In this paper we review the provision of the laser diagnostics that are installed on the Vulcan laser facility. We will present strategies for dealing with the energy of high energy systems and with ways of handling the beam sizes of the lasers. We present data captured during typical experimental campaigns to demonstrate their reliability and variation in shot to shot values.

An energy measurement system in a Large-aperture high power laser experiment platform is introduced. The entire measurement system includes five calorimeters, which carry out the energy measurement of the fundamental frequency before the frequency conversion unit, remaining fundamental frequency, remain second-harmonics, third harmonics, as well as the energy balance measurement after the frequency conversion unit. Combinational indirect calibration and direct calibration are employed to calibrate the sampling coefficients of the calorimeters. The analysis of the data showed that, regarding the energy balance coefficients, combinational calibration approach gives a higher precision, and leads to an energy balance with 1%; and regarding the energy sampling coefficients for the various wavelengths after the frequency conversion, the results from direct and combinational calibration are consistent. The uncertainties for all energy sampling coefficients are within 3%, which guarantees the reliability of the energy measurement for the laser facility.

The objectives of the present study were to examine relationships between methane (CH4) output and animal and dietary factors, and to use these relationships to develop prediction equations for CH4 emission from beef cattle. The dataset was obtained from 108 growing-to-finishing beef steers in five studies and CH4 production and energy metabolism data were measured in indirect respiration calorimeter chambers. Dietary forage proportion ranged from 29.5% to 100% (dry matter (DM) basis) and forages included grass silage, fresh grass, dried grass and fodder beet. Linear and multiple regression techniques were used to examine relationships between CH4 emission and animal and dietary variables, with the effects of experiment or forage type removed. Total CH4 emission was positively related to live weight (LW), feeding level and intake of feed (DM and organic matter) and energy (gross energy (GE), digestible energy (DE) and metabolisable energy (ME)) (P < 0.001), while CH4/DM intake (DMI) was negatively related to energy digestibility and ME/GE (P < 0.05 or less). Using LW alone to predict CH4 emission produced a poor relationship when compared to DMI and GE intake (GEI) (R2 = 0.26 v. 0.68 and 0.70 respectively). Adding feeding level, dietary NDF concentration and CP/ME or feeding level, energy digestibility and ME/GE to support LW resulted in a R2 of 0.66 or 0.84. The high R2 (0.84) was similar to that obtained using DMI or GEI together with energy digestibility and ME/GE as predictors. Further inclusion of dietary forage proportion and ADF and NDF concentration to the multiple relationships using GEI as the primary predictor resulted in a R2 of 0.87. These equations were evaluated through internal validation, by developing a range of similar new equations from two-thirds of the present data and then validating these new equations with the remaining one-third of data. The validation indicated that addition of energy digestibility and ME/GE to support LW with feeding level, DMI and GEI considerably increased the prediction accuracy. It is concluded that CH4 emission of beef steers can be accurately predicted from LW plus feeding level, DMI or GEI together with energy digestibility and ME/GE. The dataset was also used to validate a range of prediction equations for CH4 production of cattle published elsewhere.