Digital repository of Slovenian research organisations

Show document
A+ | A- | Help | SLO | ENG

Title:Drivers and barriers to DSS adoption in European crop protection : insights from a machine learning analysis of farmer and advisor surveys
Authors:ID Furiosi, Margherita (Author)
ID Marinko, Jurij, Institut "Jožef Stefan" (Author)
ID Podpečan, Vid, Institut "Jožef Stefan" (Author)
ID Debeljak, Marko, Institut "Jožef Stefan" (Author)
ID Fedele, Giorgia (Author)
ID Caffi, Tito (Author)
Files:URL URL - Source URL, visit https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2026.1711425/full
 
.pdf PDF - Presentation file, download (1,90 MB)
MD5: 459CA897F8B24ED8E6B18274819D22A2
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo IJS - Jožef Stefan Institute
Abstract:Integrated pest management (IPM) prioritizes non-chemical alternatives for managing pests and/or diseases, reserving chemicals as last solution, when economically and environmentally justified. The holistic consideration of the agroecosystem makes decision-making in crop protection more complex, as it requires selecting the most appropriate action at the right time. Decision support systems (DSS) for IPM help manage the risks of pests and diseases affecting crops by predicting potential threats and suggesting suitable control measures. However, their adoption remains modest among farmers, despite demonstrated benefits. An anonymous online survey was conducted among farmers, advisors, and other agricultural stakeholders to investigate factors influencing DSS uptake, or lack thereof. The survey distinguished between DSS users and non-users, enabling targeted questions on different aspects of DSS use and adoption. In total, 78 respondents were classified as DSS users and 29 as DSS non-users. Data were analyzed through clustering, followed by statistical validation of clusters and induction of a classification tree, to identify the most influential features shaping cluster formation among both DSS users and DSS non-users. The analysis identified four clusters in the DSS users’ dataset and two clusters in the DSS non-users’ dataset. For DSS users, DSS output reliability and usefulness were identified as the most influential features. Membership in a farmers’ network and DSS ease of use also contributed to cluster separation. For DSS non-users, DSS availability for different cropping systems was the most important attribute determining cluster separation. The results indicate that farmer involvement in DSS development and calibration may enhance trust and, therefore, adoption. Moreover, the need for user-friendly systems providing simple and clear information was highlighted. Although the lack of DSS tailored to specific cropping systems emerged as the main barrier, limited awareness and concerns about costs were also important obstacles. The applied methodological approach presents a reproducible and robust AI-based framework, built on open-source tools, to analyze stakeholders’ perceptions of IPM DSS and extract knowledge from complex survey data. This study provides valuable insights to facilitate DSS adoption for more sustainable crop protection and underscores the importance of both DSS technical performance and end-user needs.
Keywords:AI-based analysis, decision support systems uptake, pathways and obstacles, questionnaire
Publication status:Published
Publication version:Version of Record
Submitted for review:23.09.2025
Article acceptance date:10.03.2026
Publication date:26.03.2026
Publisher:Frontiers
Year of publishing:2026
Number of pages:str. 1-14
Numbering:Vol. 10, [article no.] 1711425
Source:Švica
PID:20.500.12556/DiRROS-28783 New window
UDC:005
ISSN on article:2571-581X
DOI:10.3389/fsufs.2026.1711425 New window
COBISS.SI-ID:273681667 New window
Copyright:© 2026 Furiosi, Marinko, Podpečan, Debeljak, Fedele and Caffi.
Note:Nasl. z nasl. zaslona; Soavtor iz Slovenije: Jurij Marinko; Opis vira z dne 31. 3. 2026;
Publication date in DiRROS:07.04.2026
Views:164
Downloads:83
Metadata:XML DC-XML DC-RDF
:
Copy citation
  
Share:Bookmark and Share


Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Record is a part of a journal

Title:Frontiers in sustainable food systems
Shortened title:Front. sustain. food syst.
Publisher:Frontiers Media S.A.
ISSN:2571-581X
COBISS.SI-ID:529824537 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0103-2022
Name:Tehnologije znanja

Funder:EC - European Commission
Project number:101000339
Name:An EU-wide farm network demonstrating and promoting cost-effective IPM strategies
Acronym:IPMWORKS

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:26.03.2026
Applies to:VoR

Secondary language

Language:Slovenian
Title:Drivers and barriers to DSS adoption in European crop protection: insights from a machine learning analysis of farmer and advisor surveys
Keywords:z umetno inteligenco podprta analiza, uporaba orodij za podporo odločanju, vprašalnik, težave pri uporabi


Back