In vitro cumulative gas production techniques: History, methodological considerations and challenges

Methodology used to measure in vitro gas production is reviewed to determine impacts of sources of variation on resultant gas production profiles (GPP). Current methods include measurement of gas production at constant pressure (e.g., use of gas tight syringes), a system that is inexpensive, but may be less sensitive than others thereby affecting its suitability in some situations. Automated systems that measure gas production at constant volume allow pressure to accumulate in the bottle, which is recorded at different times to produce a GPP, and may result in sufficiently high pressure that solubility of evolved gases in the medium is affected, thereby resulting in a recorded volume of gas that is lower than that predicted from stoichiometric calculations. Several other methods measure gas production at constant pressure and volume with either pressure transducers or sensors, and these may be manual, semi-automated or fully automated in operation. In these systems, gas is released as pressure increases, and vented gas is recorded. Agitating the medium does not consistently produce more gas with automated systems, and little or no effect of agitation was observed with manual systems. The apparatus affects GPP, but mathematical manipulation may enable effects of apparatus to be removed. The amount of substrate affects the volume of gas produced, but not rate of gas production, provided there is sufficient buffering capacity in the medium. Systems that use a very small amount of substrate are prone to experimental error in sample weighing. Effect of sample preparation on GPP has been found to be important, but further research is required to determine the optimum preparation that mimics animal chewing. Inoculum is the single largest source of variation in measuring GPP, as rumen fluid is variable and sampling schedules, diets fed to donor animals and ratios of rumen fluid/medium must be selected such that microbial activity is sufficiently high that it does not affect rate and extent of fermentation. Species of donor animal may also cause differences in GPP. End point measures can be mathematically manipulated to account for species differences, but rates of fermentation are not related. Other sources of inocula that have been used include caecal fluid (primarily for investigating hindgut fermentation in monogastrics), effluent from simulated rumen fermentation (e.g., 'Rusitec', which was as variable as rumen fluid), faeces, and frozen or freeze-dried rumen fluid (which were both less active than fresh rumen fluid). Use of mixtures of cell-free enzymes, or pure cultures of bacteria, may be a way of increasing GPP reproducibility, while reducing reliance on surgically modified animals. However, more research is required to develop these inocula. A number of media have been developed which buffer the incubation and provide relevant micro-nutrients to the microorganisms. To date, little research has been completed on relationships between the composition of the medium and measured GPP. However, comparing GPP from media either rich in N or N-free, allows assessment of contributions of N containing compounds in the sample. (c) 2005 Published by Elsevier B.V.

Inter-laboratory variation of in vitro cumulative gas production profiles of feeds using manual and automated methods

A study was conducted to estimate variation among laboratories and between manual and automated techniques of measuring pressure on the resulting gas production profiles (GPP). Eight feeds (molassed sugarbeet feed, grass silage, maize silage, soyabean hulls, maize gluten feed, whole crop wheat silage, wheat, glucose) were milled to pass a I mm screen and sent to three laboratories (ADAS Nutritional Sciences Research Unit, UK; Institute of Grassland and Environmental Research (IGER), UK; Wageningen University, The Netherlands). Each laboratory measured GPP over 144 h using standardised procedures with manual pressure transducers (MPT) and automated pressure systems (APS). The APS at ADAS used a pressure transducer and bottles in a shaking water bath, while the APS at Wageningen and IGER used a pressure sensor and bottles held in a stationary rack. Apparent dry matter degradability (ADDM) was estimated at the end of the incubation. GPP were fitted to a modified Michaelis-Menten model assuming a single phase of gas production, and GPP were described in terms of the asymptotic volume of gas produced (A), the time to half A (B), the time of maximum gas production rate (t(RM) (gas)) and maximum gas production rate (R-M (gas)). There were effects (P<0.001) of substrate on all parameters. However, MPT produced more (P<0.001) gas, but with longer (P<0.001) B and t(RM gas) (P<0.05) and lower (P<0.001) R-M gas compared to APS. There was no difference between apparatus in ADDM estimates. Interactions occurred between substrate and apparatus, substrate and laboratory, and laboratory and apparatus. However, when mean values for MPT were regressed from the individual laboratories, relationships were good (i.e., adjusted R-2 = 0.827 or higher). Good relationships were also observed with APS, although they were weaker than for MPT (i.e., adjusted R-2 = 0.723 or higher). The relationships between mean MPT and mean APS data were also good (i.e., adjusted R 2 = 0. 844 or higher). Data suggest that, although laboratory and method of measuring pressure are sources of variation in GPP estimation, it should be possible using appropriate mathematical models to standardise data among laboratories so that data from one laboratory could be extrapolated to others. This would allow development of a database of GPP data from many diverse feeds. (c) 2005 Published by Elsevier B.V.