Agri-Food Research in Europe:
Mapping report
Bibliometric mapping of agri-food research
activities in 33 countries and survey of the
research capacity in 14 countries
January 2008
This report is part of the project “EU AGRI MAPPING” which has been awarded financial support by
the European Commission through the contract FP6- 506087 under the 6th framework programme of
the European Community for research, technological development and demonstration activities. The
Community is not responsible for any use that might be made of the content of this publication.
ACKNOWLEDGEMENT
This report forms part of the deliverables from "EU AGRI MAPPING ", a project which has
been awarded financial support by the European Commission under the 6th Framework
Programme. More detailed information on the project can be found on the website
http://www.agrifoodresearch.net. The following reports are available:
Country reports
33 country-reports on the agri-food research system (249 pages)
Country reports summary Summary of the trends and needs in agri-food research (50 pages)
Mapping report
Bibliometric mapping of agri-food research activities in 33 countries and
survey of the agri-food research capacities in 14 coutries (68 pages)
Final report
Overview of the European agri-food research landscape (20 pages)
Edited by:
Balázs BORSI and Attila UDVARDI
Based on contributions by:
Balázs BORSI
Olivier CHARTIER
Gábor PAPANEK
András SCHUBERT
Attila UDVARDI
Mária VANICSEK
Erzsébet VISZT
2
CONTENTS
Foreword .................................................................................................................................... 4
1. Objectives and methodology .................................................................................................. 5
2. European agriculture by country groups .............................................................................. 10
3. Agrifood research in the EU-33 countries – a bibliometric assessment .............................. 14
3.1 The position of Europe in agrifood scientific publications ............................................ 14
3.2 The importance of agrifood science in national S&T .................................................... 17
3.3 Specialisation patterns .................................................................................................... 19
3.4 The growth of agrifood science publications ................................................................. 20
3.5 A gap between institutions ............................................................................................. 21
4. Agrifood research capacities surveyed in the EU-12+2 countries ....................................... 22
4.1 Institutional setup and financing .................................................................................... 22
4.2 Human resources ............................................................................................................ 26
4.3 Research infrastructure ................................................................................................... 30
4.4 Innovative and scientific output ..................................................................................... 32
4.5 Research competence ..................................................................................................... 36
4.6 Excellence ...................................................................................................................... 39
5. Conclusions .......................................................................................................................... 42
References ................................................................................................................................ 44
Annexes .................................................................................................................................... 45
7.1 Agrifood fields of science .............................................................................................. 45
7.2 The bibliometric methods............................................................................................... 49
7.3 Basic agrifood bibliometric indicators ........................................................................... 53
7.4 Survey methodology ...................................................................................................... 62
7.5 Basic survey results – summary statistics by countries.................................................. 68
3
Foreword
When the AgriMapping project was launched in January 2006, the project team felt that we
stepped on the way to European agricultural and food research ‘united in diversity’. The
journey looks long, and this research report in the reader’s hand is a first attempt to set a
common way of thinking about the present, and more importantly, the future of European
agrifood research. It was not at all easy to compile this document because the agrifood
research domain is complicated, and usually the agrifood industry, which is undergoing
important changes, is considered sensitive throughout the world. Nevertheless, we believe that
Europe needs to find appropriate answers to global challenges also in the agrifood arena. To
find those answers, policy makers and stakeholders should be aware of what is actually at
stake.
The ‘Mapping Report’ is the synthesis of the statistical information and the survey results
available to describe agrifood research in European countries. The main source of information
was the results of a bibliometric analysis (in the EU-33 countries), a web-assisted survey (in
the EU-12+2 countries) and the country reports (for the EU-15 countries) prepared in the
AgriMapping project frame in 2006 and 2007. When relevant, available complementary
statistics were also used.
It needs to be stressed that at the time of writing this report the response rate to the survey in
the EU-12+2 countries surpassed 60% of the research organisations registered as ‘agrifood
research organisation’ by the AgriMapping project. This gives a sound base for most of the
statements in the study, however, we should also know that the sample of research
organisations used is strongly biased towards state-owned or public organisations. Altogether
about 1900 agrifood research units were identified, and the answers of 1160 could be used for
this report. This gives an acceptable base for most of the statements in this report, which
means that no major deviations would be expected if the response rate increased.
Nevertheless, the Polish and the Turkish figures derived from the survey results should be
treated more as reliable approximations.
The editors would like to express their sincere thanks to Olivier Chartier, the AgriMapping
project co-ordinator, who was ready day and night to discuss the issues that emerged during
the compilation of this report. We are grateful to Zsuzsa Antal, Nastasia Belc, George
Boustras, Marie Fauchadour, Max Feinberg, Dora Groó, Emese Karácsonyi, Nada Konickova,
Aneta Maszewska, Ivan Minkov, Claudia Elena Mosoiu, Tiiu Ohvril, Bozena Podlaska,
Joanna Pullicino, Algirdas Radzevicius, Pavol Schwarcz, Ilze Stokmane, Irma Tomazic, Tuba
Turan, Liliana Vizintin, And Lana Zutelija, without whom the extensive international survey
of agrifood research entities could not have been a reality. We deeply acknowledge the high
quality bibliometric analytical work delivered by András Schubert, which provided a
European-level insight into the diversity of agrifood research. Last, but not least, Anna
Munkácsy and Tamás Tompa must be mentioned for their invaluable technical assistance in
processing the data.
Budapest, January 2008
Balázs Borsi
editor
GKI Economic Research Co.
4
1. Objectives and methodology
The overarching aim of this mapping report is to present where Europe and the New Member
States and the candidate countries of the European Union stand in terms of agrifood research.
We hope that the report helps the identification of strengths, weaknesses and gaps, which can
then serve as a knowledge base for thinking about future scenarios in the agrifood industry in
general and in agrifood research in particular. The tool chosen to reach this general objective
is a mapping exercise.
The term ‘mapping’ has become a widely used buzzword recently. Mapping does not have an
agreed definition. In practice it refers to a systematic and structured effort, in which we
explore and present an object in a previously unknown structure. This structure may refer to:
 geographic considerations, when the phenomenon explored (the subject or unit of
analysis) is presented by countries, regions or cities;
 classification system(s), when the units/subjects analysed are presented according to
pre-defined groups, and these groups are not necessarily organised in a hierarchic
structure; and
 quality or quantity considerations, when the phenomenon is presented according to
different quality or quantity levels.
Mapping is used in many different subject areas. For example, in cartography, mapping is the
creation of maps depicting features on the earth's surface. In psychology and cognitive
science, mapping is the relationship between a source domain and target domain or the
relation between the elements of source and target in an analogy. In genetics, gene mapping
reveals the relative position of genes in a genome. In computer science, it can be any
computable function, a procedure, or a table, e.g. relating a key to its value in an associative
array. In our domain, i.e. science and technology policy, mapping refers to the geographical
distribution and concentration of a component of the National Innovation System.
Box 1: National Innovation System (NIS)
According to innovation system theory, innovation and technology developments are results of a complex set of relationships
among actors in the so-called National Innovation System. Actors in the NIS include enterprises, universities and
government research institutes, financial institutes etc.
A NIS can be defined as follows:
“the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and
diffuse new technologies” (Freeman, 1987)
“the elements and relationships which interact in the production, diffusion and use of new, and economically useful,
knowledge ... and are either located within or rooted inside the borders of a nation state” (Lundvall, 1992)
“a set of institutions whose interactions determine the innovative performance ... of national firms” (Nelson, 1993)
”the national institutions, their incentive structures and their competencies, that determine the rate and direction of
technological learning (or the volume and composition of change generating activities) in a country” (Patel and Pavitt, 1994)
“that set of distinct institutions which jointly and individually contribute to the development and diffusion of new technologies
and which provides the framework within which governments form and implement policies to influence the innovation
process. As such it is a system of interconnected institutions to create, store and transfer the knowledge, skills and artefacts
which define new technologies” (Metcalfe, 1995)
See: OECD (1997): National Innovation Systems, OECD, Paris
In furthering the development of the European Research Area (nota bene: the European
Innovation System), mapping is an important activity as it aims to increase the visibility of
European research and development capabilities.
5
In this report we analyse the research activities of Europe that are related to agricultural
production, food industry and the rural society. The following notions and definitions are
given:
 Research and development (R&D): “the creative work undertaken on a systematic
basis in order to increase the stock of knowledge, including knowledge of man, culture
and society, and the use of this stock of knowledge to devise new applications”
(OECD [2002] p. 30). What makes R&D different from pure science is its orientation
towards applications.
 Agricultural production consists of two large subsectors, animal production and crop
production. Animal production includes establishments that raise livestock, such as
beef cattle, poultry, sheep, and hogs; farms that employ animals to produce products,
such as dairies, egg farms, and apiaries (bee farms that produce honey); and animal
specialty farms, such as horse farms and aquaculture (fish farms). Crop production
includes the growing of grains, such as wheat, corn, and barley; field crops, such as
cotton and tobacco; vegetables and melons; fruits and nuts; and horticultural
specialties, such as flowers and ornamental plants (U.S. Department of Labor, Bureau
of Labor Statistics – www.bls.gov on February 2008).
 The food industry covers various businesses that supply much of the food energy
consumed by the population. Subsistence farmers can be considered outside of the
scope of the modern food industry. Among others, the food industry is mainly
concerned with raising of crops and livestock, the production of seafood; regulations
(including food quality and safety), manufacturing (agrichemicals, seed, farm
machinery and supplies, agricultural construction, food processing, food preparation
and packaging etc.); food conservation and transportation technologies including
logistics; trade.
 Rural society is a society in which there is a low ratio of inhabitants to open land and
in which the most important economic activities are the production of foodstuffs,
fibres, and raw materials (Encyclopaedia Britannica – www.britannica.com on
February 2008).
From the above it follows that agrifood research means R&D activities, the results of which
are used in agricultural and food industry production as well as developing the performance
and well-being of the rural society. We should also note that there are areas, for which
agrifood research might be relevant but which are concerned rather with industrial activity
(such as the production of plants for industrial use). In any case, for ourselves we understood
agrifood research with the broadest possible scope.
Mapping of NIS components, such as the agrifood research sub-system, can have different
foci:
 mapping the research activities is the identification of agrifood research and
development areas addressed by research institutions;
 mapping the research capacities aims to explore the research capacities of the
institutions active in agrifood research and development areas;
 mapping of competencies is the identification of research institutions competent in
agrifood research and development areas;
 mapping of research excellence aims at identifying the best research performing
institutions in agrifood research and development areas.
6
The depth and coverage of the mapping exercise can also differ. Mapping can be realised at
the level of research teams, research institutions or the level of a region, a country or a group
of countries.
In this report, mapping was equally given a geographical, a classification system and a quality
ladder structure. First, in the geographical approach, agrifood research activities are explored
and presented by countries and country groups. Second, agrifood research is understood in the
broadest possible spectrum, whereby the project team defined 11 broad fields of agrifood
research, divided into 42 fields and 187 sub-fields and these fields are used in the study.
Third, agrifood research activities are also viewed as who is competent in what, where quality
infrastructure and a critical mass of researchers exist and where we can find notable scientific
and innovative output. Fourth, we have also looked at where some excellence can be find
looking at multiple criteria from the AgriMapping survey results.
Table 1
Agrifood science and research fields* as defined by the AgriMapping consortium
Broad fields of science / research
A
economic, social and political aspects
C
food technology, human nutrition and
consumer concerns
engineering, mechanisation, ICT
D
plant breeding and biotechnology
E
plant production and protection
F
animal production and husbandry
G
animal health and welfare
B
H
I
aquaculture and fisheries
forestry and landscape
management of natural and biological
J
resources
K horizontal issues
*For the full classification see the Annex.
Source: AgriMapping network
Sub-fields
A1. production and producer issues / A2. rural development / A3.
micro economics / A4. horizontal expertise / A5. market issues / A6.
policy issues / A7. agricultural public finance
B1. human nutrition / B2. post harvest and food technology / B3.
consumer concerns
C1. engineering & mechanisation / C2. ICT
D1. plant genetics / D2. plant molecular biology / D3. plant
breeding / D4. plant biotechnology and non food use
E1. plant physiology / E2. plant nutrition / E3. plant health / E4.
plant production systems
F1. animal genetics and breeding / F2. animal husbandry / F3.
production systems / F4. nutrition and feed / F5. non food use of
animal products
G1. animal physiology / G2. animal behaviour / G3. animal health /
G4. animal welfare / environmental
H1. aquaculture / H2. fisheries
I1. forestry / I2. forest products
J1. soil / water / J2. biological resources / J3. environment / J4.
climatology and climate change
K1. statistics applied to agriculture research / K2. food chemistry
The following methods were used in gathering the information:
 Web-assisted survey: in the EU-12+2 countries (the New Member States1 and
Candidate Countries of the EU: Bulgaria, Croatia, Cyprus, Czech Republic, Estonia,
Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovak Republic, Slovenia,
Turkey) a survey was realised to collect information about agrifood research centres.
A test occurred in 4 countries (Turkey, Poland, Czech Republic and Latvia), to collect
ground feedback on the questionnaire, which asked about the type of the research
organisation, the human resource conditions, the international mobility of researchers,
the research infrastructure, the scientific production, the research activity and last, but
not least the financing of the organisations (for details see the Annex).
 Bibliometric analysis: András Schubert (researcher, Institute for Research Policy
Studies, Hungarian Academy of Sciences, editor of the journal Scientometrics)
1
At the time of the project start Romania and Bulgaria was not yet member of the European Union, so earlier
project documents refer to this group as the EU-10+4 countries.
7

defined search profiles for the agrifood research fields, with the help of which
different statistical extractions took place in the Web of Science database.
Multivariate statistical analysis (in particular: cluster analysis) was used with the
available statistics and the bibliometric search results.
Box 2: Examples of mapping in the science and technology policy domain
Mapping of Excellence: With the aim to map scientific and technological excellence, the European Commission launched a
pilot exercise in 2000 in three areas (life sciences, nanotechnologies and economics). The exercise was intended to evaluate
and refine the methodology to conduce mapping of excellence exercises.
HERA: Humanities in the European Research Area - is an EU 6th Framework Programme ERA-NET project aiming at
strengthening the European voice in the Humanities. HERA brings together one pan-European and 13 national research
funding agencies across Europe in order to coordinate research activities and thereby transcend historical limitations and
develop new Europe-wide research agendas.
NW-IALAD: The integrity and safety assessment of concrete dams plays an important role for the infrastructure of many
states of the EC. However, the water reservoirs created by those dams are often considered as a potential hazard to the
population. The safety of these important structures is of great concern to the owners, operators and engineers as well as to
the public. This is the motivation to establish a thematic network, which brings together government authorities, researchers
from universities and end users from companies to conduct a state of the art review on integrity and safety assessment tools
for concrete dams, to map current research activities and to identify the needs for further research activities.
The project MORESS ("Mapping of Research in European Social Sciences and Humanities") is an important contribution to
the endeavour to establish a European Research Area in the social sciences and humanities. It has been conceived,
organized and coordinated by the European University Association (EUA) with the aim to improve access to information on
research in social sciences and humanities. Through bringing together multiple sources of information in Europe into an
integrated structure, MORESS aims to provide useful tools for interested researchers and decision-makers, and to enhance
the future quality of European research.
RECORD was a Thematic Network project of the EU, being an acronym for "Recognising Central and Eastern European
Centres of RTD: Perspectives for the European Research Area". Experts of the RECORD network went through a 24 month
long interactive learning process on benchmarking RTDI organisations and published two books: a Benchmarking Manual
and an Experimental Map of Centres of Excellence in Central and Eastern Europe.
The Research Evaluation and Policy Project (REPP) is Australia's leading centre for the systematic evaluation and mapping
of research across all fields of scholarship. A major focus of REPP is research on the advanced quantitative analysis of
scientific performance and the organisational structure of Australia's research landscape, and REPP regularly conducts
bibliometric analyses of scientific publications produced under the patronage of publicly-funded bodies such as the ARC,
CSIRO and NHMRC. Parallel to this, REPP also recognises the value of developing novel qualitative and quantitative
approaches to research assessment, and the need to generate 'metrics' or indicators sensitive to the research and
dissemination practices of a variety of fields not well served by standard bibliometric approaches, particularly in the social
sciences, humanities and arts, as well as disciplines in the applied sciences such as computing and engineering.
Mapping of research financing organizations in the US, China, and Japan: This report is a first mapping of research financing
organizations in the three countries. The study has been initiated by VINNOVA with the intention to enable a more in-depth
study on Swedish scientists and researchers possibilities of finding financing and cooperation projects with extra-European
environments.
For further reference see:
http://www.heranet.info/
http://nw-ialad.uibk.ac.at/
http://vt-www.bonn.iz-soz.de/moress/
http://www.record-network.net/
http://repp.anu.edu.au/
http://www.vinnova.se/upload/EPiStorePDF/MappingOfResearchFinancingOrganizationsInTheUSChinaAndJapan.pdf
Most of the mapping of research activities listed in Box 2 relied on bibliometric and patent
statistics analysis or empirical survey, coupled with expert opinion. The AgriMapping report
8
is unique in its approach, because it combines survey methodologies with a bibliometric
analysis, not giving higher priority to any of them.
Before analysing and drawing conclusions on European agrifood research as such, we have to
see the basic characteristics of the environment into which it is embedded. In the next chapter
we present the reader a grouping of European agrifood industry and research, which hopefully
contribute to understanding the position of the different countries that are analysed in
subsequent chapters.
Mapping European agrifood research is done from two angles. First, with the help of a
bibliometric analysis European agrifood research is studied as a whole. We show Europe’s
position, the importance of agrifood science in the EU-33 countries, the growth of
publications and an introduction to the analysis of institutional level data.
Second, with the help of survey data in the EU-12+2 countries, we explore the institutional
setup, the general financing, the human resources and the infrastructure of agrifood research.
The performance of the different EU-12+2 countries is also assessed. What is the performance
in agrifood research fields? Where, in which agrifood research fields can particular
competences be identified? What strengths and weaknesses do the countries show in terms of
research output and outcome? Which countries can attract more of the agrifood researchers
from abroad? These are the questions that the ‘Agrifood research capacities surveyed in the
EU-12+2 countries’ chapter addresses.
9
2. European agriculture by country groups
European countries have very different endowments for agriculture. First we examine whether
there are similar characteristics for agriculture and the agrifood sector between the European
countries. We use k-means cluster analysis with seven centres to create seven country-groups
with similar parameters.
Box 3: Cluster analysis
Cluster analysis is an exploratory data analysis tool which aims at sorting different objects into groups in a way that the
degree of association between two objects is maximal if they belong to the same group and minimal otherwise. Cluster
analysis can be used to discover structures in data without providing an explanation/interpretation. In other words, cluster
analysis simply discovers structures in data without explaining why they exist.
In general, the k-means method will produce exactly k different clusters of greatest possible distinction. It should be
mentioned that the best number of clusters k leading to the greatest separation (distance) is not known as a priori and must
be computed from the data. Standardisation of the variables is frequently done to get rid of the bias caused by different
scales.
For further reference see e.g.: http://www.statsoft.com/textbook/stcluan.html
We have run the cluster analysis with 9 variables. Data that characterise the agricultural
potential and efficiency of a country and are scale-independent (country size has no influence)
were chosen. The latest available 2004 indicators were used. The variables used are the
following:
 agriculture, value added (% of GDP);
 food, beverages and tobacco, value added (% of GDP);
 agricultural machinery, tractors per 100 hectares of arable land;
 arable land (hectares per person);
 permanent cropland (hectares per person);
 permanent pasture (hectares per person);
 employment in agriculture (% of total employment);
 food import per population (1000 US$)
 food export per agricultural worker (1000 US$).
For Israel and Slovakia some of the data were missing (GDP data for Israel and land data for
Slovakia), so they were left out from the analysis. In Iceland mechanisation (tractors per
hectares of arable land), in Ireland food industry GDP is very high, so they were also left out
as they represent special cases.
10
Table 2
Groups of European countries by selected agrifood variables
(characteristic average 2004 data for the groups are shaded)
Legend: Green cells: 50 percent higher values than the average; red cells: 50 percent lower values than the
average
Source: GKI computations
Group 1: Romania and Turkey
The share of agricultural value added in the GDP is the highest amongst the groups, and also
the food industry has the highest weight in the case of these countries. Agriculture accounts
for nearly one-third of employment, mechanisation is poor and external trade indicators are
also at poor levels.
Group 2: Bulgaria, Croatia, Hungary, Latvia, Lithuania and Poland
The share of agriculture in GDP is higher than in more developed economies, but
substantially lower than in the first group. The arable land in hectares per person is the highest
between the analysed country groups. Mechanisation of production is poor, but employment
in agriculture has a marked weight in the labour force structure. The export productivity of
agriculture is higher than in the previous country group but lags substantially behind that of
the developed economies.
Group 3: Greece, Portugal and Spain
11
In this group of the Mediterranean countries agriculture has a lower weight in GDP than in the
previous groups. The importance of agriculture in employment and the export productivity is
similar to that of the preceding group, however, mechanisation is better. The permanent
cropland and the permanent pasture in hectares per person are at the highest level between the
country groups.
Group 4: Austria, Cyprus, France, Czech Republic, Germany, Italy, Malta, Norway, Slovenia,
Switzerland and the United Kingdom
This is the most heterogeneous group, but these countries are similar in terms of the
agricultural statistics used for the analysis. For different reasons mechanisation of the
agrifood sector is at high levels, but agriculture in general has a low weight in the economy.
Group 5: Denmark, Estonia, Finland and Sweden
In the Scandinavian countries the productivity agrifood export is outstanding, but agriculture
has low importance in GDP production and employment.
Group 6: Belgium, the Netherlands and Luxembourg
The Benelux states are a very specific country group of developed economies, where the
otherwise low-importance agrifood industry specialises for the export of expensive agrifood
products. Export productivity is remarkable and so is the import intensity of agrifood
products.
12
Fig. 1
The 6 groups (by the general agriculture and food industry characteristics)
Source: GKI Economic Research Co.
By extracting well-interpretable country groups, the above cluster analysis provides us a
snapshot of European agriculture. Certainly, the different country groups feature different
state of agricultural development. Their prospects and further growth will depend on the
responses given to the new challenges facing agriculture and agrifood research.
According to the EC [2007] report, one of the major hurdles facing Europe in making the
transition knowledge based agri-futures in the need to address the growing challenge of
knowledge failures. European agricultural research is currently not delivering the type of
knowledge, which is needed by end users in rural communities as they embark on the
transition to the rural knowledge-based bio-society. The problems are not exclusive to
agricultural research but they are felt more acutely in this sector where the role of traditional,
indigenous knowledge is already being undermined as a result of the growing disconnection
with ongoing research activity.
The following parts of the Mapping Report tries to assist the debate by showing what could be
seen from European agrifood research with the help of bibliometric data and survey of
agrifood research organisations.
13
3. Agrifood research in the EU-33 countries – a bibliometric assessment
3.1 The position of Europe in agrifood scientific publications
Based on the bibliometric data analysis,2 the EU-33 countries together have a dominant
position in agrifood research in the world. Nevertheless, on average scientific papers from the
United States have greater impact as they are more frequently referred to: the average citation
per paper is about 30% higher than that of the EU-33 countries.
Fig. 2
The number of agrifood publications and citations in 1996-2005
Publications
Citations
Rest of
the world
30%
Rest of
the world
22%
USA
30%
USA
38%
EU-33
40%
EU-33
40%
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences. For the methods used please consult the Annex.
If measured by their share in prestigious publications, such as the ones in the Web of Science
(WoS) database, five countries dominate European agrifood research. The UK has the largest
portion, about one-fifth of the agrifood publications, but it is known that the WoS database is
biased towards the UK. Nevertheless, Germany has about 14%, France 10%, Spain 8% and
the Netherlands about 6%. Approximately the same figures apply for citations: together with
the UK these five countries account for more than 60% of the citations from European
countries.
2
This Chapter is based on the bibliometric analysis done for the AgriMapping project. For methodological
details please consult the Annex.
14
Fig. 3
Publications and citations in 1996-2005 (EU33 = 100)
25
20
15
10
5
Share in EU-33 publications (%)
UK
FR
DE
ES
NL
IT
FI
SE
DK
BE
CH
NO
PL
IL
TR
AT
GR
IE
CZ
HU
PT
SK
HR
SI
EE
IS
BG
LT
RO
LV
LU
CY
MT
0
Share in EU-33 citations (%)
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences. For the methods used please consult the Annex.
The European picture is slightly different if the citations per papers figures are computed.
Beside the UK, the Scandinavian countries (Denmark and Sweden, first of all), the Benelux
states and Switzerland manage to produce influential papers across several fields of agrifood
science. Most probably the small countries highly specialise in their agrifood R&D, excelling
on certain areas (for a general picture see the figure below and for detailed charts the Annex).
15
Fig. 4
Citations in 1996-2005 (countries with at least 10 publications, most cited top 5 countries
on the scientific fields A-K)
Legend: A: economic, social and political aspects; B: food technology, human nutrition and consumer concerns;
C: engineering, mechanisation, ICT; D: plant breeding and biotechnology; E: plant production and protection; F:
animal production and husbandry; G: animal health and welfare; H: aquaculture and fisheries; I: forestry and
landscape; J: management of natural and biological resources; K: horizontal issues. For the detailed list of
agrifood research fields please consult the Annex.
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences. For the methods used please consult the Annex.
The EU-12+2 countries together have less than 10% share in Europe’s agrifood publications
in the WoS database. In citations they account for a 3-4% portion only. Among the most
prestigious publications there are much less publications and citations from the New Member
States and the Candidate Countries than from the developed Europe.
16
3.2 The importance of agrifood science in national S&T
The share of agrifood science publications in total publication counts is around 2% in the
world. This means that agrifood science is represented below the share agriculture and food
industry has in GDP3 or R&D. There can be two main many reasons for that. One is that
agrifood research is probably less publication-intensive than other scientific disciplines e.g.
chemistry, engineering or medical sciences. The other is that a substantial portion of the
publication output of national agrifood research / science is not reviewed by Thomson
Scientific for the Web of Science database, because they appear in national language or other
local journals.
Box 4: The most important and relevant scientific literature databases
FAO Agris: The AGRIS database promoted by FAO is a dedicated database for agricultural sciences and technology. It
currently contains over 2.3 million bibliographic references from 1975 to date.
CAB Abstracts: This database is specialised for life sciences (agriculture accounting for a very large portion within it)
covering journals over 150 countries. It contains over 5.2 million records from 1973 onwards. Over 7000 academic journals
are selected and abstracted annually. It has its own thesaurus, which could be compared with the AgriMapping fields of
agrifood science in the future.
Scopus: It is a broad coverage of the scientific, technical, medical and social sciences literature also including patents. Out of
its 15000 peer-reviewed journals about 3400 titles are life sciences. Scopus has a total of about 33 million abstracts.
Web of Science: The WoS database provides access to multidisciplinary information from approximately 8,700 of the most
prestigious, high impact scientific journals in the world.
There are three distinct groups among the EU-33 countries:
 Some smaller European economies produce 3-4% agrifood-related articles as a share
of the total publication output. The figures for Iceland, Ireland, Norway, Estonia,
Finland, Cyprus and Denmark vary between 3 and 4%.
 In Slovakia, Malta, the Czech Republic, Hungary, Luxembourg, Spain, Greece,
Portugal, Sweden, Netherlands, Belgium, Croatia, the UK, and Turkey the share of
agrifood science publications in the total is between 2 and 3%.
 The figure for rest of the EU-33 countries is between 0.7 and 2%, with Romania and
Bulgaria having the lowest shares.
3
Certainly and interestingly, the statement is true for the developed world, whose publications dominate the
Web of Science database, which was used for this report.
17
Fig. 5
Share of agrifood science publications in total scientific publications (%, 1996-2005)
4,5
4
3,5
3
2,5
2
1,5
1
0,5
USA
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences and the National Science Foundation (US). For the
methods used please consult the Annex.
The three groups tell us about the relative position of agrifood science in the total national
scientific production.
18
World
IS
EU33
IE
NO
FI
EE
CY
SK
DK
MT
CZ
HU
ES
LU
PT
GR
SE
NL
BE
HR
UK
LT
TR
AT
PL
CH
LV
DE
IL
FR
IT
SI
BG
RO
0
3.3 Specialisation patterns
Are there any similarities between the countries if we also take into account the broad
agrifood fields of science? Yes and no. Again, a cluster analysis was used, but now for the
weights that each agrifood field of science (from A to K, see the Table below).
Table 3
0,17
0,11
0,04
0,23
0,21
0,34
0,38
0,10
0,20
0,40
0,13
0,15
0,27
0,07
0,25
0,21
0,31
0,27
0,22
0,13
0,41
0,26
0,09
0,14
0,03
0,26
0,11
0,13
0,13
0,09
0,08
0,21
0,10
0,30
0,15
0,08
0,60
0,15
0,60
0,15
0,09
0,32
0,91
0,08
0,15
0,08
0,96
0,56
0,31
0,13
1,10 0,35
0,40 0,48
0,13
0,13
0,13
0,25
0,13
0,13 1,71
0,11
1,53 1,26
0,13
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences and the National Science Foundation (US). For the
methods used please consult the Annex.
With the help of bibliometric data, 10 groups of countries and individual countries could be
distinguished according to the importance of agrifood research and science in national science
and technology (S&T). For the groups the following agrifood fields of science have high
share in national S&T:
 Austria, the Czech Republic, Germany, Lithuania, Poland, Slovakia, Sweden,
Switzerland and the UK: animal production and husbandry, animal health and welfare,
and the management of natural and biological resources.
 Belgium, Croatia, Greece, Netherlands, Portugal, Spain and Turkey: animal
production and husbandry, and the management of natural and biological resources.
 Bulgaria, France, Israel, Italy, Latvia, Romania and Slovenia: none of the broad fields
of agrifood science is particularly strong within national S&T according to the
bibliometric data.
 Denmark and Hungary: plant production and protection, animal production and
husbandry, animal health and welfare, and the management of natural and biological
resources.
 Estonia and Finland: plant breeding and biotechnology, plant production and
protection, forestry and landscape, management of natural and biological resources.
 Iceland and Norway: animal production and husbandry, aquaculture and fisheries,
management of natural and biological resources.
 Cyprus: plant breeding and biotechnology, animal production and husbandry,
management of natural and biological resources.
 Ireland: food technology, human nutrition and consumer concerns, animal production
and husbandry, animal health and welfare, management of natural and biological
resources.
19
Malta
0,45
0,17
0,06
0,20
0,20
0,36
0,41
1,41
0,22
0,69
0,33
Luxembourg
0,22
0,15
0,08
0,78
0,38
0,20
0,26
0,17
0,87
0,69
0,30
Ireland
0,13
0,28
0,09
0,23
0,48
0,34
0,58
0,20
0,12
0,54
0,33
Cyprus
Iceland, Norway
A: economic, social and political aspects
B: food technology, human nutrition and consumer concerns
C: engineering, mechanisation, ICT
D: plant breeding and biotechnology
E: plant production and protection
F: animal production and husbandry
G: animal health and welfare
H: aquaculture and fisheries
I: forestry and landscape
J: management of natural and biological resources
K: horizontal issues
Estonia, Finland
Austria,
Czech Rep.,
Bulgaria,
Belgium,
Germany,
France,
Croatia,
Lithuania,
Israel,
Greece,
Poland,
Italy,
Netherlands,
Slovakia,
Latvia,
Portugal,
Sweden,
Romania,
Spain, Turkey
Switzerland,
Slovenia
UK
Denmark, Hungary
Groups of European countries by agrifood research fields: percentage weight of the
scientific field in all S&T publications 1996-2005
(characteristic average data for the groups are shaded)


Luxembourg: management of natural and biological resources.
Malta: aquaculture and fisheries, management of natural and biological resources.
Although there are clear similarities between the countries, it must be noted that this cluster
analysis is less stable than the previous one (which made use of the general agriculture and
food industry data). The countries that change their groups when a different number of cluster
centres are used are the following: the Netherlands, Germany and Switzerland. Out of the first
group, the Czech Republic, Poland and Slovakia form a different group if the number of
cluster centres is increased.
This means that for a number of small EU countries (such as Denmark and Hungary, Estonia
and Finland, Iceland and Norway, Cyprus, Ireland, Luxembourg and Malta) “high-end”
agrifood science means clearer specialisations with relatively high shares of certain research
fields. For the three large groups specialisation patterns are less evident.
3.4 The growth of agrifood science publications
The bibliometric data for agrifood research shows that the number of EU-33 publications in
the Web of Science database grow at a faster pace than that of the competitor United States.
Nevertheless, the US agrifood researchers are more influential, because in four broad agrifood
fields of science (A: economic, social and political aspects; C: engineering, mechanisation,
ICT; D: plant breeding and biotechnology; I: forestry and landscape) the growth of citations is
higher than the growth of the number of publications. For Europe this is only true for E: plant
production and protection.
Fig. 6
Growth of the number of citations and publications (2002-2004/1996-1998),
percentage points change in the share of the world total)
EU33 countries
USA
20
20
16
16
G
12
J
K
A
Growth of citations
Growth of citations
E
B
H
8
F
C
I
4
A
12
I
8
4
D
D
K B
G
0
4
E J
H
0
0
4
C
8
12
16
0 F
20
4
8
12
16
20
-4
-4
Growth of publications
Growth of publications
Legend: A: economic, social and political aspects; B: food technology, human nutrition and consumer concerns;
C: engineering, mechanisation, ICT; D: plant breeding and biotechnology; E: plant production and protection; F:
animal production and husbandry; G: animal health and welfare; H: aquaculture and fisheries; I: forestry and
landscape; J: management of natural and biological resources; K: horizontal issues. For the detailed list of
agrifood research fields please consult the Annex.
Source: GKI computations using 10 year data from the Web of Science data extractions by the Institute for
Research Policy Studies, Hungarian Academy of Sciences. For the methods used please consult the Annex.
20
Which European countries account for the growth of publications and on which fields? First
of all, the Mediterranean countries (Spain, Portugal, Greece, Turkey), two transition countries
(the Czech Republic, Poland) and Ireland, Switzerland, Belgium, Denmark and Germany.
And publications from which research fields grew faster? We have found that:
 management of natural and biological resources;
 animal health and welfare;
 plant production and protection; and
 horizontal issues
were the most popular for Europe’s agrifood researchers in 1996-2005.
3.5 A gap between institutions
The institutional level of the bibliometric data extractions could be used to show which
European institutions constitute the top-30 within European agrifood research. Although it is
highly unlikely that major institutions were left out from the detailed list in Annex 7.3, we
would stress that these 30 institutions are surely but not necessarily exclusively among the
best performing if measured by the number of prestigious publications.
In the top 30 European institutions we find institutions from the first ten countries in Fig.3.
Although the best performing EU-12+2 institutions in terms of publication output have
around 200 publications, their impact (measured by the citation per paper) is much lower than
in their Western counterparts. The only exception is the Czech Academy of Sciences.
Table 4
The identified EU-12+2 research institutions with the highest number of agrifood
publications in 1996-2005
Institution
Publications*
Citations / publications
Academy of Sciences
CZ
201
9.8
Polish Academy of Sciences
PL
218
5.6
Hungarian Academy of Sciences
HU
198
4.7
Szent István University
HU
220
3.7
Slovak Academy of Sciences
SK
112
2.7
* on a full-count basis: every co-author equally receives one point per publication
Source: 10 year data extraction from the Web of Science database by the Institute for Research Policy Studies,
Hungarian Academy of Sciences.
Generally speaking, the EU-12+2 institutions are much less frequently featured in the
agrifood science publications of the Web of Science database than their Western counterparts.
21
4. Agrifood research capacities surveyed in the EU-12+2 countries
4.1 Institutional setup and financing
Reliable data about business (or private) agrifood research capacities could not be collected in
the EU-12+2 countries of the AgriMapping survey. 4 To some extent this is also true for the
non-profit sector. As we could not reliably clarify the situation in the individual countries, the
analysis below concentrates and draws conclusions on the public domain of agrifood research,
but, when relevant, data from the business sector is also analysed.
The number of public agrifood research units is about 1800 in the EU-12+2 countries and
Poland accounts for about one third. Poland, Turkey, the Czech Republic, Romania, Bulgaria
and Hungary account for 80% of the public agrifood research capacities in the EU-12+2
countries. Research units were defined as individual research groups specialised for agrifood
research.
In general there are more university research units than public (ministerial, Academy of
Science etc.) research institutes, but it does not mean that university agrifood R&D is in
general larger than public research, because approximately the same number of researchers
work in higher education and public research units. Nevertheless, there are great differences
across the countries. Out of the larger countries, the research system in Poland and Bulgaria is
dominated by public research institutes, whereas in Turkey, Hungary or the Czech Republic
university research units are in majority. This finding is in accordance with the National
Innovation Systems (NISs) in the respective countries (see for example the Trenchart country
reports at www.trendchart.org).
Fig. 7
Number of research organisations in the AgriMapping survey by
type
size categories
Source: AgriMapping Survey 2006-2007
4
Data collection for the survey was organised individually in each country, usually by the National Contact
Points for food, who are supervised by the national governments.
22
The vast majority (almost 90%) of the agrifood research capacities are small in size and has
less than 30 employees. The fragmentation of European agrifood research is a fact on the
Eastern skirts of Europe: one fifth of the capacities has less than 5 employees and half of the
research organisations has 6-15 employees.
Two further organisational aspects of agrifood research organisations were surveyed:
 whether the research organisations are complete (their full activity is R&D) or partial
(R&D is just part of the whole activity); and
 whether they are commercial (organisations that operate in a competitive business
environment and primarily for business purposes) or public (organisations that operate
in a government-dominated, non-competitive, non-business environment).
Not surprisingly, 60 percent of the agrifood research units is ‘public and partial’ research
organisation. These are universities, state-financed institutes that conduct routine analysis as
well as research, foundations that perform research as a part of their activities, etc. 30 percent
is ‘public and complete’ research organisation. They are the institutes in Academy of Sciences
networks, foundations that perform research as their core activity etc. (for this taxonomy of
research organisation see Glaser [2000]).
In the sample 6% of the commercial organisations is ‘complete’, these are the R&D
enterprises, while the remaining 4% is ‘partial and complete’, which are in-house R&D
departments in industrial enterprises. Here we underline again that the conclusions for the
business sector are not robust enough, because many of them were not included on the
AgriMapping list of agrifood research organisations in the EU-12+2 countries. In the sample
Cyprus is the only country, where commercial enterprises have dominance in agrifood R&D.
The EU-12+2 countries can spend much smaller amounts on agrifood R&D than the more
developed countries. The reason is twofold:
 these countries have much smaller per capita GDP than the Old Member States of the
European Union (EU-15); and
 government spending dominates agrifood R&D expenditures, which in many countries
is a smaller portion of the R&D expenditures than business R&D.
23
Fig. 8
R&D expenditures by performing sectors (% of GDP, 2005)
3
2,5
2
Higher education
Government
Industry
1,5
1
0,5
0
CY
RO
BG
SK
PL
LV
MT
LT
HU
EE
SI
CZ
EU27
US
Source: Eurostat
The survey data reinforce that government spending is the most important financial source for
agrifood R&D in the New Member States: three-quarter of the research organisations that
participated in the survey receives funding primarily from the government. Knowing that the
sample is biased towards public organisations, this is not a surprise. Nevertheless, there are
some differences in the financing patterns:
 non-competitive government funding is markedly present in Slovakia, Estonia,
Croatia, the Czech Republic and Romania;
 competitive government funding has substantial weight in Latvia, Lithuania, Turkey
and Poland;
 Slovenia, Hungary and Bulgaria have the most diversified funding for agrifood
research.
24
Fig. 9
Number of agrifood research organisations by main financing source
of the annual research budget (2003-2005)
Source: AgriMapping Survey 2006-2007
* competitive government financing: projects won after competitive bidding procedures – so that the
organisation can actually lose the funding targeted at the end of the procedure – count as source on a competitive
basis.
** non-competitive government** financing: If the organisation participates in a money-allocation mechanism
so that the money cannot be lost (but e.g. 'only' reduced), it counts as source on a non-competitive basis of
research funding even if the procedure itself is called 'competitive bidding'.
*** both competitive and non-competitive government financing
other sources: foundations, non-profit organisations, etc.
Source: AgriMapping Survey 2006-2007
Here it should be mentioned that the most developed countries will increasingly turn to
competitive funding for research in many segments of the public domain. For instance, the
funding and governance system of university research is undergoing important changes in
Denmark – in this direction.
25
4.2 Human resources
In the AgriMapping survey we enquired the number of researchers at the agrifood research
organisations. PhD students were included if they were involved in research projects that
would be ongoing even without the PhD student concerned. ’Engineers of the department’
and technical support staff are also included in the figures below. From the response rates to
the survey an estimated figure for the total number of full-time equivalent (FTE) researchers
could be computed.
Altogether the total number of agrifood researchers (FTE) in the EU-12+2 countries5 is
around 30-35 thousand, which is the size of a small city.
Fig. 10
Estimated number of agrifood researchers (FTE) in the public sector 2006-2007*
7000
6000
5000
4000
3000
2000
1000
0
MT
CY
EE
LT
LV
SI
HU
HR
BG
SK
CZ
RO
TR
PL
Number of res earchers , F T E , 2005
Number of res earchers with P hD or higher, F T E , 2005
Number of res earchers under 35, F T E , 2005
Number of women res earchers
* A rough estimate only, based on multiplying the survey data, assuming that the largest capacities have already
been involved in the survey. The final estimates were checked within the AgriMapping consortium
Source: AgriMapping Survey 2006-2007
Most of the agrifood researchers (more than 80%) work in the public sector: at universities,
ministerial etc. research institutes, in the Academy of Sciences. The researchers are highly
skilled: 60% of them has a PhD or higher scientific degree. Young researchers (under 35)
account for 40% of the researchers, the share of women researchers is close to 50%. We did
not measure, but it can be assumed that women are employed in lower positions than men
across the AgriMapping sample of countries (for a global picture on the issue see UNESCO
[2006]).
5
Reliable information from the rest of Europe could not be collected.
26
Box 5: Ageing Europe
Ageing is increasingly becoming one of the most serious economic, social and demographic phenomena of our times. It is
estimated that by 2050 the number of people over 60 in Europe will be doubled to 40% of total population or 60% of the
working age population. Over the next few decades the „baby boomers”, the largest generation, born in the ’50s and the
’60s, will start to retire. The situation will be exacerbated by the very different life expectancy of their parents and
grandparents.
This new scenario brings about many opportunities, but there is also concern for how the system will work. The larger group
of retirees will need healthcare, pensions, housing and community care, and on a greater scale than ever. At the same time
birth rates throughout Europe are falling. This means that fewer young people will drive the economy and pay growing
welfare and social bills. Social and public policies will have to be adjusted to meet these needs either in the form of higher
taxes or by encouraging people to pay more into private pension funds.
Some believe that older people should play an active role in society and be encouraged to work and study beyond
retirement, possibly through part-time work and on a voluntary basis. Legislation preferring younger generations and
neglecting the participation of older people in society has to be changed.
Pension systems start to show the signs of strain. Recent research found that many millions of people do not have an
occupational pension and have to solely rely on the state’s help when they retire. At the same time, employers are closing
generous final salary pension schemes, which have so far lessened state dependency. With regard to the above, European
governments are increasingly compelled to search for long-term solutions based on the agreement of opposing parties.
The share of young agrifood researchers is outstanding in Malta and Cyprus, whereby ageing
of researchers is a problem in Romania, Latvia, Slovakia and Poland, first of all.
Nevertheless, the trends are less worrying, because the majority (60%) of the research units
reported increasing number of young researchers in the last 5 years, and only about 10 percent
mentioned a decreasing number of young personnel during the period. From the trends and
the current state of the age tree it seems that Latvia and Lithuania are in the most problematic
situation. In the other countries, where the age distribution is worrying (Romania, Slovakia
and Poland) the trend is promising.
Fig. 11
Percentage share of
young researchers
women researchers
in 2003-2005
Source: AgriMapping Survey 2006-2007
27
Fig. 12
Evolution of young* research personnel (distribution of agrifood research organisations by
their assessment in 2006-2007)
* under the age of 35
Source: AgriMapping Survey 2006-2007
Fig. 13
Evolution of women researchers (distribution of agrifood research organisations by their
assessment in 2006-2007)
Source: AgriMapping Survey 2006-2007
28
The percentage share of women in the total number of researchers was slightly below 50% in
the EU-12+2 countries. Latvia is characterized by the highest percentage of women
researchers (60%), followed by Romania and Lithuania. Cyprus has the lowest figure (25%).
In Turkey, Hungary, the Czech Republic and Estonia there is also substantial dominance of
men in agrifood research.
The small majority (49%) of the research units reported stagnating number of women
researchers in the last 5 years, while not more than 6% noted decrease (46% reported
increasing).
Fig. 14
Estimated distribution of agrifood researchers (FTE) in the EU-12+2 countries
in 2006-2007 by field of science
Plant production and
protection
Horizontal issues Engineering,
mechanisation, ICT
Aquaculture and
fisheries
Forestry and landscape
Animal health and
welfare
Animal production and
husbandry
Economic, social and
political aspects
Plant breeding and
biotechnology
Management of nat. and
biol. resources
Food tech., human nutr.
and consumer concerns
Remark: All the scientific area of all research units are involved, which has produced at least one article, or
contributed to at least one project report in the period 2003-2005.
Source: AgriMapping Survey 2006-2007
In the EU-12+2 countries the most significant scientific fields concerning human research
capacity on the field of agrifood science are:
 plant production and protection;
 economic, social and political aspects;
 management of natural and biological resources;
 food technology, human nutrition and consumer concerns; and
 plant breeding and biotechnology.
These are the areas with some human resource potential in these countries.
29
4.3 Research infrastructure
The majority of agrifood research organisations in the EU-12+2 countries operate in
unfavourable infrastructural conditions. The average value concerning the development on
research infrastructure on a 5 graded scale is 2.1. It means that in most of the countries
research organisations have a rather obsolete research infrastructure, which is an obstacle to
international research co-operation. Nevertheless, it should be noted that this value concerns
only 963 out of the 1154 organisations, because 191 research units reported that they have
access to good quality infrastructure, but lack an own research infrastructure.
Fig. 15
Average quality* of the existing agrifood research infrastructure 2006-2007
*The following scale was used:
5 - The research organisation has an internationally competitive technology and it is able to conduct top research
in cutting-edge research topics;
4 -The research organisation has top research infrastructure, the infrastructure enables regular international
research co-operation but it is not competitive if compared with the 'best in our research field'
3 - The research organisation has good quality research infrastructure, probably one of the most up-to-date in the
country, but it is not good enough to join in international research on a regular basis
2 - The research organisation has an obsolete research infrastructure if compared with international organisations
and it is an obstacle to international research co-operation
1 - The research organisation has a rather obsolete research infrastructure and it is an obstacle to more domestic
contracts
Source: AgriMapping Survey 2006-2007
Only 24% of the research units reported at least good quality research infrastructure. 10% has
top research infrastructure, which enables regular international research co-operation. 3% has
quality infrastructure, which enables international cooperation, but it is not competitive if
compared with the “best in the given research field”.
30
On average the highest share of agrifood research institutions that have competitive good
quality infrastructure (at least 4 on the above scale) was reported from Romania, Turkey and
Cyprus, but this concerns only about one-fifth of the research organisations. Bulgaria,
Slovakia and Slovenia have the lowest share of institutions with competitive research
infrastructure in agrifood research.
Fig. 16
The agrifood research infrastructure 2006-2007
Source: AgriMapping Survey 2006-2007
35% of the surveyed research organisations reported obsolete infrastructure that is an obstacle
to perform research services for the domestic market. Additionally, 25% cannot join in
international works due to the poor quality of the research infrastructure.
Box 6: ESFRI and SCAR studies on infrastructure
The European Strategy Forum on Research Infrastructures (ESFRI) published a roadmap for research infrastructures in
Europe for the next 10 to 20 years, aimed at providing an overview of the needs for research infrastructures of pan-European
interest in all fields of science and technology. This European roadmap was the first exercise at European level and was the
result of wide stakeholder consultation: almost 1000 experts from all fields of research were involved and consulted in the
process of preparing the roadmap, of which 200 were involved in the peer-review. ESFRI’s roadmap is meant to be reviewed
every two or three years; a 2nd roadmap is expected in October 2008.
The Standing Committee for Agricultural Research (SCAR) decided to launch strategic discussions aimed at identifying key
agricultural research infrastructures of EU relevance, possible means of sharing existing infrastructures among Member
State research teams, and targeted proposals for the future activities of SCAR in this field. Shared infrastructures for agrifood
research are believed to improve efficiency, to better allow for studying agrifood phenomena of global relevance. Launching
an infrastructure study to systematically overview the future needs and governance schemes of shared European agrifood
research infrastructures seems a rational exercise by SCAR, because it can give a European scale to an important, yet still
fragmented segment of the European Research Area.
Source: an overview by Valceschini and Berthet to the SCAR (18 January, 2008)
31
Although the large-scale, web-assisted survey did not allow us to precisely identify where (on
which agrifood research fields) good quality research infrastructure exists in the EU-12+2
countries, some conclusions could be drawn. There are few, internationally acceptable pieces
of research infrastructure on the following fields:
 food technology (in Croatia, Hungary, Lithuania, Romania and Slovenia);
 plant breeding and biotechnology (Estonia, Poland and Romania);
 plant production and protection (Lithuania and Romania);
 animal health and welfare (Estonia and Turkey).
We stress again that the above list does not mean that the countries are strong players in those
fields of agrifood research. It is just an indication that from an infrastructural point of view
some capacity is available there.
4.4 Innovative and scientific output
Due to the basic sample properties, it is not a surprise that in the EU-12+2 countries almost all
(98%) of the agrifood research units published articles in 2003-2005, although these countries
are not very influential on a global scale (see also Chapter 3). One third (34%) could report
that the research organisation commercialised new products and technologies, and only one
fifth (22%) filed patent applications.
Fig. 17
Innovative and scientific activity of agrifood research organisations in 2003-2005 (%)
100
80
60
98%
40
20
34%
22%
0
publis hed artic les
filed patent applic ations
c ommerc ialis ed new produc ts
or tec hnolog ies
Source: AgriMapping Survey 2006-2007
The figures above confirm what is called the ‘European paradox’. Although the term was
formulated already at the end of the 1980’s, it became well known following the CressonBangemann [1995] report. The paradox originally said that compared with its principal
competitors the scientific performance of the EU is excellent, however, commercial
32
performance has deteriorated. “One of Europe’s major weaknesses lies in its inferiority in
terms of transforming the results of technological research and skills into innovations and
competitive advantages” (Cresson-Bangemann [1995] p.5). We must note that in the EU12+2 countries the European paradox is a greater problem than in the developed EU
countries.6 Therefore, there are some scientific achievements (shown by the publication
intensity and the bibliometric analysis results), but the links with agrifood innovations are
moderate (shown by patenting intensity and the commercialisation efforts).
Fig. 18
Share of agrifood research organisations engaged in commercialisation and patenting
activity in 2003-2005 (%)
Source: AgriMapping Survey 2006-2007
Certainly, there are country-specific differences in terms of the propensity to patent and
commercialise knowledge. Filing patent applications was the most intensive in Romania (44%
of the agrifood research units filed patent in 2003-2005). Latvia (39%) and Poland (26%).
From Malta no patenting was reported and the figure is very small for Turkey and Lithuania
as well (6 and 7%). Half of the research units commercialised new products or technologies in
Cyprus and Slovakia, while only 12%in Turkey and 16% in Croatia.
Although these figures tell us something, there is still a lot of noise in the data, which makes
direct comparisons difficult. For instance the intellectual property rights (IPR) regimes
substantially differ across countries and the large share of agrifood that filed patents in 20032005 in Romania or Latvia may not show high innovation or business value. The same is true
for the other metric used: commercialisation may only have a negligible innovation impact.
6
There are worrying signs about European scientific excellence as well. Dosi et al. [2005] argue that by now the
paradox is not true for a some key technologies (biotech, ICT, new materials, etc.), where EU R&D has been
losing ground.
33
To measure the real relative innovation and scientific performance, the AgriMapping survey
also measured the following indicators as per 100 researchers:
 Important innovation: a new product / technology / organisational mode / tool or
method had or contributed to an additional turnover of more than EUR 100 thousand
or more than 500 people use a new product/technology or it saved life or improved the
quality of life substantially. The research organisation's contribution is substantial if at
least one third of the new knowledge came from the research organisation.
 Domestic patents: granted by the national patent offices (to measure it separately from
triadic patents).
 Triadic patents: patents granted by the EPO (European Patent Office) and/or JPO
(Japan Patent Office) and/or the USPTO (United States Patent and Trademark Office).
The highest innovative performance could be measured for Malta: international and domestic
patents as well as important innovations per 100 researchers are high. Latvian researchers also
do well in terms of important innovation, however, their international patent figure is more
medium-range in the sample of EU-12+2 agrifood research organisations (and, as noted
earlier, the value of domestic patents remains questionable in comparison with the triadic
ones). According to the responses Slovak, Turkish and Romanian agrifood research suffers
most from the European paradox.
Fig. 19
S&T indicators per 100 agrifood researchers 2003-2005
* Important innovation carried out: a new product / technology / organisational mode / tool or method had or
contributed to an additional turnover of more than EUR 100 thousand or more than 500 people use a new
product/technology or it saved life or improved the quality of life substantially. The research organisation's
contribution should have been substantial: at least one third of the new knowledge came from the research
organisation.
** Patents granted by the EPO (European Patent Office) and/or the JPO (Japan Patent Office) and or the USPTO
(United States Patent and Trademark Office).
Source: AgriMapping Survey 2006-2007
34
Fig. 20
Triadic patents and important innovations per 100 agrifood researchers 2003-2005
* Important innovation: a new product / technology / organisational mode / tool or method had or contributed to
an additional turnover of more than EUR 100 thousand or more than 500 people use a new product/technology
or it saved life or improved the quality of life substantially. The research organisation's contribution should have
been substantial: at least one third of the new knowledge came from the research organisation.
** Patents filed with the EPO (European Patent Office) and/or the JPO (Japan Patent Office) and or the USPTO
(United States Patent and Trademark Office).
Source: AgriMapping Survey 2006-2007
With respect to the researcher intensity of important innovations, international patents and
agrifood research fields, the following country-specific information could be seen from the
survey:
 There are cases when international patent production (measured by the triadic patents)
and innovativeness (measured by the contribution to important innovations) go hand
in hand. The food technology, human nutrition and consumer concerns in Bulgaria,
Estonia and Poland, engineering, mechanisation and ICT (Poland), plant breeding and
biotechnology (Bulgaria, Estonia, Latvia, Poland), plant production and protection
(Estonia, Hungary and Poland), animal production and husbandry (Bulgaria, Estonia
and Hungary) and aquaculture and fisheries (Malta) fields of agrifood research can be
mentioned.
 There are countries, whose researchers contribute to important innovations on given
research fields more actively than in the whole sample, but the lack of international
patenting indicates either some gap of international competitiveness, or the very much
domestic nature of the innovations. This is the case for Bulgaria (engineering,
mechanisation, ICT) Cyprus (food technology, plant breeding and biotechnology,
plant production), Estonia (forestry), Hungary (food technology, engineering,
mechanisation, ICT, plant breeding and biotechnology, animal production and
husbandry, animal health and welfare), Malta (plant breeding and biotechnology),
35
Poland (forestry), Turkey (animal production, aquaculture) and for almost all fields in
Romania and Slovenia.
This shows that the international and domestic innovativeness and competitiveness of
agrifood research is not at all easy to measure per se, because the local context and
embeddedness is very important in some cases and distinguishing these is often not possible
with the use of relatively simple surveys. Also, we shall not forget that the analysis concerns a
few sectors only, where the European paradox is not so harshly present.
4.5 Research competence
Research competence for the EU-12+2 countries that participated in the AgriMapping survey
was shown by two rather different measures:
 the ability to take part in and conduct large research projects, in which the total
project budget is above EUR 100 thousand and the research organisation’s share is at
least EUR 20 thousand;
 the ability to attract foreign researchers for doing real research work, which is defined
with the help of the hosting period (hosting a foreign researcher for more than 6
weeks).
The number of large research projects completed per 100 researchers was around 15% in
2005 in the EU-12+2 countries. This is a low figure indicating the fragmented nature of
agrifood research (and, to some extent, less competence because the research organisations
are not able to offer research service for the industry in these scales – the threshold for large
project was only a 100.000 euro budget!). Out of the large projects two-third was realized in
collaboration with industry (showing that there can be demand) and 80% was co-ordinated by
the surveyed research organizations. Two-third of the large projects are EU projects.
In terms of the number of large research projects per researchers, the agrifood research units
of Cyprus and Malta proved to be the most effective in 2005. Out of the so-called transition
countries Slovenia, Poland and Estonia can be mentioned. Countries with the fewest number
of large projects per researcher were Slovakia and Turkey.
Although large projects are few in number, a substantial portion of them takes place in
collaboration with industry and within the framework of EU projects. Even more of these
large projects are coordinated by the research organisation in question. If competence is
measured by the ability to take up large research projects, the European Union clearly has
great influence on the agrifood research in the EU-12+2 countries as it provides impetus for
being part of large collaborative projects.
36
Fig. 21
Large projects* completed in 2005
* the total project budget is above EUR 100 thousand and the research organisation’s share is at least EUR 20
thousand
Source: AgriMapping Survey 2006-2007
With the exception of Malta, in the EU-12+2 countries the percentage of agrifood researchers
sent abroad to do research is higher than that of hosted researchers. The international mobility
of agrifood researchers is also significantly higher in Malta than in the other EU-12+2
countries.
Additionally, the relative mobility rates show that the Czech Republic, Cyprus, Slovenia, and
to some extent Poland, Estonia, Hungary, Bulgaria, Croatia and Lithuania host more agrifood
researchers within the New Member States and the candidate countries. Although we do not
know the sender countries, this shows some agrifood research competence of international
relevance. Slovakia, Romania, Latvia and Turkey have much lower mobility rates showing
that these countries are much less part of the international bloodstream of agrifood research.
37
Fig. 22
International mobility* of researchers in 2003-2005
* foreign researchers hosted for more than 1.5 months (without those, who came to acquire a Ph.D. degree) and
own researchers sent abroad to do research for more than 1.5 months
Source: AgriMapping Survey 2006-2007
Fig. 23
International mobility of researchers in 2003-2005
* foreign researchers hosted for more than 1.5 months (without those, who came to acquire a Ph.D. degree) and
own researchers sent abroad to do research for more than 1.5 months
Source: AgriMapping Survey 2006-2007
38
Box 7: Researcher mobility
Mobility of researchers is increasingly becoming a prioritised focus of European science, technology and innovation policies.
Increased mobility is seen a vital instrument to achieve an improved integration of research systems. Additionally, increased
inter-sectoral mobility is seen as an important instrument for transferring scientific expertise to companies in order to improve
their research capabilities. Enhanced mobility - especially the one from business to research institutes - will lead to an
increased awareness of business needs and opportunities.
Countries with high innovation performance compete intensively to attract top scientists and researchers. Data also indicate
that high demand for qualified labour has recently led to increased migration. Developing and transition countries are in a
weak position when competing for foreign researchers and scientists. The outflow of researchers and scientists could
potentially erode the science base of low-income countries.
Because of a strong increase in the demand for skilled relative to unskilled labour the countries concerned tend to develop
policies of return migration. A reasonable salary level has to be preferably guaranteed but the return decisions of researchers
and scientists are, however, primarily shaped by factors such as the quality of the research environment, professional reward
structures and access to state-of-the-art equipments. Several analyses point the important role of innovation systems in
influencing the inflows and outflows of highly skilled people.
Although agrifood researcher mobility data from the developed EU countries was not
collected, we assume that mobility rates there are more balanced. It should also be noted that
the mobility rates surveyed are not low.
4.6 Excellence
According to the bibliometric data analysed, there is a relatively large gap between the best
performing developed European countries and the New Member States. Nevertheless,
scientific excellence should not be treated in the same way as innovation and research
excellence as the European paradox also shows. For the EU-12+2 countries the survey results
can show:
 if there are strengths beyond the publications, because we have asked also about
innovations, patents etc.; and
 if there are country specific strengths compared with the averages measured in this
specific group of countries.
According to the survey results, there are measurable strengths in Bulgaria (food technology,
human nutrition and consumer concerns, plant breeding and biotechnology, animal production
and husbandry), Estonia (forestry and landscape, management of natural and biological
resources), Malta (aquaculture), Slovenia (forestry and landscape, management of natural and
biological resources) and Slovakia (forestry and landscape). Please note that these strengths
are measured within the EU-12+2 countries.
The bibliometric data underpin the strengths of Slovakia in forestry and landscape and
Hungary in plant production and protection. In case of the other countries, which have
measurable strength according to the survey results, the bibliometric data are less in
accordance with the survey results.
39
Table 5
Strengths and weaknesses in the EU-12+2 countries (measured against the distribution of
the absolute number of innovations, patents, large projects, articles, studies, standards
across the sample, in 2003-2005)
Legend: Green: the given fields of agrifood research have a higher weight in the country than in the whole
sample. Red: the given fields of agrifood research have a lower weight in the country than in the whole sample.
Source: AgriMapping Survey 2006-2007
Table 6
Strengths and weaknesses in the EU-12+2 countries (measured against the distribution of
the relative (per researcher) number of innovations, patents, large projects, articles, studies,
standards across the sample, in 2003-2005)
Legend: Green: the given fields of agrifood research have a higher per researcher figure in the country than in
the whole sample. Red: the given fields of agrifood research have a lower per researcher figure in the country
than in the whole sample.
Source: AgriMapping Survey 2006-2007
There were two approaches used for looking at excellent performance at the institutional level
from the survey results:
 First, we said that in 2003-2003 excellent (internationally competitive) agrifood
research organisations published articles, filed patent applications, took part in the
commercialisation of new products / technologies and hosted more than 1 foreign
researcher for more than 6 weeks.
40

Second, we considered a research organisation excellent if research is funded
primarily from corporate or international sources.
One can say that these criteria are arbitrary. This is true to some extent. However, it can
hardly be questioned that if an agrifood research organisation wants to be competitive on an
international scale, it should be able to publish articles, apply for patents and enforce its
commercial interest as well. At the same time being part of the international bloodstream of
research is also important (see also the Record Manual [2004]).
Since representation of public and university agrifood research organisations is acceptable,
the analysis of excellence was carried out only for public and university research
organisations only.
Fig. 24
Number of ‘excellent’ public agrifood research organisations in the EU-12+2 countries
(2003-2005) (the number of articles, patents, foreign researchers hosted in these
organisations is >1)
25
1
20
11
15
T ype 1+2
T ype 2
1
10
1
1
2
T ype 1
7
6
11
5
8
0
1
1
1
1
EE
MT
SI
2
2
1
1
HR
SK
1
2
TR
3
6
6
3
1
LT
CZ
BG
RO
HU
PL
Legend: Type 1: the number of articles, patents, foreign researchers hosted in these organisations is >1; Type 2:
the majority of funding is corporate or international
Source: AgriMapping Survey 2006-2007
In the first approach (Type 1 of excellence) a total of 40 such organisations were found. Half
of them are universities. The vast majority has 5-100 researchers. Government money
dominates research funding. In the second approach (Type 2 of excellence) a total of 38
organisations were found. They are smaller in size than the group of the Type 1 of excellence.
Last, but not least we should underline that we found only 3 agrifood research organisations,
which meet both criteria of excellence.
41
5. Conclusions
The AgriMapping exercise was an exciting path-breaking experiment for many reasons:
 it aimed at clarifying where Europe stands on a field (agrifood research) that was
previously not surveyed from a global standpoint;
 it could deliver a classification system of agrifood science and research fields, which
proved to be a useful input for both the bibliometric analysis and the survey, on which
the empirical data collection part of the project relied;
 it brought together experts and policy practitioners to regularly discuss agrifood
research from half of Europe;
 it validated that the use of web assisted survey and bibliometric analysis fit well the
exploration of the activities and the capacities of research.
In the National Innovation System approach, the agriculture and food industry context is
important to understand national agrifood research. When agricultural endowments and
agrifood industrial performance is analysed, there are similarities between groups of countries
in Europe. The Mediterranean countries, for instance, have similar characteristics as well and
it is not at all sure if there is agrifood research cooperation between these countries. The other
example is Scandinavia, where probably there are more research collaborations in the
agrifood arena. Certain types of agrifood cooperation might be encouraged by policy in these
groups, starting by more in-depth sectoral analysis.
According to the bibliometric indicators, agrifood research output is not bad in Europe.
However, it is fragmented and less influential than US agrifood science, although some
catching up could be measured in the number of publications. There is also a gap between
both the EU-15 (“Old Member States”) and US and the EU-15 and the EU-12+2 (New
Member States plus Croatia and Turkey) countries. A study of other indicators than those
used in this exercise (number of publications and number of citations) could help to validate
the solidity of this finding.
The empirical survey carried out in the EU-12+2 has much relevance due to the lag these
countries suffer from in agrifood research.
Across these economies agrifood research is dominated by state-owned institutions and is
relatively under-funded. The research infrastructure is in bad shape, it often does not allow the
researchers to join in international work. The share of large projects is low, showing the
fragmentation of research not only in Europe in general, but also within the surveyed
countries. The European Paradox is prevalent: there are scientific results but contacts with
industry are low. With a few exceptions (Malta and Cyprus) business orientation seems very
limited (which contrasts global trends). We should also note that business agrifood research
was not sufficiently covered and thus remained relatively hidden and unknown. To help the
clarification of the situation – as a first step – agrifood research conferences with the
involvement of business research should be encouraged to see who the larger players are.
In the EU-12+2 countries the FTE number of agrifood researchers is estimated at 30-35
thousand (size of a small town). These countries have skilled agrifood researchers and ageing
is not as serious as expected. We hypothesise that with its Barcelona-Lisbon strategy the EU
is perceived to offer perspectives also for agrifood researchers in these countries.
42
In the EU-12+2 countries the most significant scientific fields measured by human research
capacities on the field of agrifood science are:
 plant production and protection;
 economic, social and political aspects;
 management of natural and biological resources;
 food technology, human nutrition and consumer concerns; and
 plant breeding and biotechnology.
The European paradox is a problem area in most of the EU-12+2 countries: patenting is not
frequent, there is a stronger focus on publications. International patenting activity compared
with important innovations shows that local agrifood competitiveness is more frequently
supported by agrifood research organisations and international competitiveness is more
questionable. Further, the low figures on large projects indicate that there is also a problem
with the “supporting industry” behind agrifood research, because large projects are largely
generated by EU funding. Despite this rather dark picture, mobility rates of researchers was
measured to be relatively high. It is probably a characteristic of agrifood research (because,
for instance, to deliver valuable research results in this particular field requires more on-thespot research by fellow researchers in international collaborations) and again indicates that
there is some knowledge flow across Europe in this respect. Certainly, we say this without
knowing the sender countries, the analysis of which could clarify the situation (e.g. there are
probably intensive “traditional” staff exchanges between the Czech Republic and Slovakia, or
Malta and Italy).
In AgriMapping a combined way of looking at excellence was used because excellence is a
multi-faceted and dynamic phenomenon. Similar approaches are encouraged in similar future
exercises (in this respect the bibliometric analysis could provides only one, although
important portion of the information that helps analysis). Within the EU-12+2 countries some
country-specific strengths could be shown in Bulgaria (food technology, human nutrition and
consumer concerns, plant breeding and biotechnology, animal production and husbandry),
Estonia (forestry and landscape, management of natural and biological resources), Malta
(aquaculture), Slovenia (forestry and landscape, management of natural and biological
resources) and Slovakia (forestry and landscape). The bibliometric data also support the
strengths of Slovakia in forestry and landscape and Hungary in plant production and
protection.
Measured against multiple criteria, less than one-tenth of the public agrifood research
organisations surveyed proved to be ‘excellent’. Given this situation, raising awareness to
(business) R&D and innovation among researchers in the public domain seems particularly
important.
Last, but not least we underline that local contexts are very important as much of the agrifood
research is less exposed to globalisation than other fields, so the results of this mapping report
should be treated with care. Nevertheless, both the bibliometric analysis and the survey results
from the EU-12+2 could show important characteristics of European agrifood R&D.
43
References
Cresson, E. – Bangemann, M. (1995): Green Paper on Innovation. EC. Brussels. 1995.
Dosi, G. – Llerena, P. - Labiba, M.S. (2005): Science-Technology-Industry Links and the „European Paradox:
Some Notes on the Dynamics of Scientific and Technological Research in Europe. LEM Working Paper. 2005.
EC (2007): Foresighting food, rural and agri-futures. Reportof high level independent expert group appointed by
the European Commission. European Commission, Brussels, February 2007. (distributed on the SCAR
Conference “Towards future challenges of agricultural research in Europe”, Brussels, 26-27 June 2007)
Glaser, J. (2000): Content and organisational forms of innovations – Some comments on the Case Studies. In:
Werner Meske and Dang Duy (eds.): Vietnam’s Research and Development System in the 1990s – Structural
and Functional Change. Discussion paper P00-401. Berlin: Wissenschaftszentrum Berlin, 183-202
OECD (2002): Frascati Manual. Proposed standard practices for surveys on research and development. OECD,
Paris
OECD (2005): Oslo Manual. Guidelines for collecting and interpreting innovation data. 3rd edition, OECD, Paris
Record Manual (2004): Benchmarking Innovative Research Organisations in European Accession Countries.
Edited by Borsi, B, Dévai, K., Papanek, G., Rush, H. European Commission, Budapest University of
Technology and Economics
UNESCO (2006): Women in science: under-represented and under-measured. UIS Bulletin on Science and
Technology Statistics, Issue No. 3. November 2006
44
Annexes
7.1 Agrifood fields of science
A
Economic, social and political aspects
A1 Production and producer issues
A2 Rural development
A3 Micro economics
A4 Horizontal expertise
A5 Market issues
A6 Policy issues
A7 Agricultural public finance
A1.1
A1.2
A1.3
A2.1
A2.2
A2.3
A2.4
A3.1
A3.2
A3.3
A3.4
A3.5
A3.6
A4.1
A4.2
A4.3
A4.4
A4.5
A4.6
A5.1
A5.2
A5.3
A5.4
A5.5
A5.6
A5.7
A6.1
A6.2
A6.3
A6.4
A6.5
A6.6
A7.1
Land
Production structure
Producer income
Rural development
Rural socio-economics
Rural labour market
Poverty
Market development
Financial issues
Agricultural production
Organisation and management
Environmental management
Organic production
Econometric modelling
Statistical and econometric analysis
Computer programs
Agricultural census and survey system
Policy evaluation
Foresight and prospective study
Food chain analysis
Organic markets
Agricultural supply and demand
Price
Distribution and consumer
Competitiveness
Trade
Agricultural and food market policy
Trade policy
Quality policy
Environmental policy
Food and nutrition policy
Rural development policy
Agricultural public finance
B Food technology, human nutrition and consumer concerns
B1 Human nutrition
B1.1
Functional food
B1.2
Conventional food
B1.3
Nutrigenomics
B1.4
Food and diet related diseases
B1.5
Food pattern and health
B1.6
Consumer habits
B2 Postharvest and food technology
B2.1
Food chain management
B2.2
Transportation
B2.3
Storage
B2.4
Cooling
B2.5
Processing
B2.6
Conservation
B2.7
Packaging
B3 Consumer concerns
B3.1
Risk assessment
B3.2
Food quality and quality control
B3.3
Traceability
B3.4
Residues and contaminants
B3.5
Trust
B3.6
Coexistence
45
C
Engineering, mechanisation, ICT
C1 Engineering & mechanisation
C2 ICT
D
Plant breeding and biotechnology
D1 Plant genetics
D2 Plant molecular biology
D3 Plant breeding
D4 Plant biotechnology and non food use
E
Plant production and protection
E1 Plant physiology
E2 Plant nutrition
E3 Plant health
E4 Plant production systems
C1.1
C1.2
C1.3
C1.4
C1.5
C1.6
C1.7
C2.1
C2.2
C2.3
C2.4
Traction
Animal traction
Building and housing
Machinery, equipment, tools
GPS (Global Positioning system)
Robotics
Precision agriculture
Tracking and tracing
Identification and registration
GIS (Geographical Information System)
DSS (Decision Support System)
D1.1
D1.2
D1.3
D2.1
D2.2
D2.3
D2.4
D3.1
D3.2
D3.3
D4.1
D4.2
D4.3
D4.4
D4.5
D4.6
D4.7
D4.8
D4.9
Genetic resources
Plant genomics
Gene regulation
Molecular evolution
Molecular ecology
Bioenergetics
Photosynthesis
Conventional breeding
Resistance (stress, pathogens, etc) breeding
GMO
Plant (cell) based vaccines
Plant (cell) based fine chemicals
Biomass –energy
Bioplastics
Fibers
Cosmetics, medicals, colorants etc
Construction materials
Paper
Fuels
E1.1
E1.2
E1.3
E1.4
E2.1
E2.2
E2.3
E2.4
E2.5
E3.1
E3.2
E3.3
E3.4
E3.5
E4.1
E4.2
E4.3
E4.4
E4.5
E4.6
E4.7
E4.8
Plant development
Hormone action and regulation
Physical stress (water, drought, temperature etc)
Plant-plant interaction
Nutrient assimilation
Nutrient deficiency
Toxicity (toxicological evaluation)
Fertilisation
Mineral balance
Pest research
Plant protection
Weed management
Pathogen control
Biological control
Intensive cropping
Extensive cropping
Organic farming
Grassland and pastures
Peri-urban agriculture
Open air horticulture
Protected horticulture
Urban horticulture
46
F
Animal production and husbandry
F1 Animal genetics and breeding
F2 Animal husbandry
F3 Production systems
F4 Nutrition and feed
F5 Non food use of animal products
G
Animal health and welfare
G1 Animal physiology
G2 Animal behaviour
G3 Animal health
G4 Animal welfare
G5 Environmental
H
Aquaculture and fisheries
H1 Aquaculture
H2 Fisheries
I
Forestry and landscape
I1 Forestry
F1.1
F1.2
F1.3
F1.4
F2.1
F2.2
F3.1
F3.2
F3.3
F3.4
F4.1
F4.2
F5.1
F5.2
F5.3
Animal genetics
Animal genetic resources
Selection technologies
Reproduction and embryology
Mating technologies
Embryo-technologies
Intensive
Extensive
Pastures
Organic farming
Animal nutrition
Feed and feed technology
Cosmetics
Wool – Leather
Medicals
G1.1
G1.2
G1.3
G1.4
G1.5
G1.6
G2.1
G2.2
G3.1
G3.2
G3.3
G3.4
G4.1
G5.1
G5.2
G5.3
Growth and development
Lactation
Endocrinology
Immunology
Neurobiology
Other physiologies
Ethology
Housing systems
Disease control strategies
Disease detection
Vaccine development
Antibiotics resistance
Animal welfare
Manure management
Ecosystems
Pasture management
H1.1
H1.2
H1.3
H1.4
H1.5
H1.6
H2.1
H2.2
H2.3
H2.4
Aquatic animal nutrition
Aquatic animal genetics and breeding
Water quality
Aquatic animal health and pathology
Aquaculture production systems
Non-food use of aquatic resources
Fishery management
Fishery ecology
Marine ecosystems
Fish capture systems
I1.1
I1.2
I1.3
I1.4
I1.5
I1.6
I1.7
I1.8
Sustainable management
Fires and hazards
Diseases and pest control
Forest ecology
Genetic resources
Breeding and propagation
Agro forestry
Forest farming
47
I2
J
K
Forest products
I2.1
I2.2
I2.3
I2.4
I2.5
I2.6
I2.7
Management of natural and biological resources
J1 Soil
J1.1
J1.2
J1.3
J1.4
J1.5
J2 Water
J2.1
J2.2
J2.3
J2.4
J2.5
J2.6
J3 Biological resources
J3.1
J3.2
J3.3
J3.4
J3.5
J4 Environment
J4.1
J4.2
J4.3
J4.4
J4.5
J5 Climatology and climate change
J5.1
J5.2
J5.3
Horizontal issues
K1 Statistics applied to agriculture research
K2 Food Chemistry
48
Pulp
Energy
Timber
Ecology
Land surveying
Environmental design
Countryside management
Conservation
Rehabilitation
Erosion
Soil (micro)biology
Fertility
Water management
Irrigation
Drainage
Water and sanitation
Water conservation
Hydrology
Alternative resources
Ecosystems
Biodiversity
Natural resources management
Nature conservation
Landscape
Ecotoxicology
Desertification
Environmental health
Waste management
Climate change and agriculture
Climate change models and forecast
Climate change monitoring
7.2 The bibliometric methods
The bibliometric methods were used to assess the worldwide research activity in agricultural
and food science and technology as it is reflected by the mainstream journal literature.
Besides merely counting the publications, an attempt is also made to gauge their scientific
influence using the standard techniques of citation analysis.
Data sources
Publication and citation data can be taken from Thomson Scientific’s Web of Science (WoS)
database. Although WoS is not specialized to the agri-food field, its multidisciplinary and
international character helps to put the results of the analysis into the widest possible frame of
comparison. A particular advantage of WoS is that it includes the institutional address of all
authors of the papers (not only that of the first or contact author), thus it helps to assign
correctly co-authored papers to all contributing countries/institutions.
Subfield categorization
The classification system elaborated in the AgriMapping project categorizes the agri-food
field into 11 level-1, 41 level-2 and 186 level-3 subfields. Preliminary data extractions from
the WoS database suggested that level-2 is the deepest level where meaningful bibliometric
analysis can be performed. The 41 level-2 fields (denoted in the classification by A1 to K2)
were, therefore, chosen as subfield levels of analysis.
Country/institution assignment
Publications are assigned to countries/institutions according to the country/organization field
of their record in the WoS database. This, in turn, is based on the institutional address given in
the by-line of the publication. Publications were counted on a fractional count basis, i.e. for
articles with collaborating institutions from multiple countries/economies, each
country/economy receives fractional credit on basis of proportion of its participating
institutions. The fractional count basis enables the aggregability of the indicators for various
country groups/clusters. It means that if a paper was authored by scientists from k countries,
then each contributing country was credited by 1/k publication (instead of 1 publication in
case of full counts). Similarly, if a papers with authors from k countries received z citations,
each contributing countries were credited by z/k citations (instead of z). The publication and
citation numbers calculated this way can be directly summed over any number of countries to
form correct subset indicators.
Data retrieval strategies
For each of the 41 level-2 fields, a specific “search profile” is designed with the aim of
retrieving as many relevant publications of the field as possible without allowing excessive
“noise”, i. e., vaguely relevant or irrelevant items. It must be understood that the primary aim
of the retrieved publication list is to serve as a representative sample of its field (both as its
size and its composition is considered), and by no means should it satisfy the criteria, e.g., of
a specialized bibliography.
Data retrieval is based on “key terms”, which – depending on the actual topic – may be key
journals, key elements of institutional names, key authors, keywords in the title, abstract or
keyword list of the paper, etc. Key terms are used in proper logical combinations to achieve
the desired filtering effect.
49
Usually, first a broader profile is constructed for the level-1 field, which is then narrowed
using more specific terms at level-2 (often taken from the specifics of the constituent level-3
fields).
An example
Let us take as an example the field B2: “Postharvest and food technology”. It belongs to the
level-1 field B: “Food technology, human nutrition and consumer concerns”. This field can be
delimited by a set of journals ranging from
ACTA-ALIMENTARIA
AGRICULTURAL-AND-FOOD-SCIENCE-IN-FINLAND
AGRO-FOOD-INDUSTRY-HI-TECH
ALIMENTA
ALIMENTARY-PHARMACOLOGY-&-THERAPEUTICS
AMERICAN-JOURNAL-OF-CLINICAL-NUTRITION
AMERICAN-JOURNAL-OF-ENOLOGY-AND-VITICULTURE
AMERICAN-JOURNAL-OF-POTATO-RESEARCH
AMERICAN-POTATO-JOURNAL
ANNALS-OF-NUTRITION-AND-METABOLISM
ANNUAL-REVIEW-OF-NUTRITION
AQUACULTURE-NUTRITION
ARCHIV-FUR-LEBENSMITTELHYGIENE
ARCHIV-FUR-TIERERNAHRUNG-ARCHIVES-OF-ANIMAL-NUTRITION
...
to
POSTHARVEST-BIOLOGY-AND-TECHNOLOGY
POTATO-RESEARCH
PROCEEDINGS-OF-THE-NUTRITION-SOCIETY
PROGRESS-IN-FOOD-AND-NUTRITION-SCIENCE
REPRODUCTION-NUTRITION-DEVELOPMENT
REVISTA-DE-AGROQUIMICA-Y-TECNOLOGIA-DE-ALIMENTOS
REVISTA-ESPANOLA-DE-CIENCIA-Y-TECNOLOGIA-DE-ALIMENTOS
SCIENCES-DES-ALIMENTS
SEIBUTSU-KOGAKU-KAISHI-JOURNAL-OF-THE-SOCIETY-FOR-FERMENTATION-ANDBIOENGINEERING
TRENDS-IN-FOOD-SCIENCE-&-TECHNOLOGY
ZEITSCHRIFT-FUR-LEBENSMITTEL-UNTERSUCHUNG-UND-FORSCHUNG
ZUCKERINDUSTRIE;
a set of institutional name elements, like
FOOD, CROP, ALIMENT*, NUTR*, LEBENSMITT*,
a set of keywords
ALIMENT*; APICULT*; AQUACULT*; BEEF; BEER*; BEVERAGE*; ...; SEAFOOD; SUGAR-BEET*;
SUGAR-CANE*; VEGETABLE*; VITAMIN*; WHEAT; WINE*; (the asterisk * sign marks arbitrary
ending of the word).
This wider (level-1) profile is then restricted with the specifics of the level-2 field, partly
taken form the topics of the constituent subfields:
B2.1: Food chain management
B2.2: Transportation
B2.3: Storage
50
B2.4: Cooling
B2.5: Processing
B2.6: Conservation
B2.7: Packaging
The characteristic keywords of the B2 field thus include terms like
CONSERVATION; COOLING; FOOD-CHAIN-MANAGEMENT; FOOD-TECHNOL*;
PACKAG*; POSTHARVEST; PROCESSING; STORAGE; TRANSPORTAT*; etc.;
FREEZING;
If required, negative criteria may also be set to exclude undesirable combinations of key
terms, e. g.,
PROCESSING NOT DATA-PROCESSING
By combining the above search conditions in a proper logical order, a search profile yielding
exactly the publications belonging to the B2 field can be constructed.
Goodness of the search profiles
The goodness of the search profiles was verified with the help of several other databases in a
few cases. The example of Fisheries & Aquaculture is given below.
Legend: WoS core jrnls: search in the Web of Science database using only journal titles.
WoS spec prof: search in the Web of Science database using the search profiles for the level 2 fields of science,
WoS gen prof: search in the Web of Science database using simplified search profiles for the level 1 fields of
science,
Scopus: search in the Scopus database using simplified search profiles for the level 1 fields of science,
CAB Abs: search in the CAB Abstracts database using simplified search profiles for the level 1 fields of science,
The search profiles were generated by the Institute for Research Policy Studies, Hungarian Academy of
Sciences.
51
Although for some less developed countries there can be larger differences, in general the
distribution of publications among the EU countries (and the USA) is very similar, however,
relevance of the specific, somewhat more in-depth search profiles for the level 2 fields of
agrifood science was observed to be higher.
An addendum to this mapping report contains the search profiles by fields of science.
Trend analysis in Chapter 3.4
To make time trends easily and directly traceable, a different citation counting scheme was
used in the 3x3yrs table. Here, citations to each paper was counted in a three-year period (the
year of publication plus the subsequent two years), that is, the same citation time window was
applied independently of the year of publication. Indicators for three three-year periods were
then formed and tabulated. The tenth year of the study (2005) was left out from this analysis,
since the required citation window was far not completed in the time of the data retrieval.
52
7.3 Basic agrifood bibliometric indicators
Number of publications by countries and fields of science 1996-2005
World EU-33 USA AT
BE BG
A1 2 378
772
702 22,3 31,7
0,5
A2 6 969 1 697 2 394 27,2 29,4
0,3
A3
813
238
254
5,7
2,0
A4 1 232
338
567
9,8 12,7
A5 1 280
382
454
3,4 10,2
1,5
A6 1 448
501
500
9,4 16,0
1,3
A7
195
67
58
0,5
4,2
1,0
B1 5 681 2 103 1 684 24,3 75,1
2,5
B2 5 433 2 187 1 099 14,9 73,8
6,0
B3
937
427
244
5,3 19,0
0,5
C1 1 219
391
440
5,0 26,7
1,0
C2 2 366
791
766 13,7 23,4
1,0
D1 2 999 1 042
743 13,6 52,1
6,5
D2 3 467 1 116 1 125 29,4 34,6
1,5
D3 3 165 1 014
804 17,4 32,7
9,5
D4 6 747 2 179 1 139 53,1 48,6
7,0
E1 1 674
576
483 19,0 15,9
3,8
E2 7 836 2 505 1 640 39,7 49,6
3,5
E3 4 017 1 077 1 224
5,2 13,6
0,5
E4
998
476
132 31,8
4,5
F1
8 826 3 362 1 816 43,2 78,5
5,1
F2
1 070
419
221
9,3 13,0
F3
3 945 1 208
647 20,0 28,4
F4
5 509 1 886 1 135 23,8 68,1
1,5
F5
802
228
99
3,8
2,5
2,0
G1 4 264 1 607 1 301 32,7 56,2
5,3
G2 5 379 2 293 1 517 37,2 56,7
2,5
G3 5 746 2 379 1 517 76,0 99,0
2,5
G4 2 436 1 365
264 30,5 47,7
0,5
G5 1 310
363
420
5,0
7,5
0,5
H1 8 441 2 626 2 163 20,9 73,9
0,3
H2 3 988 1 157 1 121
9,4 17,2
2,3
I1 10 376 2 829 3 440 70,0 88,8
4,0
I2
3 364
781 1 118 20,9 13,0
J1
7 799 2 523 1 569 40,9 85,8
3,8
J2
5 353 1 474 1 718 21,0 38,3
4,8
J3
6 560 1 902 2 160 27,3 45,4
3,3
J4
4 932 1 700 1 442 33,4 42,9
2,5
J5
6 346 2 177 2 215 36,0 45,3
6,2
K1 6 690 2 248 1 819 42,7 77,5
1,5
K2 3 756 1 780
651 24,1 56,0
4,0
 128373 52291 38084 798 1372 84,8
HR
CY
2,5
10,0
1,0
2,5
1,0
1,0
6,5
6,0
1,0
3,0
2,0
2,0
1,0
4,2
5,3
0,5
16,5
7,0
0,5
3,5
10,0
2,0
1,0
3,0
6,5
9,5
5,5
0,5
1,0
2,0
6,4
1,3
0,5
19,6
2,5
6,7
1,0
1,0
3,5
4,2
5,5
2,0
1,0
16,0
162
0,3
4,0
1,0
0,5
0,1
2,0
1,6
1,5
22
CZ
3,4
8,5
1,0
5,5
3,6
1,0
1,0
16,3
18,9
0,5
7,0
5,3
12,3
15,6
18,3
21,1
9,0
45,2
29,8
3,0
133,0
5,0
12,3
64,4
11,0
17,7
17,0
42,9
1,5
3,0
43,2
3,0
42,3
6,0
23,8
27,0
16,7
22,5
23,3
37,5
16,4
709
DK
EE
FI
FR
DE GR HU
IS
IE
IL
IT
LV
LT
16,2
1,9 12,5 45,4 111,7 12,3
8,2
2,0
8,3
7,5 17,1
1,5
34,0
6,4 35,4 69,0 116,2 30,7
8,3
1,5 29,3 23,3 41,8
2,6
9,9
8,9
10,8 15,4 31,9
3,8
2,5
4,5
4,0
1,7 10,3
5,5
0,5
9,3 40,5 41,3 13,3
2,7
4,0 14,2
11,5
10,5 44,2 58,4 11,0
1,1
1,0
6,4
3,0 11,4
13,3
1,0 10,3 46,5 64,7 11,6
1,0
1,5
6,2
2,7 12,6
1,0
0,5
0,3
0,5
3,8 14,0
2,0
1,5
0,5
4,5
68,9
0,5 95,2 214,6 316,7 15,5 19,6
0,5 55,1 29,3 157,7
2,0
87,5
37,5 201,6 238,6 99,4 28,0
1,4 81,8 92,0 204,7
23,6
4,5 45,9 58,9 11,8
3,5
14,8
3,5 24,1
13,0
6,2 22,2 73,0
5,0
4,7
1,0
8,3
5,5 21,9
30,0
3,3 22,7 66,6 93,1 29,8 19,2
5,0 11,5 64,3
0,5
2,0
24,2
14,9 183,8 158,3
9,3 10,4
1,0
4,7 35,7 79,6
1,0
24,9 27,9 73,8 107,2 203,7
9,5
8,3
1,6
3,9 20,7 71,1
0,5
32,0
2,8 17,0 111,7 160,5
7,9 18,7
5,6 35,6 60,6
0,5
0,5
55,7
4,0 149,7 127,4 283,5 37,7 10,0
11,6 21,3 196,0 11,0
4,0
8,8
4,3 27,7 57,7 105,4
3,0
3,8
0,5
2,0 16,5 29,9
1,0
83,3 11,5 92,4 240,3 460,1 28,6 87,0
2,0
5,2 74,8 115,2
1,0
6,5
61,3
20,6 73,2 172,8 18,8 38,7
3,0 33,5 50,9
1,0
1,0
59,4
23,0 13,3 109,2
3,5
1,5
0,5
3,0
4,0 20,2
3,0
79,5
2,5 66,3 456,1 533,3 63,7 36,6
4,0 73,4 50,7 177,8
0,1
2,1
11,4
0,8 11,2 45,4 94,2
5,0
6,5
2,5
7,0 22,0
78,8
1,0 31,3 176,5 156,6 11,4
3,5
1,3 65,0 20,5 66,5
77,4
0,5 50,6 246,0 277,7 29,0 12,3
0,2 43,0 39,7 64,9
2,8
7,0
1,5 14,8 35,3
2,7
2,5
14,1
1,5
34,9
2,3 21,8 154,9 276,0
5,5 40,4
2,5 23,1 30,2 106,7
0,5
73,1
4,5 57,8 199,6 348,2 11,0 14,8
1,2 24,5 44,1 65,7
1,0
3,0
66,0
1,5 12,4 150,6 512,1 14,4 81,6
1,9 28,2 29,0 75,7
5,5
86,6
30,7 55,3 279,1
1,3 11,8
1,5 17,8
5,0 51,4
1,0
9,5
9,6 31,1 45,2
8,3
2,0
2,0
6,0
7,2 17,9
1,0
78,8
2,1 67,4 349,7 174,1 56,9 29,0 11,1 40,5 103,4 160,3
0,6
1,0
55,8
2,3 40,1 143,9 68,9 36,0
2,8 17,7 10,2 14,2 90,2
0,3
74,4 23,1 288,2 235,7 473,0 42,8 12,6
1,4 13,3 36,7 81,7
2,2
4,2
23,3
5,2 168,5 34,4 78,7 11,5
9,2
5,0 25,8
0,2
0,2
133,0
4,5 70,5 264,1 447,4 24,8 40,7
5,0 17,2 47,2 109,4
6,5
19,3
0,8 41,2 150,2 156,7 48,9 19,7
0,1
5,9 45,3 69,6
1,5
2,6
54,2
8,5 100,6 155,6 182,3 33,0 18,1
4,2 13,7 20,2 87,0
3,2
55,1
3,9 61,8 143,5 250,3 27,0
7,3
2,3
9,5 30,5 116,0
2,0
61,3
6,2 47,6 212,7 345,4 38,5 11,3
4,0 12,6 16,7 85,5
0,5
101,4
8,0 126,0 246,0 291,6 42,5 54,7
5,0 14,0 32,5 109,6
0,5
64,9
1,1 31,6 224,1 175,8 51,2 17,8
1,2 62,6 12,7 211,9
1,0
1587 118 1656 4629 6706 782 607 70,8 645 893 2649 26,8 54,8
LU
MT
0,5
0,5
0,5
1,0
0,5
0,5
0,5
0,5
3,8
0,3
0,3
1,3
2,5
2,1
0,5
2,0
0,3
0,5
10 6,25
NL
131,9
115,1
31,5
35,1
41,8
70,7
4,8
137,0
87,5
34,6
44,1
63,2
67,0
51,4
85,3
63,5
26,3
118,3
61,0
50,5
182,5
32,7
90,9
123,6
2,3
88,5
147,5
176,1
126,1
40,8
97,1
42,7
131,4
35,0
179,6
176,8
165,2
121,5
133,0
164,6
57,4
2962
NO
20,9
39,4
10,7
7,0
16,5
21,8
2,0
24,7
34,7
13,8
5,5
13,4
10,9
21,2
10,7
34,5
8,3
43,6
11,1
15,0
81,3
9,3
32,2
35,4
19,2
42,8
29,3
22,5
7,5
298,9
73,6
88,7
32,0
49,8
18,0
40,7
35,0
63,7
69,2
27,0
1220
PL
4,6
22,3
0,5
1,1
2,3
33,8
36,3
4,0
2,7
4,4
13,9
8,9
23,8
48,3
9,7
46,7
14,9
1,2
124,3
8,0
11,5
88,2
12,0
98,2
20,5
156,6
6,0
6,3
66,5
14,2
40,2
7,5
35,8
17,0
16,4
33,5
10,6
21,2
28,9
1020
Source: 10 year data from the Web of Science data extractions by the Institute for Research Policy Studies, Hungarian Academy of Sciences
PT
RO SK
5,7
1,2
7,3
6,5
1,5
8,6
2,1
3,0
1,5
3,5
1,0
14,8
3,3
0,5
8,3
5,0
15,5
0,8
3,2
26,4
2,0
4,0
5,5
1,0
1,0
0,5
1,0
8,3
1,9
1,5
9,4
5,6
9,2
3,4
9,1
1,5
2,2
44,6 13,0 15,2
3,8
1,2
3,2
32,7
2,0 11,8
4,5
2,0
4,8
31,7
1,0
4,3
12,6
9,4
0,3
7,2
3,0
2,3
6,3
1,0
8,3
1,5
4,0
0,6
46,8
2,0
20,9
1,3
33,9
3,1
8,3
11,4
3,3
20,8
1,2
22,1
4,5
29,4
3,5
9,6
5,2
31,3
2,2
38,5
6,0
489 58,8
38,8
2,0
6,0
20,4
2,3
20,9
14,5
13,6
0,3
1,0
3,8
1,0
45,8
2,0
1,5
9,0
10,0
28,3
4,4
9,0
9,8
295
Citations per publications by countries and fields of science 1996-2005
A1
A2
A3
A4
A5
A6
A7
B1
B2
B3
C1
C2
D1
D2
D3
D4
E1
E2
E3
E4
F1
F2
F3
F4
F5
G1
G2
G3
G4
G5
H1
H2
I1
I2
J1
J2
J3
J4
J5
K1
K2
Av.
World EU-33 USA
5,3
5,2
6,2
5,1
5,0
5,9
5,2
4,5
6,3
5,0
4,2
5,4
3,4
2,9
4,2
4,4
4,0
5,3
3,3
3,4
4,2
12,3 12,1 16,2
7,0
8,2
8,1
7,0
6,8
8,7
4,1
3,8
5,3
6,3
5,8
7,2
15,7 15,6 23,0
16,1 15,2 20,1
10,8 11,3 13,9
7,2
8,1 11,1
14,0 13,2 17,1
7,7
8,6
9,7
7,5
7,6
8,7
7,3
6,6 11,2
9,5
9,7 16,5
8,9
7,2 15,5
5,8
6,5
7,7
6,6
6,9 10,8
4,2
4,4
8,2
11,8
9,3 17,5
10,6
9,7 13,4
6,2
5,6
8,4
4,4
5,3
4,1
7,8
6,6 10,4
8,3
8,5
9,0
11,6 10,7 13,5
10,7 10,2 13,5
6,5
6,6
8,2
8,0
9,1
9,3
6,2
5,2
8,4
11,1
9,9 13,2
7,4
8,3
9,3
14,6 14,5 16,2
7,1
7,3
7,8
8,4
9,1 12,3
8,7
8,5 11,3
AT
4,7
1,4
3,3
5,0
2,1
2,5
1,0
10,6
5,9
7,6
10,3
5,8
17,9
10,5
14,1
6,8
11,9
5,1
27,2
2,2
18,9
2,6
3,2
3,9
2,6
13,6
10,9
3,5
6,1
3,4
12,7
6,0
8,5
11,1
7,1
3,3
8,6
4,6
8,3
9,0
7,1
7,8
BE
8,8
6,8
2,8
9,2
2,9
5,3
3,6
11,8
10,6
9,6
2,2
9,8
18,3
17,2
9,7
13,6
10,7
7,6
5,5
3,9
8,9
6,8
4,4
7,2
26,2
6,0
7,3
6,2
3,4
4,1
10,3
5,1
15,0
14,5
8,7
4,7
9,3
9,8
8,8
8,1
7,5
8,8
BG HR
CY
0,0
0,8
1,0
1,3
0,0
0,4
2,0
1,2
0,0
8,2
4,3
1,0
0,0
11,0
2,3
0,3
0,5
5,1
3,9
3,4
0,0
5,1
2,5
0,0
4,2
2,8
2,0
0,3
9,5
4,8
0,0
1,0
3,9 10,0
1,7
1,4
3,0
0,8
2,0
0,7
2,0
5,5
8,0
1,0
12,0
1,2
6,5
4,0
1,6
1,5
1,9
1,2
0,6
3,9
1,5
0,0
1,0
0,0
0,0
1,0
4,2
2,0
13,9 16,8 42,0
1,8
0,8
5,7
0,8
11,2
6,2
7,3
4,7
2,3
3,6
4,0 18,0
1,0
2,0
1,0
0,0
6,2
1,0
8,0
0,5 16,3
1,7
0,3
2,5
4,1
CZ
2,6
4,2
2,0
0,2
0,3
0,0
0,0
5,5
3,9
5,0
0,9
3,8
15,0
7,3
5,4
7,8
12,3
4,3
1,1
2,3
2,6
1,1
1,2
2,5
3,5
4,8
4,8
3,2
11,3
2,2
5,2
3,7
2,7
10,7
7,0
2,6
5,4
5,0
7,5
2,5
5,3
4,1
DK
EE
FI
FR
6,7
9,3
7,7
4,6
4,7
5,1
4,0
4,1
4,5
2,4
3,9
2,2
2,0
2,9
3,6
3,7
1,4
1,7
2,5
1,0
3,0
2,4
67,0
0,0
2,1
10,6
3,0 15,6 12,8
10,8
9,1
8,8
9,6
4,8
4,0
3,0
2,1
8,0
6,0
0,4
8,7
5,1
14,6
19,9 13,9
17,3 17,6
9,9 14,9
10,1
3,4
6,4 12,8
6,3
2,3
6,3
8,6
9,1
6,6
8,7 13,5
11,5
5,0
6,7 10,5
11,7
5,0
9,4
7,4
5,0
3,6
9,1
4,3
8,9 10,1
8,6
3,8
7,2 10,8
7,4
6,0
5,7
7,5
8,3
3,0
5,1
6,5
2,4
3,7
1,3
9,6
4,1
9,8 11,3
10,1
7,9
9,5
8,8
10,2
8,0
9,9
4,9
5,6
2,9
6,6
20,5
7,2
4,8
9,4 10,3
8,8
8,3
11,4
3,7
6,6
7,6
12,4
3,2
9,9
9,9
6,8
1,3
5,1
6,1
10,0
4,7
8,9
9,0
9,8
8,8
7,7
5,5
9,2
2,1
8,5
8,0
12,0
6,6
8,5
9,2
11,6 21,4 10,1 14,5
8,9
3,2
6,3
7,7
12,7
3,7
8,0 11,5
9,8
7,7
8,1
9,3
DE GR HU
IS
IE
3,3
1,7
4,8
5,0
3,8
2,5
3,9
2,5
2,0
3,5
1,9
1,3
6,2
2,8
8,4
3,2
1,5
5,0
1,4
2,4
0,0
2,0
4,5
2,1
2,9 14,0
1,3
3,0
1,4
0,5
0,0
9,7
4,5
8,9
4,0 18,4
7,1
6,7
5,0
4,3 11,9
4,2
5,7
0,4
5,2
3,2
2,2
1,6 15,5
1,7
5,2
2,6
3,5
3,3
16,0
5,4
7,0
0,0
7,6
14,5
3,2
1,9 26,3
6,1
12,4
5,5
1,7
17,7
10,4
3,7
5,2
8,5
16,3
5,7
3,8
6,0
3,5
9,4
3,4
1,8
5,0
9,4
4,1
3,5
1,9
3,7
5,1
1,4
0,0 30,0
3,7
6,6
3,8
3,5 10,3 13,0
4,1
4,6
5,2
18,0
4,3
3,3
1,3
1,5
9,0
4,4
3,5
2,6 10,0
7,5
3,9
2,1
4,0
10,2
2,4
3,3
3,6
9,3
6,6
2,4
5,0 14,3
6,6
3,8
6,3
2,0
8,7
5,5
2,6
3,0
1,0
0,3
6,0
3,7
3,2
2,0
0,0
4,8
7,5
8,3
3,6
6,3
9,3
10,6
8,8
1,9
6,9
5,3
10,4
3,8
3,9 65,0
6,3
5,5 15,3
2,5
8,7
4,7
3,1
2,6
6,5
5,7
3,3
0,6 173,0
2,5
7,6
4,6
5,5
5,0
3,9
7,8
3,0
5,1
1,0
2,8
12,0
4,8
5,0 10,2
8,7
8,3
3,1
2,7
3,6
3,3
8,1
6,6
4,6 14,9 13,9
7,9
4,7
3,0
7,2
9,1
IL
IT
LV
LT
LU
MT
6,6
4,8
5,0
2,8
6,0
5,2
2,4
9,0
3,2
4,2
6,8
7,8
2,0
1,2
3,5
2,8
2,0
0,0
2,0
1,7
10,9
7,5
1,5
1,0
9,7
5,6
9,9
3,2
1,8
4,0
6,6
5,9
0,0
1,0
1,0
22,9 11,0
11,0
17,4 11,3
0,0
6,5
14,8
6,8
2,0
0,0
15,8
8,1
9,0
2,0
14,2
9,4
11,0 30,0
10,0
6,9
2,0
2,3
6,0
8,5
0,0
1,0
3,0
6,3
0,7
11,7
7,4
3,0
2,5
7,9
8,9
3,7
4,7
9,7
5,1
0,4
8,1
7,3
18,5
8,0
5,0
12,8
7,8 19,0
0,8
4,9
4,8
4,5
5,9
3,0
0,0
4,9
4,6
7,5
7,5
5,3 15,7
5,0
1,0
8,1
11,2
9,3
4,0
1,0
2,0
10,9 10,4
2,3
2,6 21,6
8,7
3,9
0,0
0,0
6,7
7,0
0,5
2,8
3,8
4,4
1,1
0,0
0,5
7,0
5,6
3,5
3,4
2,0
14,0
5,7
1,5
0,2
8,9
9,6
2,0
3,8
0,0
5,6
6,1 15,0
3,0
5,2
7,7
9,0
9,5
6,9
6,8
2,7
5,1
5,0
NL
6,6
5,1
6,7
6,2
3,3
5,8
9,6
12,3
14,2
5,4
5,8
7,1
17,0
16,6
11,9
7,0
12,3
11,2
13,8
6,5
15,4
7,3
6,5
8,4
1,4
9,7
10,4
8,6
9,1
8,5
9,0
12,9
12,3
7,1
9,6
4,3
10,8
11,4
11,2
8,2
19,5
9,9
NO
PL
PT
RO SK
5,6
2,9
3,8
1,8
0,5
4,5
2,1
4,4
2,0
0,5
2,9 16,0 12,0
0,7
1,8
1,7
0,3
4,7
5,6
0,0
0,6
5,8
0,9
0,1
0,0
0,8
9,5
0,4
11,3
5,1
7,8
4,8
1,9
11,8
3,7
9,3
5,0
2,5
7,1
0,8
7,1
3,0
1,7
0,9
2,8
0,8
4,0
7,5
6,5
2,5
4,7
6,7
12,1
5,6 10,2
1,7
15,8 11,2
7,9
5,7
5,1
2,9 16,8
1,0
5,0
7,8
2,4
4,4
1,8
1,8
12,2 10,1
4,5
6,2
0,8
5,4
3,5
4,7
3,0
4,2
9,1
2,2
4,1
0,0
2,4
5,8
1,2
7,9
2,2
4,6
0,0
1,6
4,6
4,4
4,8
0,0
5,4
2,0
5,3
1,0
5,7
2,4
4,0 12,0
1,0
1,0
5,1
0,3
1,4
9,6
1,8 13,7
2,9
11,2
3,0 17,1
3,0
2,6
7,6
1,8
4,3
3,7
3,1
6,5
1,3
2,1
8,0
9,7
2,8
6,1
0,0
11,1
2,6
5,7
1,0
2,1
9,7
3,1
5,6
3,5
2,0
10,9
7,0
5,4
3,8
2,4
7,6
3,1
6,8
0,0
8,3
4,0
4,6
7,2
2,7
7,6
2,4
5,4
2,3
2,0
8,2
3,2
6,1
1,8
1,3
10,6
5,2
5,4
0,9
1,1
12,9
8,2
9,2
7,6 11,1
8,1
3,9
4,0
4,0
3,7
9,5
3,6
7,8
0,7
5,1
9,3
2,9
6,0
2,7
2,2
Source: 10 year data from the Web of Science data extractions by the Institute for Research Policy Studies, Hungarian Academy of Sciences
54
Publications (P) and citations per publications (C/P) by the top 30 EU-33 institutions and fields of science 1996-2005
INSTITUTION
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
INRA
UNIV WAGENINGEN & RES CTR
SWEDISH UNIV AGR SCI
CNRS
CSIC
UNIV LONDON
ROYAL VET & AGR UNIV
UNIV HELSINKI
UNIV UTRECHT
DANISH INST AGR SCI
UNIV EDINBURGH
UNIV READING
STATE UNIV GHENT
KATHOLIEKE UNIV LEUVEN
UNIV OXFORD
UNIV HOHENHEIM
TECH UNIV MUNICH
NORWEGIAN UNIV LIFE SCI
CNR
UNIV CAMBRIDGE
UNIV BRISTOL
LUND UNIV
SCOTTISH AGR COLL
HEBREW UNIV JERUSALEM
UNIV ABERDEEN
UNIV WALES
UNIV GIESSEN
AGR RES ORG
UNIV BONN
UNIV ZURICH
FR
NL
SE
FR
ES
UK
DK
FI
NL
DK
UK
UK
BE
BE
UK
DE
DE
NO
IT
UK
UK
SE
UK
IL
UK
UK
DE
IL
DE
CH
TOTAL
PUB C/P
2380 10,3
1508 10,0
1298 11,5
1278 14,3
1227 9,8
836 11,8
621 10,0
608 11,6
524 10,7
519 8,6
516 14,9
490 10,1
490 10,1
470 8,3
433 16,8
427 6,7
421 7,4
413 8,5
411 8,2
401 13,9
392 11,7
372 15,7
367 10,6
334 13,1
328 8,5
324 10,2
320 6,9
302 9,2
302 5,2
287 12,5
A
PUB C/P
103 3,4
221 7,9
44 6,7
24 10,0
14 6,6
198 8,1
15 3,9
24 3,0
32 9,6
8 8,1
44 6,1
50 3,6
15 2,3
49 4,5
65 10,4
19 3,5
25 2,3
38 7,5
3 19,0
46 5,0
23 10,2
19 5,6
21 4,4
23 4,7
54 4,9
62 7,4
22 2,6
4 2,0
23 2,4
12 14,7
B
C
PUB C/P PUB C/P
198 12,1
39 5,8
126 13,2
70 8,0
33 8,2
45 5,8
32 18,4
29 5,8
247 10,4
31 2,5
36 11,5
10 13,9
83 9,7
8 5,0
71 14,0
5 2,4
29 9,7
12 7,1
37 13,3
16 5,9
10 7,0
11 9,7
73 12,0
11 4,3
53 12,6
6 3,7
52 10,3
35 5,3
13 18,8
3 3,0
49 9,1
11 3,6
41 5,3
17 4,2
17 14,3
7 3,9
48 7,8
12 2,3
21 14,2
4 8,0
30 18,3
1 2,0
39 8,5
6 20,5
5 24,0
9 4,1
36 12,7
2 18,5
9 17,0
11 7,1
4 5,3
4 4,5
24 5,4
15 8,5
81 11,8
7 2,7
23 6,8
11 1,5
23 10,0
2 4,5
D
PUB C/P
255 16,5
143 13,4
162 15,4
205 16,5
156 10,8
78 18,7
69 12,6
78 14,3
26 9,4
22 11,6
66 27,8
19 11,2
63 22,5
23 6,0
32 10,7
53 6,8
56 9,3
34 8,8
97 9,1
24 20,3
25 16,2
55 23,9
8 8,8
53 26,1
18 8,3
33 8,5
15 4,4
33 13,8
16 8,1
19 47,3
E
PUB C/P
275 9,4
183 8,9
198 8,3
89 21,3
201 9,4
49 14,2
94 15,4
37 7,1
16 34,4
101 7,4
34 19,9
56 7,6
22 4,0
37 8,9
14 14,8
101 7,2
59 4,1
42 11,0
42 10,8
22 14,5
25 19,3
34 11,6
35 12,5
53 7,9
33 8,0
32 17,3
27 12,5
52 9,4
67 4,7
9 23,0
F
PUB C/P
788 9,9
265 9,3
264 11,1
88 16,0
79 14,0
48 9,0
100 9,7
73 11,4
84 13,5
199 8,5
110 15,6
67 9,0
64 9,2
43 5,5
36 20,9
100 6,3
81 10,0
114 7,5
39 7,2
43 22,7
49 14,3
22 25,2
169 11,9
52 16,6
39 5,4
56 7,8
75 6,2
72 8,3
53 6,1
21 16,7
G
PUB C/P
257 7,7
144 6,9
190 7,9
161 15,8
57 11,9
120 9,1
133 6,6
58 12,4
233 8,1
100 6,4
165 8,9
37 6,7
97 6,3
44 6,4
116 11,7
26 2,9
58 4,8
26 10,6
14 15,4
172 10,6
193 8,8
30 10,5
122 9,3
38 11,6
35 7,2
39 9,4
102 5,4
23 7,9
30 4,8
157 7,7
H
PUB C/P
113 7,7
83 8,9
24 6,8
166 11,8
113 12,1
64 10,6
26 10,6
25 7,0
6 17,7
5 11,0
5 6,6
9 15,8
51 11,6
34 8,1
9 11,4
12 9,9
3 4,7
15 5,5
33 6,5
11 11,7
11 7,4
13 6,5
1 15,0
30 10,6
56 10,4
28 9,2
1 13,0
19 7,8
5 1,8
4 4,8
Source: 10 year data from the Web of Science data extractions by the Institute for Research Policy Studies, Hungarian Academy of Sciences
55
I
PUB
145
111
255
91
50
59
39
166
21
1
63
21
29
26
44
20
43
74
19
22
7
54
4
12
36
33
3
2
10
14
C/P
16,0
9,4
17,6
11,0
9,0
14,1
7,2
13,8
8,7
14,0
24,3
6,8
12,5
13,7
7,2
4,4
7,7
11,3
7,2
15,6
22,4
26,3
4,3
22,7
9,9
7,2
14,0
11,5
4,0
7,6
J
PUB C/P
268 9,1
318 11,4
233 14,3
417 13,7
272 9,1
186 16,1
70 9,1
113 16,0
88 10,9
71 11,6
74 21,9
162 12,8
88 8,3
124 10,5
125 27,5
66 8,8
69 9,1
81 8,6
94 7,5
56 16,1
42 15,2
112 21,6
39 15,0
40 8,2
68 10,8
68 12,8
62 12,3
28 5,0
78 4,5
28 18,3
K
PUB C/P
274 9,4
154 8,1
99 8,9
84 11,1
135 12,6
61 9,1
84 9,7
49 7,4
22 16,6
55 8,6
19 8,9
43 8,7
50 8,6
59 7,4
11 17,5
38 6,2
36 8,3
52 6,7
47 7,6
11 35,4
14 7,9
43 8,5
17 10,7
22 5,6
18 7,9
13 15,7
16 9,6
13 4,2
24 9,0
10 6,2
Fig. 1
Citations per publications in 1996-2005 - Economic, social and political aspects (A)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 2
Citations per publications in 1996-2005 - Food technology, human nutrition and consumer
concerns (B)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 3
Citations per publications in 1996-2005 - Engineering, mechanisation, ICT (C)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 4
Citations per publications in 1996-2005 - Plant breeding and biotechnology (D)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
57
Fig. 5
Citations per publications in 1996-2005 - Plant production and protection (E)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 6
Citations per publications in 1996-2005 - Animal production and husbandry (F)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
58
Fig. 7
Citations per publications in 1996-2005 - Animal health and welfare (G)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 8
Citations per publications in 1996-2005 - Aquaculture and fisheries (H)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
59
Fig. 9
Citations per publications in 1996-2005 - Forestry and landscape (I)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
Fig. 10
Citations per publications in 1996-2005 - Management of natural and biological resources
(J)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
60
Fig. 11
Citations per publications in 1996-2005 - Horizontal issues (K)
Legend: green: less than 10 publications; blue: 10 or more publications
Source: computations from the Web of Science database by the Institute for Research Policy Studies, Hungarian
Academy of Sciences. For the methods used please consult the Annex.
61
7.4 Survey methodology
Two survey questionnaires were used, they are shown as the responders saw them. Some of
the questions were adopted from the Record Manual [2004].
Questionnaire for registration on www.agrifoodresearch.net
THE ANSWERS WILL BE PUBLISHED
Respondent
Full name
Phone
Email
Information on the research group
Name in national language
Name in English
City name in national language
City name in English
Country
Contact person of this research group (published on agrifoodresearch.net)
Full name
E-mail
Tel
Additional contact information
Web Site
I agree to display the e-mail of the contact person on Yes
agrifoodresearch.net
No
BASIC INFORMATION
C1. Please mark: your research organisation is (or belongs to) a:
University / higher education research institution
Public research institute (e.g. Academy of Science, government research
organisation etc.)
Private non-profit institution
Business enterprise
Other type, please specify





C2. Average number of employees in your research group:
Average number of employees in 2005
C3. Over the last 3 years, did your research group:
Yes



Publish articles?
File patent applications?
Commercialise new products or technologies?
62
No



C4. Please indicate the scientific area in which your research group has produced at least one article, or
contributed to at least one project report over the past 3 years:
Research field code (cf attached list)
1
2
3
4
…
C5. Name and Email of researcher
Please indicate the name and E-mail of the researchers from your research group.
Name of the researcher
E-mail address
1
2
3
4
….
Note 1 : An invitation to register on agrifoodresearch.net researcher database will be sent by E-mail.
Note 2: Researchers will indicate the reference of their publications and research projects. Without this
information, the research group will not appear in the search of agrifoodresearch.net.
Questionnaire for the mapping survey
THE INFORMATION WILL NOT BE PUBLISHED
A.1. PLEASE MARK IF THE A, B, C OR D TYPE IS THE CLOSEST TO YOUR ORGANISATION:
Organisation tasks / 'Complete' research organisations
'Partial' research organisations
Organisational forms
A
B
Commercial (non(e.g. R&D enterprises)
(e.g. in-house R&D in industrial
public)*
enterprises)
C
D
(e.g. research institutes in Academy of (e.g. universities, state-financed institutes
Public (nonSciences networks, foundations that
that conduct routine analysis as well as
commercial)**
perform research as their professional
research, foundations that perform
activity etc.)
research as a part of their activities, etc.)
* organisations that operate in a competitive business environment and primarily for business purposes
** organisations that operate in a non-competitive, non-business environment
B.1 NUMBER OF EMPLOYEES AND RESEARCHERS (INFORMATION FOR THE RESEARCH
GROUP )
2005
Total number of employees on a Full-Time-Equivalent (FTE) basis
Total number of researchers* on a Full-Time-Equivalent (FTE) basis
Number of researchers with Ph.D. degree or higher on a Full-Time-Equivalent (FTE) basis
Number of researchers under 35 on a Full-Time-Equivalent (FTE) basis
*Ph.D. students can be included if they are involved in research projects that would be ongoing even without the
Ph.D. student concerned. ’Engineers of the department’ and technical support staff are also to be included
63
Please mark your assessment on the evolution of young research personnel (researchers under 35) in the
research group:
The percentage of young researchers has increased in the last 5 years

(there are more young researchers)
The percentage of young researchers has not changed in the last 5 years

The percentage of young researchers has decreased in the least 5 years

(there are less young researchers)
B.2 INTERNATIONAL MOBILITY
Total number of foreign researchers hosted for more than 1.5 months in the last 3 years (2003
– 2005) *
Number of researchers sent abroad to do research for at least 1.5 months in the last 3 years (
2003 – 2005)
*please do NOTcalculate those, who came to acquire a Ph.D. degree
B.3 GENDER
Percentage of women in the total number of researchers
Please mark your assessment on the gender of research personnel:
The percentage of women researchers has increased in the last 5 years (there are more women
researchers)
The percentage of women researchers has not changed in the last 5 years
The percentage of women researchers has decreased in the least 5 years (there are less
women in research)



B4. RESEARCH INFRASTRUCTURE
Please mark your assessment of the physical research infrastructure (without office equipment):
The research organisation has an internationally competitive technology and it is able to conduct
top research in cutting-edge research topics
The research organisation has top research infrastructure, the infrastructure enables regular
international research co-operation but it is not competitive if compared with the 'best in our
research field'
The research organisation has good quality research infrastructure, probably one of the most upto-date in the country, but it is not good enough to join in international research on a regular basis
The research organisation has an obsolete research infrastructure if compared with international
organisations and it is an obstacle to international research co-operation
The research organisation has a rather obsolete research infrastructure and it is an obstacle to
more domestic contracts
We have no substantial infrastructure, but we have access to it and can participate in top research
both nationally and internationally






C1. SCIENTIFIC PRODUCTION AND INNOVATION IN THE LAST 3 YEARS
2003-2005
Number of important innovations*
Number of domestic patents granted:
Number of patents granted by the EPO and/or JPO and/or USPTO **
Number of publications in journals reviewed by the Institute for Scientific Information***
*Important innovation: a new product / technology / organisational mode / tool or method had or contributed to
an additional turnover of more than EUR 100 thousand or more than 500 people use a new product/technology
or it saved life or improved the quality of life substantially. The research organisation's contribution is
substantial if at least one third of the new knowledge came from the research organisation.
** EPO : European Patent Office ; JPO: Japan Patent Office ; USPTO: United States Patent and Trademark
Office
***and thus appears in the Science Citation Index
64
C2. LARGE RESEARCH PROJECTS
ongoing
/started
2005
in
completed in
2005
Number of large research projects*
Of which: the number of projects in collaboration with industry
the number of projects in which the organisation co-ordinates
the number of European Union Framework Programme projects
*the total project budget is above EUR 100 thousand and the organisation’s share is at least EUR 20 thousand.
C3. ACTIVITY BY RESEARCH AREAS
Please provide the number of important innovations, patents, large projects and international articles realised in
the last three years (2003, 2004 and 2005) for each scientific area (note: the total can be higher than the total of
C1)
Number
important
innovations
Number of
of international Number
patents
of large
(EPO; JPO; projects
USPTO)
Scientific field code
(cf attached list)
Number of
articles
in Number of Number of
international studies and standards
jou
reports*
written**
rnals
Number in 2003-2005:
* Only reports financed by and / or supplied to national (and international) organisations. The research group is
a major contributor to these reports: at least one third of the knowledge should come from the research group.
**Only approved standards. The research group is a major contributor to these reports / standards: at least one
third of the knowledge should come from the research
65
D1. INDICATE RESEARCH budget breakdown (for the last 3 years):
PLEASE MAKE SURE THAT YOUR ANSWERS CONCERN RESEARCH BUDGET ONLY.
What percentage of your annual research budget is financed by
0-5%
6-25% 26-50%, 51-75% 76-100%
a) Private companies?





b) International sources(such as the EU, UN, OECD,





NATO etc.)?
c) Not competitive* government financing?





d) Competitive* government financing?





e) Other sources (foundations, non-profit organisations,





etc.)?
*Projects won after competitive bidding procedures – so that the organisation can actually lose the funding
targeted at the end of the procedure – count as source on a competitive basis. If the organisation participates in a
money-allocation mechanism so that the money cannot be lost (but e.g. 'only' reduced), it counts as source on a
non-competitive basis of research funding even if the procedure itself is called 'competitive bidding'.
The sample and the response rate
Table 7
Number of agrifood research units in the master list and the response rate (%)
Higher
education
research unit
Public
research
institution
Private nonprofit
research
313 (26%)
PL
261 (60%)
45 (22%)
TU
194 (51%)
CZ
108 (52%)
71 (61%)
88 (81%)
68 (93%)
RO
43 (81%)
115 (89%)
BG
HU
78 (73%)
33 (67%)
HR
71 (54%)
48 (56%)
39 (82%)
EE
15 (73%)
15 (80%)
SI
34 (71%)
23 (96%)
24 (92%)
LT
21
(86%)
15
(100%)
SK
23 (96%)
12 (92%)
LV
CY
1
8
MT
5
4
Total
1 041 (54%)
734 (69%)
Source: AgriMapping Survey November 2007
4
9
11
2
3
Business
research
organisation
5
7
9
11
5
5
1
2
3
32 (66%)
Other
Total
1
1
9
16
4
2
1
0
4
2
5
2
58 (76%)
0
2
1
37 (84%)
584 (41%)
247 (45%)
206 (59%)
194 (85%)
169 (86%)
121 (72%)
121 (55%)
56 (80%)
52 (75%)
47 (94%)
40 (93%)
39 (95%)
15 (73%)
11 (82%)
1 902 (61%)
About half of the higher education agrifood research units and two third of the public agrifood
research organisations responded to the survey questionnaire. The best response rates (>80%)
were attained in Latvia, Lithuania, Slovakia, Bulgaria, Romania, Malta and Estonia.
Naturally, Poland and Turkey managed to collect less answers to the questionnaire in relative
terms, but in absolute numbers we are talking about several hundreds of agrifood research
units only from these two countries.
66
Fig. 12
Agrifood research capacities by type (for all units in the master list)
Source: AgriMapping Survey 2006-2007
Fig. 13
Number of agrifood research units and the responders
Source: AgriMapping Survey 2006-2007
67
SI
TR
Source: AgriMapping survey 2006-2007
Researchers under 35
(FTE, 2005)
Researchers with PhD or
higher degree (FTE, 2005)
Large EU projects
completed in 2005
SK
61
149
5
3
70
47
11
4
188
78
9
10
19
45
12
111
42
4
22
11
29
21
9
135
291
132
94
9
13
21
36
33
5
59
27
6
140
16
Large EU projects ongoing /
started in 2005
RO
12
36
4
1
6
5
4
2
18
11
5
3
3
4
7
17
10
4
9
5
8
8
0
20
61
15
38
3
8
9
8
6
4
4
3
2
7
5
Large projects completed
with industry in 2005
MT
PL
3
23
4
0
3
2
0
1
7
8
3
2
2
3
1
9
8
4
9
4
2
1
0
18
42
26
32
5
4
5
1
2
1
1
3
0
5
1
Large projects ongoing /
started with industry in 2005
LT
34
99
4
2
38
26
6
2
55
42
7
9
7
32
10
57
21
4
22
10
21
22
3
81
155
70
63
7
10
11
18
15
4
24
12
3
98
10
Large projects completed
in 2005
LV
191
164
471
664
25
17
11
10
253
325
150
197
41
26
8
1
355
314
236
226
19
26
33
44
37
35
109
104
24
29
323
211
143
134
9
7
90
153
61
112
84
107
67
97
8
8
394
511
632
929
593
660
469 1237
27
37
35
44
51
103
309
297
273
480
12
18
101
102
70
111
15
18
792
530
127
70
Large projects ongoing /
started in 2005
HU
355
296
1100
823
42
23
14
6
535
314
333
210
65
37
10
6
706
513
471
249
68
31
81
29
81
43
265
179
57
32
609
378
321
179
17
10
271
179
180
92
208
171
177
115
17
16
971
757
1891 1299
1276
866
1953
801
69
47
82
34
183
73
848
449
885
402
32
16
193
134
217
79
23
10
1765 1269
283
78
Triadic patents granted
in 2003-2005
EE
445
2269
178
43
779
557
247
17
981
695
195
217
170
424
135
952
775
26
314
445
296
256
26
1175
3707
1660
4121
81
1528
778
1443
1556
159
259
391
39
1985
783
Domestic patents granted
in 2003-2005
CZ
2426
1955
188
43
813
455
258
15
2089
1559
104
161
130
412
93
2949
1100
716
292
289
210
205
24
8004
5225
1988
3400
71
949
319
2903
1291
166
451
355
33
1694
474
Important innovations
in 2003-2005
CY
35
101
4
3
38
27
6
3
55
43
7
9
7
32
11
57
22
5
22
11
22
22
5
81
156
70
63
7
10
13
18
15
4
24
12
3
98
10
Researchers sent abroad
for more than six weeks
in 2003-2005
HR
Public research institution
business enterprise
other nec
university / higher education
Public research institution
Public research institution
business enterprise
university / higher education
Public research institution
private non-profit
business enterprise
other nec
university / higher education
Public research institution
university / higher education
Public research institution
business enterprise
university / higher education
Public research institution
university / higher education
Public research institution
university / higher education
university / higher education
Public research institution
university / higher education
Public research institution
private non-profit
business enterprise
other nec
university / higher education
Public research institution
business enterprise
university / higher education
Public research institution
private non-profit
university / higher education
Public research institution
Researchers
(FTE, 2005)
BG university / higher education
number
Employees
(FTE, 2005)
type
Employees
(headcount, 2005)
Country
Research organisation
Women researchers
(FTE, 2005)
Organisations that
published articles in 20032005
Organisations that filed
patent applications in 20032005
Organisations that
commercialised new
products or technologies in
2003-2005
Foreign researchers hosted
for more than six weeks
in 2003-2005
7.5 Basic survey results – summary statistics by countries
88
229
6
3
145
58
12
6
283
101
8
9
20
68
15
137
50
4
33
13
52
33
8
181
372
254
157
13
15
23
62
67
5
56
26
6
277
20
65
202
62
3
50
68
8
8
98
53
21
15
11
33
17
114
48
10
30
150
36
45
7
147
299
144
359
11
46
46
32
91
19
25
20
6
126
39
51
228
20
3
49
33
6
3
68
62
20
14
11
37
18
62
53
9
39
50
23
23
5
111
277
115
269
18
25
56
45
19
5
29
14
3
104
52
35
137
4
3
38
27
6
3
55
46
11
9
14
32
11
52
20
6
32
23
35
21
5
79
168
71
63
9
12
13
24
15
4
26
12
3
100
10
58
238
9
3
59
70
45
21
121
138
46
33
17
75
24
131
61
12
71
40
45
31
8
144
482
333
516
30
22
70
73
60
7
72
69
6
234
23
48
150
5
3
68
45
9
13
92
67
18
14
10
43
11
88
42
6
22
21
32
24
5
105
281
213
301
16
14
47
47
59
13
31
26
4
137
13
48
139
16
3
46
37
9
13
82
53
14
14
11
42
12
95
38
9
33
35
28
24
5
98
203
161
222
18
17
36
32
25
5
47
44
3
111
14
39
120
11
3
46
31
6
6
65
46
7
10
7
33
11
72
31
6
22
21
26
22
5
97
195
112
138
13
14
29
28
20
6
27
19
3
100
12
45
131
4
3
44
34
15
11
64
57
11
10
7
49
11
64
35
8
43
17
27
26
7
95
249
99
97
10
15
20
40
38
4
37
28
3
110
10
43
110
4
3
38
28
10
10
60
47
8
12
8
38
11
56
28
5
22
11
25
22
5
89
196
87
91
8
12
16
32
29
4
28
22
3
99
10