Are Decision Support Tools Oriented Toward Improving On-Farm Sustainability? A Systematic Review

Decelerating climate change requires a shift away from conventional production practices across industries, including agriculture, to meet the United Nations Sustainable Development Goals (SDGs). Agricultural sustainability has therefore gained growing interest, and growing evidence suggests that frameworks and computer-based decision-making support, known as Decision Support Tools (DSTs), can enhance sustainability. This study analyses the functionalities and methodologies of DSTs designed to assess sustainability at the farm level. A systematic literature review was conducted following the PRISMA methodology to identify (1) key characteristics of operational DSTs, (2) SDG-related areas requiring enhanced decision-making support, and (3) the extent to which DST implementation improves sustainability. Results indicate that while DST applications frequently present expected outputs, recommendations, improved management scenarios, or identify vulnerable areas, there is a notable lack of studies evaluating how these tools translate information into practical, long-term actions for sustainable development at the farm scale. The TOMCAST model was the only DST reporting direct evidence of efficacy through reduced disease incidence and yield losses. Most reviewed DSTs target resource-use optimisation (SDG 12), whereas tools assessing biodiversity (SDG 15) and social impacts remain scarce. By identifying methodological gaps and underrepresented sustainability dimensions, this review provides both a diagnosis of current limitations and a roadmap for developing more implementation-oriented, SDG-aligned tools. Future research should adopt participatory approaches and assess the short- and long-term impacts, accessibility, operability, and costs associated with DST implementation and maintenance, while expanding the integration of Agriculture 4.0 and 5.0 technologies beyond remote sensing. • More focus is needed on DSTs' impact in turning data into farm-sustainable actions. • DSTs to assess biodiversity (SDG 15) and social impact are still scarce. • More solutions are needed to balance DSTs' quality, access, and maintenance costs. • Decision-makers’ perspectives should be considered to assess DSTs’ operability.

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Journal
Environmental and Sustainability Indicators
Published
2026-03-01
DOI
https://doi.org/10.1016/j.indic.2026.101236
Primary Topic
Smart Agriculture and AI
Type
article
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article

Are Decision Support Tools Oriented Toward Improving On-Farm Sustainability? A Systematic Review

Sara Marcelino, Marta Soares Marcelino, Arminda do Paço, Pedro Dinis Gaspar et al.
Environmental and Sustainability Indicators
Smart Agriculture and AI
article

Are Decision Support Tools Oriented Toward Improving On-Farm Sustainability? A Systematic Review

Sara Marcelino, Marta Soares Marcelino, Arminda do Paço, Pedro Dinis Gaspar, Tânia M. Lima
article en

Abstract

Decelerating climate change requires a shift away from conventional production practices across industries, including agriculture, to meet the United Nations Sustainable Development Goals (SDGs). Agricultural sustainability has therefore gained growing interest, and growing evidence suggests that frameworks and computer-based decision-making support, known as Decision Support Tools (DSTs), can enhance sustainability. This study analyses the functionalities and methodologies of DSTs designed to assess sustainability at the farm level. A systematic literature review was conducted following the PRISMA methodology to identify (1) key characteristics of operational DSTs, (2) SDG-related areas requiring enhanced decision-making support, and (3) the extent to which DST implementation improves sustainability. Results indicate that while DST applications frequently present expected outputs, recommendations, improved management scenarios, or identify vulnerable areas, there is a notable lack of studies evaluating how these tools translate information into practical, long-term actions for sustainable development at the farm scale. The TOMCAST model was the only DST reporting direct evidence of efficacy through reduced disease incidence and yield losses. Most reviewed DSTs target resource-use optimisation (SDG 12), whereas tools assessing biodiversity (SDG 15) and social impacts remain scarce. By identifying methodological gaps and underrepresented sustainability dimensions, this review provides both a diagnosis of current limitations and a roadmap for developing more implementation-oriented, SDG-aligned tools. Future research should adopt participatory approaches and assess the short- and long-term impacts, accessibility, operability, and costs associated with DST implementation and maintenance, while expanding the integration of Agriculture 4.0 and 5.0 technologies beyond remote sensing. • More focus is needed on DSTs' impact in turning data into farm-sustainable actions. • DSTs to assess biodiversity (SDG 15) and social impact are still scarce. • More solutions are needed to balance DSTs' quality, access, and maintenance costs. • Decision-makers’ perspectives should be considered to assess DSTs’ operability.

Environmental and Sustainability Indicators
University of Beira Interior (PT)
Zero hunger
Openalex Percentile: Top 4%
Smart Agriculture and AI
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