S. López

Estimating the extent of degradation of ruminant feeds from a description of their gas production profiles observed in vitro: derivation of models and other mathematical considerations.

Equations to describe gas production profiles, obtained using manual or automated systems for in vitro fermentation of ruminant feeds, were derived from first principles by considering a simple three-pool scheme. The pools represented were the potentially degradable and undegradable feed fractions, and accumulated gases. The equations derived and investigated mathematically were the generalized Mitscherlich, generalized Michaelis-Menten, Gompertz, and logistic. They were obtained by allowing the fractional rate of degradation to vary with time. The equations permit the extent of ruminal degradation (hence the supply of microbial protein to the duodenum) to be evaluated, thus linking the gas production technique to animal production.

Propionate precursors and other metabolic intermediates as possible alternative electron acceptors to methanogenesis in ruminal fermentation in vitro

Fifteen potential precursors of propionate were tested for their ability to decrease CH4 production by ruminal fluid in vitro. Sodium acrylate and sodium fumarate produced the most consistent effects in batch cultures, with 50 % of the added precursors being fermented to propionate and CH4 production decreasing by between 8 and 17 %, respectively. Additives were more effective when added as free acids, but this also decreased the pH and may have inhibited fibre digestion. Changing the dietary substrate from predominantly grass hay to predominantly concentrate had no influence on the effectiveness of acrylate and fumarate. In an in vitro fermentor (the rumen simulating technique, Rusitec) with a grass hay-concentrate (50:50, w/w) diet as substrate, both compounds were again fermented to propionate (33 and 44 % conversion to propionate, respectively). However, fumarate appeared more effective as a H2 sink compound. It was calculated to capture 44 % of the H2 previously used for CH4 formation compared with a 22 % capture of H2 with acrylate. Fumarate also caused a stimulation in fibre digestion. Thus, sodium fumarate was the preferred propionate precursor for use as a feed ingredient to decrease CH4 emissions from ruminants.

Influence of sodium fumarate addition on rumen fermentation in vitro.

The influence of sodium fumarate on rumen fermentation was investigated in vitro using batch and semi-continuous cultures of mixed rumen micro-organisms taken from three sheep receiving a basal diet of hay, barley, molasses, fish meal and a mineral-vitamin supplement (500, 299.5, 100, 91 and 9.5 g/kg DM respectively). Batch cultures consisted of 10 ml strained rumen fluid in 40 ml anaerobic buffer containing 200 mg of the same feed given to the sheep. Sodium fumarate was added to achieve a final concentration of 0, 5 or 10 mmol/l, as a result of the addition of 0, 250 or 500 mumol, equivalent to 0, 200 and 400 g/kg feed. CH4 production at 24 h (360 mumol in the control cultures) fell (P < 0.05) by 18 and 22 mumol respectively (SED 7.5). Total gas production was increased by the addition of fumarate without significant accumulation of H2. Substantial increases in acetate production (92 and 194 mumol; SED 26.7, P < 0.01) were accompanied by increases in propionate formation (212 and 396 mumol; SED 13.0, P < 0.001). Longer-term effects of fumarate supplementation on ruminal fermentation and CH4 production were investigated using the rumen simulation technique (Rusitec). Eight vessels were given 20 g basal diet/d, and half of them received a supplement of fumarate (disodium salt) over a period of 19 d. The response to the daily addition of 6.25 mmol sodium fumarate was a decrease in CH4 production of 1.2 mmol (SED 0.39, P < 0.05), equivalent to the consumption of 4.8 mmol H2, and an increase in propionate production of 4.9 mmol (from 10.4 to 15.3 (SED 1.05) mmol/d, P < 0.01). The inhibition of CH4 production did not decline during the period of time that fumarate was added to the vessels. Thus, the decrease in CH4 corresponded well to the fraction of the fumarate that was converted to propionate. Fumarate had no significant (P > 0.05) effect on total bacterial numbers or on the number of methanogenic archaea, but numbers of cellulolytic bacteria were increased (8.8 v. 23.9 (SED 2.49) x 10(5) per ml, P < 0.01). Fumarate also increased DM digestibility of the basal diet after 48 h incubation (0.476 v. 0.508 (SED 0.0123), P < 0.05). Thus, it was concluded that sodium fumarate may be a useful dietary additive for ruminants, because it diverts some H2 from CH4 production and because it is able to stimulate proliferation of cellulolytic bacteria and digestion of fibre.

Effect of DL-malate on mixed ruminal microorganism fermentation using the rumen simulation technique (RUSITEC)

The objective of this study was to investigate the effects of DL-malate on the in vitro fermentation of a 50 : 50 forage : concentrate diet using the rumen simulation technique (RUSITEC) and to compare these effects with those induced by the addition of propionate. The RUSITEC system consisted of eight vessels: three of them received daily 5.62 mmol of DL-malate, three vessels received daily 5.62 mmol of propionate and two vessels received no additives (control). After an adaptation period of 11 days the main fermentation parameters were determined for five consecutive days. There were no significant differences between treatments either in pH or in the daily production of NH3‐N. Compared to control diet, the addition of DL-malate resulted in an increase (p < 0.05) of hemicellulose disappearance and a trend (p < 0.10) towards a greater disappearance of dry matter, organic matter and neutral detergent fibre. Differences between DLmalate and propionate in diet degradation were not significant. DL-malate treatment resulted in an increase (p < 0.01) of daily propionate production, and a decrease (p < 0.05) in the amount of both methane (mmol/g DM fermented) and L-lactate (mg/day). Compared to propionate, DL-malate produced an increase (p < 0.05) of acetate production and tended to produce a lower amount of propionate (p < 0.10). In conclusion, these results seem to indicate that DL-malate enhanced the in vitro fermentation by increasing production of propionate and digestibility of hemicellulose. # 1999 Published by Elsevier Science B.V. All rights reserved.

Influence of nitrogen source on the fermentation of fibre from barley straw and sugarbeet pulp by ruminal micro-organisms in vitro

Incubations were carried out with a batch culture system to study the effects of different N sources on the fermentation by ruminal micro-organisms from Merino sheep of two fibre substrates derived from feedstuffs that differed in their fermentation rate. The substrates were neutral-detergent fibre (NDF) from barley straw and sugarbeet pulp. N sources were ammonia (NH4Cl) and peptides (Trypticase). Three treatments were made by replacing ammonia-N with peptide-N at levels of 0 (AMMO), 33 (PEPLOW) and 66 % (PEPHIGH) of total N. There were no differences (P>0.05) between treatments in NDF degradation for both the barley straw and the sugarbeet pulp. Peptides increased (P<0.05) total volatile fatty acids daily production for both substrates, with greater values (P<0.001) for PEPHIGH than for PEPLOW for the sugarbeet pulp. The presence of peptides also increased (P<0.05) microbial N synthesis compared with AMMO, with PEPHIGH supporting more growth (P<0.001) than PEPLOW when the sugarbeet pulp NDF was fermented. The presence of peptides increased (P<0.01) the amount of solids-associated micro-organisms (SAM)-N for both the barley straw and the sugarbeet pulp fibres, values in the PEPHIGH treatment being higher (P<0.001) than those in PEPLOW. The proportion of SAM-N in the total microbial N was not affected (P>0.05) by the presence of peptides compared with the AMMO treatment, but values were greater for the PEPHIGH compared with the PEPLOW N source, reaching statistical significance (P<0.05) only for the sugarbeet pulp. For liquid-associated micro-organisms, the AMMO treatment resulted in the greatest (P<0.05) proportion of N derived from ammonia for both substrates, with a further decrease (P<0.01) for the PEPHIGH treatment compared with the PEPLOW for the sugarbeet pulp, indicating preferential uptake of peptides when they were available. Microbial growth efficiency (g microbial N/kg NDF degraded) was not affected (P>0.05) by N source. These results indicate that N forms other than ammonia are needed for maximal growth of fibre-digesting ruminal micro-organisms.

Linear models for determining digestibility

Dhanoa, M. S., Lopez, S., France, J. (2008). Linear models for determining digestibility, in Mathematical Modelling in Animal Nutrition, (eds) France, J.Kebreab, E. CABI Publishing, pp. 12-46. A brief overview of linear regression is presented in this chapter, followed by an appraisal examining the use of linear models to estimate digestibility, one of the main components of the nutritive value of feedstuffs, and hence one of the most studied variables in quantitative animal nutrition. Chapter 2 RONO: 2460 3006

A generic multi-stage compartmental model for interpreting gas production profiles

The gas production technique has become a key tool in feed evaluation and rumen fermentation studies. The value of the technique relies on modelling experimental data to obtain estimates of rumen degradation parameters. One of the first models used to describe gas production profiles was the simple exponential equation, although it has some important limitations when applied to gas production curves: (1) the intercept is positive, (2) only fits diminishing returns profiles, and (3) models gas per se (i.e. fails to link gas production to substrate degradation). The first limitation is overcome mathematically by re-parameterisation, making the intercept zero. The second limitation can be resolved by introducing a discrete lag to mimic sigmoidicity or by using sigmoidal functions. The third limitation is overcome by modelling substrate degradation from gas production profiles, so that equations are derived from mechanistic principles, and all parameters have biological meaning. The link between substrate degradation and gas production allows for extent of substrate degradation in the rumen to be determined for a given passage rate. Several multi-phase models have been proposed, but these were originally derived empirically and assumptions made a posteriori. Based on the conceptual difference between stage and phase, a multi-stage approach is proposed, a generic model presented and the accompanying equations derived. A two-stage model with four pools (substrate, intermediate products, fermentation end-products and by-products such as fermentation gas) is illustrated. An interpretation of the breakdown of polysaccharides to monosaccharides (first stage) and the fermentation of these monosaccharides to yield gas and other products (VFA and microbial matter) (second stage) is presented. Gas production profiles were used to demonstrate fitting the two-stage model and to consider its ability to describe gas production curves.

Regression procedures for relationships between random variables

Finding association and relationship among measured random variables is a common task in biological research and regression analysis plays a major role for this purpose. Which type of regression model to use depends on the nature of the predictor variable and on the purpose of the analysis. The most commonly used model ordinary least squares (Type I regression) applies when measurement errors affect only the response variable. The predictor is either without measurement errors or under the control of the investigator. However, if the predictor variable does have measurement errors then an ‘errors in both variables’ or Type II regression model is more appropriate and takes into account variation in both the response and the predictor variables simultaneously. When repeatability error variances in both variables are known then the maximum likelihood solution (or Deming regression) is appropriate. If the measurement error variance is unknown then a suitable Type II model should be selected. In this respect, Bartlett’s three-group method, major axis regression, standard major axis regression (also called reduced major axis), ranged major axis and instrument variable methods are discussed in relation to energy balance studies with cattle.