Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Typical Model Studies01:30

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A mathematical perspective on hypothesis-driven model construction: A case study in pea.

Mathematical biosciences·2026
Same author

Plant Root Architectural Traits Mediate a Trade-Off Between Suppression and Tolerance of Competitors.

Ecology and evolution·2026
Same author

A simple plant-mycorrhizal fungal resource trade co-evolution model explains mutualism stability, extinction and transitory parasitism via fitness feedback.

The New phytologist·2025
Same author

Morphological Composition Influences Redundancy, Complementarity and Ecological Relevance of Habitat Complexity Metrics in Simulated Coral Communities.

Ecology and evolution·2025
Same author

Optimal control of multiple myeloma assuming drug resistance and off-target effects.

PLoS computational biology·2025
Same author

Could Canola Canopy Architecture Affect Pathogen Infection by Impacting Flower Accumulation on Branches?

Phytopathology·2025

Related Experiment Video

Updated: Jul 22, 2026

A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models.

Michael Renton1, Jim Hanan, Kevin Burrage

  • 1UMR BEPC, INRA, Montpellier, France.

The New Phytologist
|May 5, 2005
PubMed
Summary

This study introduces canonical modelling for plant function, offering a flexible intermediate approach. It simulates plant responses without complex physiological details, bridging the gap between empirical and mechanistic models.

More Related Videos

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Related Experiment Videos

Last Updated: Jul 22, 2026

A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Area of Science:

  • Plant science
  • Computational biology
  • Mathematical modelling

Background:

  • Functional-structural plant models are often complex and computationally expensive.
  • Purely empirical models lack the ability to simulate plant adaptability.
  • A need exists for intermediate modelling approaches balancing detail and complexity.

Purpose of the Study:

  • To present an intermediate approach for modelling plant function.
  • To simulate plant responses without requiring detailed physiological knowledge.
  • To integrate canonical modelling with L-systems for functional-structural plant models.

Main Methods:

  • Utilized a 'canonical' modelling approach for plant function.
  • Employed compartment models with standard mathematical flux functions.
  • Integrated canonical modelling with L-systems for plant structure representation.

Main Results:

  • Demonstrated the creation of functional-structural plant models using canonical modelling and L-systems.
  • Showcased the ability to represent plant function in descriptive or mechanistic ways.
  • Validated canonical modelling as a flexible and relatively simple approach.

Conclusions:

  • Canonical modelling offers a useful, flexible, and simple method for intermediate-level plant function modelling.
  • This approach effectively simulates plant responses without deep physiological detail.
  • The integration with L-systems facilitates the development of advanced functional-structural plant models.