Improving the efficiency of energy utilization in cattle

The efficiency of energy utilisation in cattle is a determinant of the profitability of milk and beef production, as well as their environmental impact. At an animal level, meat and milk production by ruminants is less efficient than pig and poultry production, in part due to lower digestibility of forages compared with grains. However, when compared on the basis of human-edible inputs, the ruminant has a clear efficiency advantage. There has been recent interest in feed conversion efficiency (FCE) in dairy cattle and residual feed intake, an indicator of FCE, in beef cattle. Variation between animals in FCE may have genetic components, allowing selection for animals with greater efficiency and reduced environmental impact. A major source of variation in FCE is feed digestibility, and thus approaches that improve digestibility should improve FCE if rumen function is not disrupted. Methane represents a substantial loss of digestible energy from rations. Major determinants of methane emission are the amount of feed consumed and the proportions of forage and concentrates fed. In addition, feeding fat has long been known to reduce methane emission. A myriad of other supplements and additives are currently being investigated as mitigators of methane emission, but in many cases compounds effective in sheep are ineffective in lactating dairy cows. Ultimately, the adoption of ‘best practice’ in diet formulation and management may be the most effective option for reducing methane. In assessing the efficiency of energy use for milk and meat production by cattle, and their environmental impact, it is imperative that comparisons be made at a systems level, and that the wider social and economic implications of mitigation policy are considered.

The trading profitability of forecasts of the gilt–equity yield ratio

Research has highlighted the usefulness of the Gilt–Equity Yield Ratio (GEYR) as a predictor of UK stock returns. This paper extends recent studies by endogenising the threshold at which the GEYR switches from being low to being high or vice versa, thus improving the arbitrary nature of the determination of the threshold employed in the extant literature. It is observed that a decision rule for investing in equities or bonds, based on the forecasts from a regime switching model, yields higher average returns with lower variability than a static portfolio containing any combinations of equities and bonds. A closer inspection of the results reveals that the model has power to forecast when investors should steer clear of equities, although the trading profits generated are insufficient to outweigh the associated transaction costs.

Improving computer interaction for older people - studying mouse clicks

Interactions using a standard computer mouse can be particularly difficult for novice and older adult users. Tasks that involve positioning the mouse over a target and double-clicking to initiate some action can be a real challenge for many users. Hence, this paper describes a study that investigates the double-click interactions of older and younger adults and presents data that can help inform the development of methods of assistance. Twelve older adults (mean age = 63.9 years) and 12 younger adults (mean age = 20.8 years) performed click and double-click target selections with a computer mouse. Initial results show that older users make approximately twice as many errors as younger users when attempting double-clicks. For both age groups, the largest proportion of errors was due to difficulties with keeping the cursor steady between button presses. Compared with younger adults, older adults experienced more difficulties with performing two button presses within a required time interval. Understanding these interactions better is a step towards improving accessibility, and may provide some suggestions for future directions of research in this area.

Improving flood inundation models using remotely sensed data

The paper discusses the wide variety of ways in which remotely sensed data are being utilized in river flood inundation modeling. Model parameterization is being aided using airborne LiDAR data to provide topography of the floodplain for use as model bathymetry, and vegetation heights in the floodplain for use in estimating floodplain friction factors. Model calibration and validation are being aided by comparing the flood extent observed in SAR images with the extent predicted by the model. The recent extension of this to the observation of urban flooding using high resolution TerraSAR-X data is described. Possible future research directions are considered.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Improving participatory varietal selection processes: participatory varietal selection and the role of informal seed diffusion mechanisms for upland rice in Ghana

This paper considers the process of Participatory Varietal Selection (PVS) and presents approaches and ideas based on PVS activities conducted on upland rice throughout Ghana between 1997 and 2003. In particular the role of informal seed systems in PVS is investigated and implications for PVS design are identified. PVS programmes were conducted in two main agroecological zones, Forest and Savannah, with 1,578 and 1,143 mm of annual rainfall, respectively, and between 40 and 100 varieties tested at each site. In the Savannah zone IR12979-24-1 was officially released and in the Forest zone IDSA 85 was widely accepted by farmers. Two surveys were conducted in an area of the Forest zone to study mechanisms of spread. Here small amounts (1-2 kg) of seed of selected varieties had been given to 94 farmers. In 2002, 37% of 2,289 farmers in communities surveyed had already grown a PVS variety and had obtained seed via informal mechanisms from other farmers, i.e. through gift, exchange or purchase. A modified approach for PVS is presented which enables important issues identified in the paper to be accommodated. These issues include: utilising existing seed spread mechanisms; facilitating formal release of acceptable varieties; assessing post-harvest traits, and; the need for PVS to be an ongoing and sustainable process.

Farmers' attitudes towards techniques for improving oestrus detection in dairy herds in South West England

Unidentified heats contribute to declining fertility rates in English dairy herds. Several techniques have been advocated to improve heat detection rates. Despite demonstrable technical efficacy and cost-effectiveness, uptake is low. A study in South West England used the Theory of Reasoned Action (TORA) to explore dairy farmers' attitudes and beliefs towards heat detection techniques. Few farmers were convinced that following prescribed observation times, milk progesterone testing and using pedometers would fit their system or improve on their current heat detection practices. Perceived difficulty of using a technique was not a constraint on adoption. Without promotion that addresses identified barriers and drivers to adoption, little change in current practice can be expected. (c) 2006 Elsevier B.V. All rights reserved.