A Bayesian Model of Pasture Curing

Curing percentage (the percentage of dead material in the sward) is a necessary component of fire behaviour modelling and subsequent fire danger ratings in grasslands. Current methods of estimating curing have limitations. Curing is controlled by leaf turnover in grasses but individual leaf turnover rates of themselves do not give estimates of curing. Bayesian modelling provides the potential to incorporate leaf turnover rates representing the entire life cycle of each leaf into a standalone model of curing from which statistical summaries can be generated and used in field models. In this study, curing percentage was estimated over thermal time for four common C3 grasses, and tested against field data

3D Scanning System for Automatic High-Resolution Plant Phenotyping

Thin leaves, fine stems, self-occlusion, non-rigid and slowly changing structures make plants difficult for three-dimensional (3D) scanning and reconstruction -- two critical steps in automated visual phenotyping. Many current solutions such as laser scanning, structured light, and multiview stereo can struggle to acquire usable 3D models because of limitations in scanning resolution and calibration accuracy. In response, we have developed a fast, low-cost, 3D scanning platform to image plants on a rotating stage with two tilting DSLR cameras centred on the plant. This uses new methods of camera calibration and background removal to achieve high-accuracy 3D reconstruction. We assessed the system's accuracy using a 3D visual hull reconstruction algorithm applied on 2 plastic models of dicotyledonous plants, 2 sorghum plants and 2 wheat plants across different sets of tilt angles. Scan times ranged from 3 minutes (to capture 72 images using 2 tilt angles), to 30 minutes (to capture 360 images using 10 tilt angles). The leaf lengths, widths, areas and perimeters of the plastic models were measured manually and compared to measurements from the scanning system: results were within 3-4% of each other. The 3D reconstructions obtained with the scanning system show excellent geometric agreement with all six plant specimens, even plants with thin leaves and fine stems.Comment: 8 papes, DICTA 201

Three Dimensional (3D) Reconstruction of Subterranean Clover

Three dimensional (3D) plant reconstructions, extended to four dimensions with the use of time series and accompanied by visual modelling, is being used for a number of purposes including the estimation of biovolume and as the basis for functional structural plant modelling (FSPM). This has been successfully applied to crop species such as cotton (Paproki et al. 2012). Measuring the growth pattern and arrangement of a pasture sward is a difficult task but can be used as an indirect measure of other variables of interest, such as growth rate, light interception, nutritional quality, herbivore intake, etc. (Laca and Lemaire 2000). Digital representation of individual plants in three dimensions is one way to determine sward structure. The High Resolution Plant Phenomics Centre (HRPPC) has developed PlantScan™ which combines robotics, image analysis and computing advances, to accelerate and automate the measurement of plant growth characteristics and allow discrimination of differences between individual plants within species. Image silhouettes and LiDAR (Light Detection And Ranging) are used and combined to digitise plant architecture in three dimensions with a high level of detail. Colour information, extracted from multispectral sensors, and thermal imaging from infra-red (IR) cameras are then overlaid on these 3D plant representations, thus providing a tool to link plant structure to plant function. Successful reconstructions using data collected by PlantScan™ in controlled conditions, have been conducted for a range of grasses such as wheat (Triticum aestivum), rice (Oryza sativa), corn (Zea mays) and broadleaf species such as canola (Brassica napus), cotton (Gossypium hirsutum) and tobacco (Nicotiana tabacum). This suggests that modelling the sward structure of grass and legume pasture species should be equally achievable. This study explores the use of PlantScanTM to reconstruct 3D images of the important and common pasture legume, subterranean clover (Trifolium subterraneum) with a view to analysing their 3D structure in-silico

Bringing out the gimp: fashioning the SM imaginary

The intention of this article is to investigate the cultural power associated with the gimp and the gimp mask. The gimp is a clothed or costumed SM body, frequently a submissive that often wears a leather or rubber costume that covers and effectuates the entire body including the face. The gimp is also a representation of SM that circulates throughout fashion and film and other forms of popular culture. Since the gimp’s first outing and naming in the film Pulp Fiction it has become the byword for the head-to-toe leather SM look that has been appropriated by a number of designers as way of exploring and exploiting the relationship between fashion, fetishism, and transgression. As a counterpoint to the popular image of SM in fashion and film, this article also explores how the artists Catherine Opie and Robert Mapplethorpe have represented the gimp, not as an index of horror or transgressive style rather as an affirmative image of their own SM communities that, while still intended to shock, is an defiant attempt to rescue or reclaim the gimp from its negative associations

Leaf Growth and Senescence Rates in Brown-Back Wallaby Grass, \u3cem\u3eRytidosperma duttonianum\u3c/em\u3e

Knowledge of leaf turnover in grasses is necessary to model curing (the accumulation of dead material in the sward), which is not well represented in current pasture growth models, nor for many Australian native species. Leaf turnover begins with the appearance of successive leaves, which elongate until typically, a leaf ligule develops to indicate a mature, fully expanded length. Green leaf life span extends from appearance to the beginning of senescence, which ultimately leads to death (Fig. 1). Here, the individual rates of leaf growth and senescence for the Australian native brown-back wallaby grass, Rytidosperma duttonianum (Cashmore) Connor & Edgar, over the whole life cycle, are reported

A Plant-Physiology Approach to a Fire-y Problem

As vegetation dies, it dries and becomes more flammable. Fire agencies require accurate and timely assessments of curing (the percentage of dead material in the sward) to model grass fire behaviour and calculate fire danger ratings (Cheney and Sullivan 2008). Visual observation is commonplace and the more objective use of the Levy Rod is recommended, although both have drawbacks (Anderson et al. 2011). There is great potential for pasture growth models to provide curing estimates to assist with the management of wild grass fires (Gill et al. 2010). This PhD project focused on plant physiological characters to populate models that could be used to predict curing assessments for fire management purposes

Dataset for 'A highly active mineral-based ice nucleating agent supports in situ cell cryopreservation in a high throughput format'

Cryopreservation of biological matter in microlitre scale volumes of liquid would be useful for a range of applications. At present, it is challenging because small volumes of water tend to supercool, and deep supercooling is known to lead to poor post thaw cell viability. Here we show that a mineral ice nucleator can almost eliminate supercooling in 100 microlitre liquid volumes during cryopreservation. This strategy of eliminating supercooling greatly enhances cell viability relative to cryopreservation protocols with uncontrolled ice nucleation. Using infrared thermography, we demonstrate a direct relationship between extent of supercooling and post-thaw cell viability. Using a mineral nucleator delivery system we open the door to the routine cryopreservation of mammalian cells in multiwell plates for applications such as high throughput toxicology testing of pharmaceutical products and regenerative medicine

Growth Measurement of Arabidopsis in 2.5D from a High Throughput Phenotyping Platform

The last few years have seen an increasing interest in the development of high throughput phenotyping platforms (HTP) that allow the automated measurement of plant growth and structure. These platforms have utilised various imaging technologies, including fluorescence imaging, thermal imaging, and visible imaging. Since plants are structurally complex and inherently three-dimensional (3D), 3D imaging and reconstruction approaches have distinct advantages over 2D imaging when it comes to quantifying structural information (such as leaf angle distribution, leaf area etc.). High throughput phenotyping platforms, when combined with 3D image analysis, enable researchers to investigate complex functional traits related to plant structure, including responses to external and internal signals or perturbations. Moreover, image-based reconstruction techniques are able to produce complex structural models of both large and small individual plants, which retain colour information and are topologically coherent. In this paper, we present a computational workflow for analysing the growth of Arabidopsis thaliana rosettes over time using stereo reconstruction. Stereo reconstruction for plant phenotyping generally includes data collection and point cloud generation. In our approach, we not only use stereo image pairs to generate point clouds of the plants but also reconstruct mesh surfaces for further analysis. By applying a semi-global matching algorithm, 2.5D point clouds of Arabidopsis growing in trays with multiple plants were generated. Point clouds were then filtered and segmented in order to isolate single plants using clustering methods. A variety of surface reconstruction methods were then used to generate meshes from the point clouds. These meshes were analysed to quantify the plant dimensions and surface area in three dimensions. The segmentation was stable over time and was used to generate a time series for the growth of the individual plants over time. The advantages of such a stereo reconstruction system are: i) the system is able to construct realistic point clouds and meshes of the scene, ii) the processing pipeline is computationally efficient, iii) it allows stereo reconstruction and segmentation of individual plants in trays of 20 plants each for high throughput analysis. The overall approach proved useful in quantifying morphometric parameters in 3D for a set of Arabidopsis accessions and relating plant structure to plant function