Developing Queensland 3D Tropical Fruits and Nuts modelling capabilities

Development of 3D functional structural plant models for macadamias and other tropical fruit and nuts.

3D modelling of mango fruit skin blush in the tree canopy

The fruit of certain mango cultivars (e.g., 'Honey Gold') can develop blush on their skin. Skin blush due to red pigmentation is from the accumulation of anthocyanins. Anthocyanin biosynthesis is related to environmental determinants, including light received by the fruit. It has been observed that mango skin blush varies with position in the tree canopy. However, little investigation into this spatial relationship has been conducted. The objective of this preliminary study was to describe a 'Honey Gold' mango tree by capturing its three-dimensional (3D) architecture. A light path tracing model QuasiMC was then used to predict light received by fruit. The use of this 3D model was to better understand the relationship between mango fruit skin blush and fruit position in the canopy. The digitised mango tree mimicked the real tree at a high level of detail. Observations on mango skin blush distribution supported the proposition that sunlight exposure is an absolute requirement for anthocyanin development. No blush development occurred on shaded skin. It was affirmed that 3D mapping could allow for virtual experiments. For example, for virtual canopy thinning (e.g., 'window pruning') to admit more sunlight with a view to improve fruit blush. Improvements to 3D modelling of mango skin blush could focus on increasing accuracy, e.g., measurement of leaf light reflectance and transmission and the inclusion of the effect shading by branches.

Estimation of light interception in research environments: A joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions

Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.