Methane emissions from ruminant livestock is a major source of greenhouse gases, accounting for approximately two-thirds of anthropogenic methane sources. Methane yield from ruminants (MY; g/kg DM intake) is known to be positively correlated with the mean retention time (MRT) of rumen contents, and MRT in the rumen is largely controlled by the contractile forces of the reticulo-rumen and the relaxing of the reticulo-omasal orifice. The discovery of immuno-reactive endocrine and neural cells distributed throughout the epithelia and glands of the digestive tract suggest that the endocrine system may play a key role in regulating digesta MRT and MY in ruminants. The thyroid hormone triiodothyronine (T₃), known to influence digesta kinetics, was used to initiate our studies to modify digesta MRT and determine the impact that digesta MRT has on the production of enteric methane and MY. To investigate the influence digesta kinetics had on ruminant MY, it was necessary to develop a kinetic model capable of accurately estimating the rate of flow of digesta through the digestive tract. An extensive review of existing published mathematical models for ruminant digesta kinetics was conducted and a model developed by Aharoni et al. (1999) for the estimation of cattle digesta kinetics was selected and modified to produce a new multicompartmental double-marker digestive tract model for use in sheep.

Monitoring and early detection of leaf rust caused by fungus 'Naohidemyces vaccinii' in plants is critical for sustainable production of blueberries in Australia. In this study, the main aim was to use hyperspectral remote sensing as a tool to detect leaf rust at an early stage in blueberries. Reflectance was measured in the wavelength range from 350 to 2500nm using a handheld hyperspectral spectro-radiometer. Differences in spectral reflectance were seen at a number of wavelengths in the visible, NIR and SWIR regions for the Sharpblue variety under field conditions. In glasshouse conditions the OB1 and Sharpblue varieties showed differences between inoculated and uninoculated plants in NIR and SWIR regions. The NIR region showed significant spectral difference between the three varieties of blueberry. The results indicate the possibility to detect differences in healthy and leaf rust infected blueberry plants at an early stage of the diseases using hyperspectral remote sensing techniques.