analysed with dictionary-based text analysis, we further examined those with the highest percentage of transformative knowledge. Specifically, the 60 papers with the highest TK percentage were selected, ranging from 16.7–61.1% of transformative knowledge content. Through the concordance check performed with Yoshikoder, four of these papers have been excluded as irrelevant. The remaining 56 papers were analysed to identify potential correlations that explain their increased content of TK compared to the rest of the papers. The aforementioned papers are highlighted with yellow in ANNEX V.
An initial analysis shows that these papers are not concentrated in specific journals; they are rather published in a variety of journals. Additionally, publishing year does not seem to be an important factor, as there is no tendency in more recent papers to contain higher (or lower) percentages of transformative knowledge. Unlike what the recent literature suggests (Friedrich et al. 2021), our analysis shows that research on sustainable agriculture has not yet shifted away from the techno-economic focus.
Instead, there seemed to be specific projects that have produced a large number of ‘transformative’ papers. To further investigate this correlation, for each of these transformative papers, we associated its H2020 research project13. As a result, a list has been created with H2020 projects sorted by the high-TK papers they have generated, which is presented in Table 4.
Table 4
H2020 projects with high TK% papers
Projects having papers with TK > = 25%
|
Project name*
|
Number of papers
|
Project’s high-TK / project’s total # of papers
|
LIFT
|
8
|
42.11%
|
SOILCARE
|
7
|
15.91%
|
IOF2020
|
5
|
42.11%
|
BioEcon
|
3
|
23.08%
|
SET-Nav
|
3
|
21.43%
|
WiseGRID
|
2
|
100.00%
|
MacroFuels
|
2
|
22.22%
|
REEEM
|
2
|
7.14%
|
inteGRIDy
|
1
|
6.25%
|
ISAAC
|
1
|
50%
|
Smart-AKIS
|
1
|
25%
|
* All of these projects are represented in this table with their acronyms but all information about them is given in Annex VI.
The subject of all projects with the largest number of TK papers, and their characteristics are presented in Annex VI. As this investigation is a fortiori policy oriented, we meant to relate TK outcome of projects to the action types that characterize H2020 projects, and the respective funding modes. In Table 5, it can be seen that the majority of the projects with high TK are RIA projects followed by IA and CSA. We observe that CSA projects have a higher percentage of transformative papers among their total produced papers (16%), while this percentage for RIA and IA projects is 3% and 5% respectively.
This can be explained by the fact the CSA funding covers primarily accompanying measures concerning policy dialogues and mutual learning exercises and studies, as well as complementary activities of strategic planning, networking and coordination between programmes in different countries. Thus, research and innovation outcome by various projects is compiled in the frame of CSA funding for dissemination, awareness-raising and communication to ultimately support policy making. On the other hand, RIA and IA projects aiming at producing new knowledge/technology and new or improved products respectively have resulted in a higher absolute number of TK papers, along with a much higher number of total produced papers compared with CSA projects.
Table 5
Number of research projects per action type for the different TK thresholds
Action type
|
TK > = 25%
|
TK > = 20%
|
TK > = 16.7%
|
% of total papers
|
RIA
|
5
|
5
|
6
|
2,7%
|
CSA
|
3
|
3
|
4
|
16%
|
IA
|
4
|
4
|
4
|
4,7%
|
Therefore, scientific papers with high TK can be correlated with RIA projects as these projects’ main goals are to establish new knowledge and at the same time explore the feasibility of new/improved technology. Although the large part of research outcome of RIA projects identifies to knowledge types such as systems knowledge pointing out complex system interactions and techno-economic knowledge evaluating economic feasibility of technology a prerequisite for innovation, strong concern for transformative knowledge can also be observed. In fact, RIA projects firstly undertake a thorough analysis to assess the status of the studied subject, and then new methodologies are produced, so as to improve the situation and introduce new technologies. For example, the LIFT project, which is one of the most transformative projects in terms of its produced papers, investigated the potential benefits of the adoption of ecological farming in the EU through 30 case studies and then promoted the performance and sustainability of such systems across the EU.
Finally, we check the correlation between the worldwide and the European research by characterizing the most ‘transformative’ EU derived papers based on the previously identified clusters of the global literature. To this end, we review the titles, keywords and abstracts of these papers and match them to the previously presented thematic clusters (or their sub-sections) to understand whether specific themes among the clusters relate better to the production of transformative knowledge. The papers were categorised according to the closest relation to the clusters, as shown in Table 6.
Table 6
Number of research papers related to the clusters defined from the international literature review
Cluster Name
|
Number of papers mainly related to the cluster
|
Blue Cluster: Biomass Conversion into Energy and circular by-products
|
4
|
Green Cluster: Conservation Agriculture and its impacts
|
8
|
Light Blue Cluster: Climate change and food security
|
17
|
Orange Cluster: Life Cycle Assessment for agricultural systems
|
1
|
Purple Cluster: Energy Efficiency through smart agricultural technologies
|
6
|
Red Cluster: Heat Pumps and Solar Technologies in Agriculture
|
0
|
Yellow Cluster: Renewable Energy for sustainable agriculture
|
18
|
Non-Related
|
3
|
It can be observed that the majority of TK papers devoted to the subject of fossil-energy-free agriculture refer to renewable energy systems (Yellow Cluster) and the cluster of biomass conversion into energy (Blue Cluster), which in reality is a sub-category of the first one as they both refer to direct energy production systems in farms. These categories of FEFTS cover the direct energy impact of agriculture, which was expected to occupy the interest of the TK papers under consideration. Climate change (Light Blue Cluster) follows, and conservation agriculture (Green Cluster) comes next, which are also closely interrelated, as they refer to strategies and practices of sustainable and ecological agricultural production. Smart agricultural technologies (Purple Cluster) close the analysis, showing that the three latter clusters cover all FEFTS concerning reduction of indirect energy consumption in agricultural practices. Life Cycle Assessment of agricultural systems (Orange Cluster) and Heat pumps (Red Cluster) has negligible participation in the selected papers, showing that environmental impact is still not in the core of agricultural transformation and that heat pumps are very innovative and specific to buildings’ FEFTS, making them still non relevant for the immediate FEFTS integration to European farms.
The exercise discussed above proves it is difficult to relate with accuracy these 56 most transformative papers of the H2020 projects under analysis to the seven clusters identified in international literature. This may be a result of concurrently scattered efforts from various thematic areas to produce more transformative research, without however more organized endeavours. Papers of high TK are not always related to a specific topic, but they are wider in perspective trying to analyse more the communicational, educational, motivational, participatory and policy making components of knowledge.
[4] 2014 HORIZON 2020 in brief The EU Framework Programme for Research & Innovation URL: https://wayback.archive-it.org/12090/20181221014039/http://ec.europa.eu/programmes/horizon2020/sites/horizon2020/files/H2020_inBrief_EN_FinalBAT.pdf
[5] Horizon 2020 was the EU's research and innovation funding programme from 2014-2020 with a budget of nearly €80 billion. The programme has been succeeded by Horizon Europe. All news, events, programme details, project lists and more are available on the archived Horizon 2020 website: https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-2020_en
[6] Research projects of multi-actor consortia tackling clearly defined challenges, which can lead to the development of new knowledge or a new technology.
[7] Focused mostly on closer-to-the-market activities (e.g., prototyping, testing, demonstrating, piloting, scaling-up) aiming at producing new or improved products or services from multi-actor consortia.
[8] Coordination and networking of research and innovation projects, programmes and policies from multi-actor consortia.
[9] Projects evaluated on the sole criterion of scientific excellence in any field of research, carried out by a single national or multinational research team led by a ‘principal investigator’, either excellent young, early-career researchers, already independent researchers or senior research leaders.
[10] International research fellowships in the public or private sector, research training, staff exchanges. It is earmarked for early-stage researchers or experienced researchers, technical staff, national/regional research mobility programmes.
[11] This instrument is aimed at highly innovative SMEs with the ambition to develop their growth potential. It offers lump sums for feasibility studies, grants for an innovation project’s main phase (demonstration, prototyping, testing, application development, etc.); lastly, the commercialisation phase is supported indirectly through facilitated access to debt and equity financial instruments. It refers to either a single SME or a consortium of SMEs established in an EU or Associated Country.
[12] FTI supports actions undertaking innovation from the demonstration stage through to market uptake, targeting relatively mature, ground-breaking new technologies, concepts, processes and business models that need final development to be able to shape a new market and achieve wider deployment.
[13] It should be mentioned that from our analysis we came across 8 research projects that were not included in our original list of available projects but were under the H2020 Framework. This occurred due to the fact that each of these projects has produced a paper jointly with another project that was already included in our analysis. The aforementioned projects were removed from our analysis as they did not meet the criteria set in our methodology and at the same time the papers produced from them were already counted and analysed in the chosen research projects. These projects are: GENIALG (coproduced 2 papers with MacroFuels project), LANDSUPPORT (coproduced 1 paper with SOILCARE project), LANDMARK (coproduced 1 paper with SOILCARE project), CONSOLE (coproduced 1 paper with LIFT project), INVADE (coproduced 1 paper with SET-Nav project), TRANSrisk (coproduced 1 paper with REEM project) and SolACE (coproduced 1 paper with SOILCARE project). Furthermore, there is one project called NEFERTITI which coproduced a scientific paper together with 2 other projects which are included in our list, IOF2020 and SmartAgriHubs. For the purposes of our analysis this paper was removed both from the NEFERTITI and IOF2020 projects, with the latter being chosen as it produced more papers that the SmartAgriHubs project.