Grass Growth Modelling: to Increase Understanding and Aid Decision Making On-Farm

Key points Crop and grass growth models have been developed over the last 50 years, or so, but general appreciation of their benefits and potential has been recognised only relatively recently. The most popular application of grass growth models has traditionally been for knowledge understanding. There is growing awareness of the potential of models in decision support systems (DSS) applications to aid pasture management and grassland budgeting on dairy farms. Although some models have been developed for DSS, their widespread uptake in industry has been slow; challenges still exist which need to be addressed in order to improve their precision and user-friendliness

GrassCheck: Monitoring and Predicting Grass Production in Northern Ireland

Grass budgeting is a key management practice on dairy farms to balance grass supply on paddocks with grass demand by the grazing herd. Grass budgets must be pre-emptive to be effective. The uncertainty of grass production and the difficulty in quantifying both current and forecasted rates of growth hamper effective budgeting and paddock management. Grass growth rates are highly variable both in time and space. Therefore, they vary greatly between locations at any given time and also across the season at any given location. Figure 1 shows the pattern of growth rates recorded at the Agricultural Research Institute of Northern Ireland (ARINI) in the two seasons before this project. The GrassCheck project was established in Northern Ireland to quantify current rates of grass growth and grass quality and to predict growth rates for up to 2 weeks in advance. The project will run from 2004 until 2006. This paper outlines the project and reports on its findings after one year

Modelling Winter Grass Growth and Senescence

In temperate climates, because net grass growth in winter is low, most grass growth models deal with the main growing season (Mar-Oct in the N Hemisphere), with little emphasis on grass growth in winter (Nov-Feb). However, grass tissue turns over continuously (Hennessy et al., 2004) and the fate of herbage entering the winter is important in extended grazing season systems. This study aimed to model winter grass growth for the period 15 Oct 2001 to 28 Jan 2002 for a range of autumn closing dates (1 Sep, 20 Sep and 10 Oct) by modifying an existing model, so that the amount of green leaf could be predicted at intervals over the winter

Normal human breast xenografts activate N-nitrosodimethylamine: identification of potential target cells for an environmental nitrosamine.

Normal human breast tissue maintained as xenografts in female Balb/c (nu/nu) athymic mice is capable of metabolising N-nitrosodimethylamine (NDMA) to active intermediates that will react with DNA. Administration of NDMA to mice with slow-release implants of 17 beta-oestradiol which provide human physiological (luteal phase) circulating oestrogen levels and increase cell proliferation in the xenograft (Laidlaw et al., 1992), leads to an apparent increase in the extent of reaction with DNA compared to controls without oestrogen implants. In mice with oestrogen implants, measurements of the amounts of the promutagenic lesion, O6-methyl-2'-deoxyguanosine formed in DNA clearly indicated a dose related increase in the extent of reaction. Detection of O6-methyl-2'-deoxyguanosine using immunohistochemical procedures revealed that the nuclei of cells of the glandular epithelium, supportive tissue and adipose tissue, in decreasing order of prevalence, were positively stained for the presence of this DNA lesion. Epithelial cells, which are the putative target cells for carcinogenesis in the breast, are therefore prone to promutagenic damage as a result of exposure to an environmental nitrosamine

Development and validation of the Brazilian version of the Attitudes to Aging Questionnaire (AAQ): An example of merging classical psychometric theory and the Rasch measurement model

Aging has determined a demographic shift in the world, which is considered a major societal achievement, and a challenge. Aging is primarily a subjective experience, shaped by factors such as gender and culture. There is a lack of instruments to assess attitudes to aging adequately. In addition, there is no instrument developed or validated in developing region contexts, so that the particularities of ageing in these areas are not included in the measures available. This paper aims to develop and validate a reliable attitude to aging instrument by combining classical psychometric approach and Rasch analysis

On a Modification of the Boundary State Formalism in Off-shell String Theory

We examine the application of boundary states in computing amplitudes in off-shell open string theory. We find a straightforward generalization of boundary state which produces the correct matrix elements with on-shell closed string states.Comment: Latex, 10 pages, refs added, minor typos correcte

Application of a Novel Quantitative Tractography Based Analysis of Diffusion Tensor Imaging to Examine Fiber Bundle Length in Human Cerebral White Matter

This paper reviews basic methods and recent applications of length-based fiber bundle analysis of cerebral white matter using diffusion magnetic resonance imaging (dMRI). Diffusion weighted imaging (DWI) is a dMRI technique that uses the random motion of water to probe tissue microstructure in the brain. Diffusion tensor imaging (DTI) is an extension of DWI that measures the magnitude and direction of water diffusion in cerebral white matter, using either voxel-based scalar metrics or tractography-based analyses. More recently, quantitative tractography based on diffusion tensor imaging (qtDTI) technology has been developed to help quantify aggregate structural anatomical properties of white matter fiber bundles, including both scalar metrics of bundle diffusion and more complex morphometric properties, such as fiber bundle length (FBL). Unlike traditional scalar diffusion metrics, FBL reflects the direction and curvature of white matter pathways coursing through the brain and is sensitive to changes within the entire tractography model. In this paper, we discuss applications of this approach to date that have provided new insights into brain organization and function. We also discuss opportunities for improving the methodology through more complex anatomical models and potential areas of new application for qtDTI