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

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

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

Data associated with 'Cryopreservation of primary cultures of mammalian somatic cells in 96-well plates benefits from control of ice nucleation'

Cryopreservation of mammalian cells has, to date, typically been conducted in cryovials, but there are applications where cryopreservation of primary cells in multiwell plates would be advantageous. However excessive supercooling in the small volumes of liquid in each well of the multiwell plates is inevitable without intervention and tends to result in high and variable cell mortality. We describe a technique for cryopreservation of adhered primary bovine granulosa cells in 96-well plates by controlled rate freezing using controlled nucleation. This dataset contains experimental data derived from granulosa cell culture cryopreservation experiments and measurements of ice nucleation temperature measurements observed within 96-well plates and other cryocontainer

The influence of women's fear, attitudes and beliefs of childbirth on mode and experience of birth

Background: Women's fears and attitudes to childbirth may influence the maternity care they receive and the outcomes of birth. This study aimed to develop profiles of women according to their attitudes regarding birth and their levels of childbirth related fear. The association of these profiles with mode and outcomes of birth was explored. Methods: Prospective longitudinal cohort design with self report questionnaires containing a set of attitudinal statements regarding birth (Birth Attitudes Profile Scale) and a fear of birth scale (FOBS). Pregnant women responded at 18-20 weeks gestation and two months after birth from a regional area of Sweden (n = 386) and a regional area of Australia (n = 123). Cluster analysis was used to identify a set of profiles. Odds ratios (95% CI) were calculated, comparing cluster membership for country of care, pregnancy characteristics, birth experience and outcomes. Results: Three clusters were identified - 'Self determiners' (clear attitudes about birth including seeing it as a natural process and no childbirth fear), 'Take it as it comes' (no fear of birth and low levels of agreement with any of the attitude statements) and 'Fearful' (afraid of birth, with concerns for the personal impact of birth including pain and control, safety concerns and low levels of agreement with attitudes relating to women's freedom of choice or birth as a natural process). At 18 - 20 weeks gestation, when compared to the 'Self determiners', women in the 'Fearful' cluster were more likely to: prefer a caesarean (OR = 3.3 CI: 1.6-6.8), hold less than positive feelings about being pregnant (OR = 3.6 CI: 1.4-9.0), report less than positive feelings about the approaching birth (OR = 7.2 CI: 4.4-12.0) and less than positive feelings about the first weeks with a newborn (OR = 2.0 CI 1.2-3.6). At two months post partum the 'Fearful' cluster had a greater likelihood of having had an elective caesarean (OR = 5.4 CI 2.1-14.2); they were more likely to have had an epidural if they laboured (OR = 1.9 CI 1.1-3.2) and to experience their labour pain as more intense than women in the other clusters. The 'Fearful' cluster were more likely to report a negative experience of birth (OR = 1.7 CI 1.02-2.9). The 'Take it as it comes' cluster had a higher likelihood of an elective caesarean (OR 3.0 CI 1.1-8.0). Conclusions: In this study three clusters of women were identified. Belonging to the 'Fearful' cluster had a negative effect on women's emotional health during pregnancy and increased the likelihood of a negative birth experience. Both women in the 'Take it as it comes' and the 'Fearful' cluster had higher odds of having an elective caesarean compared to women in the 'Self determiners'. Understanding women's attitudes and level of fear may help midwives and doctors to tailor their interactions with women