ReviewSensors (Basel, Switzerland)2022
Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Digital Twin Paradigm Applied to Soil Quality Assessment: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Regional Cultivation Forms ofJournal of fungi (Basel, Switzerland) · 2026Review
- Local-Global Aware Concept Bottleneck Models for Interpretable Image Classification.Sensors (Basel, Switzerland) · 2026Article
- A digital twin-driven deep learning framework for online quality inspection in tobacco transplanting.Frontiers in plant science · 2026Article
- Mechanisms and Applications of Gastrointestinal Microbiota-Metabolite Interactions in Ruminants: A Review.Microorganisms · 2025Review
- Microclimate-Controlled Smart Growth Cabinets for High-Throughput Plant Phenotyping.Sensors (Basel, Switzerland) · 2025Article
- DLCPD-25: A Large-Scale and Diverse Dataset for Crop Disease and Pest Recognition.Sensors (Basel, Switzerland) · 2025Article
- Development and Optimization of a Real-Time Monitoring System of Small-Scale Multi-Purpose Juice Extractor.Foods (Basel, Switzerland) · 2025Article
- AI-driven transformation in food manufacturing: a pathway to sustainable efficiency and quality assurance.Frontiers in nutrition · 2025Article
- Innovative food supply chain through spatial computing technologies: A review.Comprehensive reviews in food science and food safety · 2024Review
- Digital Twins in Agriculture: Orchestration and Applications.Journal of agricultural and food chemistry · 2024Review
- Digital Twins in Agriculture and Forestry: A Review.Sensors (Basel, Switzerland) · 2024Review
- Review
- An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture.Nature communications · 2024Article
- An Approach to Develop Digital Twins in Industry.Sensors (Basel, Switzerland) · 2024Article
- An integrated method for phenotypic analysis of wheat based on multi-view image sequences: from seedling to grain filling stages.Frontiers in plant science · 2024Article
- Sensors and Robotics for Digital Agriculture.Sensors (Basel, Switzerland) · 2023Article
- Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review.Sensors (Basel, Switzerland) · 2023Review
- Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems.Biomimetics (Basel, Switzerland) · 2023Review
- Toward Better Food Security Using Concepts from Industry 5.0.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
Indexed as
Identifiers
What OpenQuestion holds
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.