ReviewJournal of agricultural and food chemistry2024
Digital Twins in Agriculture: Orchestration and Applications.
Review in Journal of agricultural and food chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Deep Learning for Deciphering the Plant Cis-Regulatory Code.Plants (Basel, Switzerland) · 2026Review
- Integrating deep learning and field validation into a decision support system for Northern Corn Leaf Blight management in maize.BMC plant biology · 2026Article
- Digital twins for plant-microbe interactions: Gap finding and filling.Plant communications · 2026Article
- AI-driven fungicide design: From target identification to field application.Plant communications · 2026Review
- Artificial intelligence for animal science: from applications to integrated knowledge systems.Animal frontiers : the review magazine of animal agriculture · 2026Article
- Digital and Green Technological Drivers of Transformation in the Agri-Food Sector.Foods (Basel, Switzerland) · 2026Review
- AI-driven multiscale virtual plant cell modeling: from molecular mechanisms to tissue functions.Planta · 2026Review
- Digital decision support integrated with diagnostics and precision fungicide application for Southern Corn Leaf Blight in maize.Scientific reports · 2026Article
- A digital twin-driven deep learning framework for online quality inspection in tobacco transplanting.Frontiers in plant science · 2026Article
- Animal digital twins: systems architecture for climate-smart protein production.npj veterinary sciences · 2026Review
- From machine learning to digital twin integration for livestock production and research.Frontiers in veterinary science · 2026Review
- Video-based cattle behaviour detection for digital twin development in precision dairy systems.npj veterinary sciences · 2026Article
- From Traditional Machine Learning to Fine-Tuning Large Language Models: A Review for Sensors-Based Soil Moisture Forecasting.Sensors (Basel, Switzerland) · 2025Review
- Digital twin-based applications in crop monitoring.Heliyon · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.
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.