07/AGRI-01 — Agricultural and Food Economics and Rural Appraisal

Danilo Bertoni

Associate Professor · MILANO
Scienze e politiche ambientali
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16
h-index
824
citations
28
publications
72%
in Q1 journals
2011
first paper
01
Indicators
Output and impact
25
g-index
21
i10-index
13
co-authors in the field
1.118
mean SJR

Working style and trajectory ?

16
career years
1.00
m-quotient
4.68
topic diversity
26
autonomy
m-quotient · 1,00 (field median 0.80)
Topic diversity · 4,68 (field median 4.50)

Output and quality

Publications per year

1
'11
1
'12
4
'15
3
'16
1
'17
3
'18
2
'19
3
'20
2
'21
2
'22
2
'23
1
'24
1
'25
2
'26

Journal quartiles (SJR · SCImago)

25with SJR
Q1 18 (72%)
Q2 4 (16%)
Q3 3 (12%)
Q4 0 (0%)
first indexed publication in 2011  ·  22 different outlets · 82% open access · 24 papers co-signed with others in the field · 25% with international co-authors (7 papers out of 28)
Article 22 · Book chapter 3 · Review 3

Recognition

1 paper is in the top 5% most cited among all papers of the field published in the same year. The threshold is recomputed year by year.
02
Collaboration
Network, projects and conferences

Collaboration in Italy

3institutions of the field co-signing papers, besides their own (with at least one joint paper)
  1. Brescia1
  2. Palermo1
  3. Verona1
own institution · circles proportional to joint papers

International collaboration

    PhD programmes

    • Member of the faculty board of the PhD programme in SCIENZE AMBIENTALI
      Università degli Studi di MILANO

    National research projects

    1 PRIN projects. Amounts are the share of their own research unit.
    • UNIT Linking Research Evidence to Policy Impact and Learning: Increasing the effectiveness of rural development programmes towards Green Deal goals (RECIPE)
      PRIN 2022 · €40,800 out of €204,808 for the project, 5 units · panel SH1
    Source: PRIN database of the Italian Ministry of University and Research (MUR). Calls covered: 2017, 2020, 2022 and 2022 PNRR; a project from another call does not appear here.

    Conference presentations

    Contributions presented at the conferences of the field whose programme the Observatory keeps.

    Main co-authors in the field

    Works with 13 researchers of the 07/AGRI-01 field. The number is the papers signed together.
    Co-authorInstitutionJoint papers
    Daniele Cavicchioli MILANO 20
    Alessandro Olper MILANO 6
    Dario Gianfranco Frisio MILANO 3
    Giovanni Ferrazzi MILANO 2
    Lucia Baldi MILANO 1
    Alessandro Banterle MILANO 1
    Daniele Curzi MILANO 1
    Eugenio Demartini MILANO 1
    Anna Antonia Maria Gaviglio MILANO 1
    Giuseppina Migliore PALERMO 1
    03
    Research
    Topics, journals and publications

    Research topics of the field

    Topics of the Observatory, among the 60 tracked, on which this researcher has published: the area of each box is proportional to the papers, the percentage is on the total of their papers. A paper can touch several topics, so the shares do not add up to one hundred.
    Common Agricultural Policy · 5 papers · 18%Common Agricultural Policy18% of papersGovernance and institutions · 4 papers · 14%Governance and institutions14% of papersSustainability assessment · 4 papers · 14%Sustainabilityassessment14% of papersCooperatives and collective action · 3 papers · 11%Cooperatives andcollective action11% of papersCorporate social responsibility and agri-food firms · 3 papers · 11%Corporate socialresponsibility andagri-food firms11% of papersEconometric and statistical methods · 3 papers · 11%Econometric andstatistical methods11% of papersKnowledge, extension and human capital · 3 papers · 11%Knowledge,extension andhuman capital11% of papersConsumer behaviour · 2 papers · 7%Food supply chains · 2 papers · 7%Food supplychains7% of papersFruit and vegetables · 2 papers · 7%Fruit andvegetables7% of papers

    Relative specialisation

    How much a topic weighs here compared with the whole field: above 1 there is specialisation, below 1 the topic is less present than average. The grey tick marks parity. Topics with fewer than three papers are excluded, where the ratio would say little.
    TopicPapersRelative specialisationIndex
    Knowledge, extension and human capital3
    6.06
    Corporate social responsibility and agri-food firms3
    5.58
    Common Agricultural Policy5
    4.58
    Cooperatives and collective action3
    3.76
    Econometric and statistical methods3
    2.22
    Sustainability assessment4
    1.42
    Governance and institutions4
    1.19

    Keywords of the publications

    farm transferagricultureyoung farmercommon agricultural policyfamily farminggenerational turnovergreeninghorticultureindicatoroccupational choice theorysustainability assessmentagbiotechagri environmental measureagri environmental schemeagri food economic

    Main journals

    The outlets where this person publishes most often. The name links to the journal page, with who publishes there in the field, the topics covered and the trend over time. Quartile and SJR are from SCImago.
    JournalPapersQuartileSJR
    The Common Agricultural Policy after the Fischler Reform: National Implementations, Impact Assessment and the Agenda for Future Reforms 3 — —
    Agricultural and Food Economics 2 Q1 1.010
    Agriculture (Switzerland) 2 Q1 0.767
    Environmental Science and Policy 2 Q1 1.720
    Land Use Policy 2 Q1 1.686
    Agricultural Systems 1 Q1 1.606

    Most cited publications

    04
    Tools
    Report and bibliography
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    Explore the Observatory →All researchersProfile of MILANO
    Profile generated by the Observatory of Italian Agricultural and Food Economics — 07/AGRI-01 — Agricultural and Food Economics and Rural Appraisal. Updated 12/10/2026. Values (h-index, citations) change over time.
    Data are processed from third-party sources (Scopus, SCImago) and provided for information only, with no guarantee of completeness, accuracy or timeliness. They are not an assessment of the quality of research or of people, in line with the CoARA commitments on reforming research assessment. The Observatory is not liable for errors or for decisions taken on the basis of this information. Reports and corrections: info@agecon.org.
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    How to read these numbers

    Technical definitions of the indicators on this profile. They describe how papers circulate in the indexed literature: they do not measure their quality, originality or usefulness.

    h-index

    The largest h such that at least h papers have received at least h citations each. It grows slowly and never goes back; it rewards steady output more than a single highly cited paper.

    g-index

    The largest g such that the g most cited papers add up to at least g² citations. Unlike the h-index it accounts for how much the top papers are cited. Computed excluding reviews: a review collects citations because of its review function, and a single one can shift the result by several points.

    i10-index

    Number of papers with at least ten citations.

    Career years

    reference year − year of the first indexed paper + 1

    They are counted from the first indexed paper, not from appointment: it measures activity in the literature, not seniority. Those who published during their PhD have a career longer than their position.

    m-quotient

    h-index ÷ career years

    Relates the h-index to career length. It avoids comparing a newcomer with someone who has published for thirty years: an h of 12 after eight years and an h of 12 after thirty describe different trajectories. In the field the median is 0.79 and half of the researchers lie between 0.50 and 1.12. The bar below the value shows the gap from the median and stops at double: 42 people out of 494 are above that threshold.

    It remains an indicator of citation volume divided by time. It does not distinguish those who changed field, had interruptions, or work on topics with slow citation cycles.

    Topic diversity

    H = −Σ pk · ln pk

    Shannon entropy computed on keywords, where pk is the share of the k-th keyword in the person's output. It is high for those who touch many subjects in a balanced way, low for those who focus. In the field it ranges from 0 to 6.15: half of the researchers lie between 3.88 and 4.97, the median is 4.57. The bar below the value shows the gap from the median, with the vertical tick marking it: it reads like the bar of the specialisation index, further down this page.

    There is no good value. Focusing on a few topics and ranging over many are two legitimate ways of doing research, and this number does not decide which is better.

    Autonomy

    min(200 ; 100 ÷ mean co-authors)

    Inverse index of the mean size of the author team. It is 100 for those who sign with one co-author on average, 50 with two, 33 with three; it rises above 100 for those who often sign alone, and the cap at 200 keeps a few single-author papers from dominating the scale. Co-authors are counted on Scopus identifiers, not names: two authors with the same surname and initial would appear as one.

    It describes a disciplinary habit more than an individual choice. In experimental sciences twenty authors are the norm, in agricultural economics much less so: comparing the two worlds with this number would make no sense.

    Co-authors in the field

    People of the 07/AGRI-01 field with whom the person has signed at least one paper. External co-authors, who are the majority, are not counted.

    Mean SJR and Q1 share

    SJR is the outlet prestige indicator computed by SCImago; the quartile places the journal within its category. The Q1 share is the percentage of papers published in first-quartile journals. They concern the outlet, not the single paper: a rarely cited article in a Q1 journal remains rarely cited.

    Papers in the top 5% most cited

    The comparison is made within the publication year, because a 2010 paper has had fifteen years to collect citations and a 2024 one has not. For each year the papers of the corpus are taken, excluding reviews, and the threshold is the number of citations of the paper in position ⌈n × 5%⌉. Years not yet concluded are excluded.

    Sources and limitations

    Bibliographic data from Scopus (Elsevier), quartiles and SJR from SCImago. Each profile is built from a Scopus author identifier: a duplicate, incomplete or contaminated profile affects all indicators. If something looks wrong, it can be reported from the personal area.

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