Simulating maize/bean polycultures using functional-structural plant modelling

Rutjens, R. J. L. (2024) Simulating maize/bean polycultures using functional-structural plant modelling. PhD thesis, University of Nottingham.

[img]
Preview
PDF (Corrected version) (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (32MB) | Preview

Abstract

Climate change, a growing global population and soil degradation put significant

stress on food production and threaten food security, both on a global scale and

in individual agricultural communities. This necessitates studies that explore sustainable

agricultural intensification. Traditional farming systems have received

increased attention, as aspects of these systems (such as niche complementarity)

might provide sustainable solutions. This work centers around the three sisters,

a polyculture of maize (Zea mays), bean (Phaseolus vulgaris) and squash (Cucurbita

spp.), and the milpa, a complex Maya polyculture centered around maize

and bean. Building on an existing functional-structural plant (FSP) model for

maize, a novel FSP model for common bean is developed (in the XL language, on

the GroIMP platform), encompassing twining behaviour and physical plant-plant

interactions. This allows us to simulate maize/bean polycultures, where common

bean climbs upwards around the maize stalk. As the model contains many input

parameters, of which some are difficult or costly to parameterise, a global sensitivity

analysis (GSA) is paramount for identifying (un)important parameters in

the model. This decreases dimensionality of the large model parameter space.

Efforts can then be concentrated on accurately estimating the most important

input parameters. GSA is therefore performed on monocultures of maize and

common bean (growing on poles). To this end, the popular Elementary Effects

GSA method is adapted to make it suitable for models with dimensional inputs,

inputs taking values on arbitrary intervals or discrete inputs. Our results show

the benefit of performing GSA on plant models: for both maize and bean, less

than 30% of input parameters where classified as important for most model outputs.

In addition, performing GSA on plant models leads to new insights about

both the model and the plant developmental processes it describes. The hope is

that this work will inspire more plant modellers to routinely incorporate sensitivity

analysis in their research. Subsequently, the model for maize and bean is

used to assess architectural facilitation in light capture in maize/bean polycultures.

Simulation results agree with experimental observations in the literature

of overyielding in polycultures including maize and climbing bean. This indicates

that aboveground processes (also) play an important role in the phenomenon

of overperforming. In addition, it confirms that such agricultural systems may

play a role in sustainable agricultural intensification. The maize/bean model presented

in this work is one of the first examples of an aboveground FSP model of

a polyculture with complex physical plant-plant interaction. Our results suggest

that FSP modelling could be a valuable tool to investigate such agricultural systems.

In this work, we have shown that it is possible to model maize/bean crop

mixtures, making an aboveground model of the three sisters only a small step

away.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Owen, M. R.
Band, L. R.
Jones, M. D.
Keywords: FSPM, functional-structural plant model, sensitivity analysis, elementary effects, maize/bean polyculture
Subjects: Q Science > QA Mathematics
S Agriculture > S Agriculture (General)
Faculties/Schools: UK Campuses > Faculty of Science > School of Mathematical Sciences
Related URLs:
URLURL Type
https://github.com/pmxrr3/EE_theory_2023Dataset
https://github.com/pmxrr3/EE_apply_2023Dataset
https://github.com/pmxrr3/maizebeanpolyculture_2023Dataset
Item ID: 77011
Depositing User: Rutjens, Rik
Date Deposited: 22 Mar 2024 09:40
Last Modified: 22 Mar 2024 09:40
URI: https://eprints.nottingham.ac.uk/id/eprint/77011

Actions (Archive Staff Only)

Edit View Edit View