ReviewPlant molecular biology2026
Quantitative research from the perspective of mathematical and physical crop science: a review of phenotyping, mechanics, and modeling.
Review in Plant molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Addressing global grand challenges, including food security, climate change, and resource scarcity, requires transcending the limitations of traditional crop science research. Traditional approaches often suffer from low-throughput, destructive nature, and qualitatively macroscopic analyses, hindering the in-depth exploration and precise manipulation of crop growth mechanisms necessary for modern agriculture. This review systematically synthesizes recent advancements and pinpoints critical bottlenecks in key areas of modern crop science research: high-throughput phenotyping, multiscale mechanics of crops, and numerical modeling of crop-environment interactions. Based on this synthesis, we propose and articulate a conceptual framework for the novel interdisciplinary field: “mathematical and physical crop science.” The framework establishes an integrated paradigm of “data-driven, mechanism-based, and system-predictive” research, structured as follows: (1) High-throughput phenotyping, coupled with artificial intelligence and machine learning-driven analysis, quantifies dynamic phenotypic traits emerging from genotype-by-environment interactions. (2) Multiscale mechanics of crops resolves the physical constraints governing crop structure and function across different scales. (3) Numerical modeling of crop-environment interactions simulates the dynamic interactions between crop physiological processes and environmental factors. The overarching goal is to integrate these historically disparate research domains, providing a unified theoretical foundation for the systematic understanding of crop physiological and developmental processes and informing sustainable agricultural practices.
Indexed as
Identifiers
42024187What Socratic 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 Socratic graph.