ArticleAgricultural systems2017
Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.
Article in Agricultural systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Challenges and Solution Directions for the Integration of Smart Information Systems in the Agri-Food Sector.Sensors (Basel, Switzerland) · 2025Pooled it
- Lessons in implementing open farm data for diverse stakeholders at Harper Adams Future Farm.Animal frontiers : the review magazine of animal agriculture · 2026Article
- Harnessing knowledge management to transform agricultural development through innovation and sustainability.Scientific reports · 2026Article
- Can artificial intelligence applications improve food supply capacity? Evidence from 296 Chinese cities.Frontiers in nutrition · 2026Article
- The Ruminant Farm Systems (RuFaS) model is a platform to support future research and actions for sustainable dairy farming.JDS communications · 2025Review
- Maize yield estimation in Northeast China's black soil region using a deep learning model with attention mechanism and remote sensing.Scientific reports · 2025Article
- Article
- Digital documentation of individual treatment data and its relation to veterinary slaughter lesions in pigs.Archives animal breeding · 2025Article
- Investigating the impact of the internet on managing green financial innovation and improving agricultural conditions in water-scarce Asian regions using ANN modeling.Scientific reports · 2024Article
- Using Dynamic Laser Speckle Imaging for Plant Breeding: A Case Study of Water Stress in Sunflowers.Sensors (Basel, Switzerland) · 2024Article
- Exploring the application of ICTs in decarbonizing the agriculture supply chain: A literature review and research agenda.Heliyon · 2024Article
- Digital documentation of treatment data and their relation to breed and performance parameters of sows.Archives animal breeding · 2024Article
- Digital twins and the future of precision mental health.Frontiers in psychiatry · 2023Article
- Barriers and opportunities of soil knowledge to address soil challenges: Stakeholders' perspectives across Europe.Journal of environmental management · 2023Article
- Scientific modelling can be accessible, interoperable and user friendly: A case study for pasture and livestock modelling in Spain.PloS one · 2023Article
- ASAS-NANP symposium: mathematical modeling in animal nutrition: the progression of data analytics and artificial intelligence in support of sustainable development in animal science.Journal of animal science · 2022Article
- Resources for image-based high-throughput phenotyping in crops and data sharing challenges.Plant physiology · 2021Article
- Shared Socio-economic Pathways for European agriculture and food systems: The Eur-Agri-SSPs.Global environmental change : human and policy dimensions · 2020Article
- Farmers' preferences for high-input agriculture supported by site-specific extension services: Evidence from a choice experiment in Nigeria.Agricultural systems · 2019Article
- Performance, farmer perception, and the routinisation (RO) moderation on ERP post-implementation.Heliyon · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.