Simulating red:far red ratio in your model

The best method depends on your goal, need for accuracy, and computing allowance

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Light is an essential factor for crop growth and development in agricultural production. Plants absorb red wavelengths through photosynthetic pigments while far-red wavelengths are reflected and transmitted by the green leaves of neighboring plants. This decreases the red:far-red ratio within the canopy.

Plants are sensitive to red:far-red ratio – lower levels induce changes from the phenotypic to the molecular level, including plant height, leaf morphology, biomass, chloroplast ultrastructure, and photosynthetic characteristics. These effects allow the plant to capture more light energy which maximizes plant growth and fitness in crowded stands. Despite the important role that red:far-red ratio plays in plant development, there has been limited success in evaluating how it affects morphogenesis within a plant canopy because it is difficult to measure. The key to unlocking this mystery is the use of functional structural plant modelling to evaluate how various radiative transfer models influence red:far-red ratio simulation and the resulting leaf structure growth using computational models.

Arthur Couturier, graduate student at France’s National Research Institute for Agriculture, Food and Environment (INRAE), and colleagues recently published a paper in in silico Plants that presents new model-based methods for describing red:far-red ratio spatial and temporal variability. The authors evaluated different methods used in modelling light to determine which was most accurate.

The methods evaluated by the authors were:

  1. the light model approach,
  2. the radiative exchange method, and
  3. the scale considered to intercept the light rays.

β€œWe simulated the light model approach two ways,” explains Couturier. β€œThe turbid-medium method represents the canopy with an array of 3D cells. It then calculates the radiative transfer within each individual cell. This approach does not fully account for the effect of position and orientation of individual organs. The RIRI model used this approach. The radiosity method calculates the radiative transfer considering the geometry of each individual foliage element and requires significant computation time. The CANESTRA model used this approach.β€œ

The radiative exchange methods considered were without scattering (only direct interception of light considered) and with light scattering in all directions after it is intercepted by the phytoelements. While light scattering is representative of what occurs within the canopy, it is computationally intensive. Therefore, it is valuable to evaluate how much impact it has on morphogenesis.

Three scales for intercepting light rays were considered:

  1. The β€˜Organ’ scale was computed from the irradiance from the surface of the considered organ,
  2. the β€˜Face’ scale computed from the irradiance intercepted by the bottom horizontal surface of the voxel where the considered organ is, and
  3. the β€˜Voxel’ scale computed from the irradiance of a considered voxel using a turbid-medium approach.
Add visual representation of the three scales that were considered Two intercept light rays in the study. The first scale, CANESTRA organ, shows light rays intercepted by the triangles of a single leaf with petiole and internode. The second scale, CANESTRA face, shows light rays intercepted by the lower face of the voxel where the leaf is located. The third scale, RIRI voxel, shows rays intercepted by the voxel where the organ is localized.
The three scales considered to intercept the light rays in the study.

The authors then ran simulations using the five methods integrated into the existing Virtual GrassLand model to determine the growth of petioles and internodes. The study focused on two plants species with contrasting architecture – alfalfa which grows vertically and white clover which grows horizontally along the ground.

A flow chart with five approaches ending in five models. The first level is model. There are two models, RIRI and CANESTRA. From the RIRI model, the light model approach is turbid medium. The radiative exchange method is without scattering. The modeling scale is Voxel. The method is therefore called β€œRIRI Voxel without scattering.” From the CANESTRA Model, the light model approach is radiosity. There are two radiative exchange methods, with and without scattering. From without scattering, the scale is FACE or Organ. The method from FACE is called β€œCANESTRA Face without scattering” and the method from ORGAN is called β€œCANESTRA Organ without scattering.” From with scattering, the scale is FACE or Organ. The method from FACE is called β€œCANESTRA Face with scattering” and the method from ORGAN is called β€œCANESTRA Organ with scattering.”
The five methods to compute radiative transfer used in the paper.

The five methods produced varying mean red:far-red ratios experienced by the internodes and petioles within the canopy during the growing season. As previously mentioned, the ratio is difficult to measure and therefore it is difficult to determine which method produced the most realistic values. However, the early decrease in red:far-red ratio produced by the CANESTRA Organ methods indicate that they can detect the presence of neighboring plant organs in the early stages of development while the other three methods only show a decreased ratio later when leaves are present.

A graph with Day of year from 100 to 180 on the x-axis and Mean red:far-red ratio intercepted from 0 to 1.2 on the y axis. Values from RIRI and CANESTRA Face with and without scattering are plateaued around a mean value of 1 from days 120 to 140, and then decline. CANESTRA Organ with and without scattering mean values fall soon after day 12 and remain low until day 180.
The early decrease in red:far-red ratio produced by the CANESTRA Organ methods.

Interestingly, the inclusion of scattering did not affect red:far-red ratio interception for simulations performed with the CANESTRA Organ model but had a strong impact on simulations performed with CANESTRA Face model. Therefore, because the use of scattering has a high computational time cost, its use must be chosen according to the accuracy needs of the simulation in view of the small differences observed.

Plant morphogenesis expressed by the simulated petiole and internode length was sensitive to the type of radiation model, especially at an early stage of development. Alfalfa, which has a vertical habit and more self-shading than horizontally-growing clover, was more sensitive to red:far-red ratio variations.

Becausered:far-red ratio has such a large effect on plants, improving the framework used to represent it  is vital to modelling efforts to increase crop yields. This work showed that model choice must be made according to the needs of the focus of the research and availability of computational resources. The authors provide a summary table regarding the advantages and disadvantages of each of the five  models and their suggested use in relation to the research questions being raised.

READ THE ARTICLE:

Arthur Couturier, Elzbieta Frak, Quentin Rambaud, GaΓ«tan Louarn, Romain Barillot, Jean-Louis Durand, Abraham Escobar-GutiΓ©rrez, Didier Combes, How much do radiative transfer models influence red:far-red simulation and subsequent plant photomorphogenesis modelling? in silico Plants, 2022, diac013, https://doi.org/10.1093/insilicoplants/diac013

Rachel Shekar

Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial experience, including the founding of GCB Bioenergy and the management of Global Change Biology. Rachel has overseen the social media development that has been a major part of promotion of both journals.

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