Effect of varying the proportion of molasses in the diet on intake, digestion and microbial protein production by steers

The present experiment was conducted to determine the efficiency of microbial protein production in the rumen and intake by cattle fed high-molasses diets. Intake and microbial crude protein (MCP) production were measured along with the concentration of rumen ammonia-nitrogen (N) and volatile fatty acids (VFA), pH and the rate of digestion of roughage in the rumen. Eight Brahman crossbred steers weighing 211 ± 19.3 (± s.d.) kg were used in a double 4 × 4 Latin square design. Steers were allocated to one of four total mixed rations: control (pangola hay only), 25M (25% molasses/urea mix + 75% hay), 50M (50% molasses/urea + 50% hay), and 75M (75% molasses/urea + 25% hay). The production and efficiency of production of MCP (EMCP) of the diet increased quadratically as the level of molasses in the diet increased. The EMCP from the molasses/urea mix was estimated as 166 g MCP/kg digestible organic matter (DOM), a relatively high value. Intake of dry matter (DM) and DOM increased quadratically, reaching a peak when molasses was ~50% (as fed) of the ration. Digestibility of DM increased quadratically and that of neutral detergent fibre decreased linearly with increasing level of molasses in the diet. Molasses inclusion in the diet had no effect on rumen pH, ammonia and VFA concentration in the rumen fluid, plasma urea-N, urine pH or ruminal fractional outflow rate of ytterbium-labelled particles and Cr-EDTA. It was concluded that a diet with a high level of molasses (>50%) and supplemented with adequate N had high EMCP, and that low MCP production was not a factor limiting intake or performance of cattle consuming high-molasses diets.

Effect of varying the proportion of molasses in the diet on intake, digestion and microbial protein production by steers

The present experiment was conducted to determine the efficiency of microbial protein production in the rumen and intake by cattle fed high-molasses diets. Intake and microbial crude protein (MCP) production were measured along with the concentration of rumen ammonia-nitrogen (N) and volatile fatty acids (VFA), pH and the rate of digestion of roughage in the rumen. Eight Brahman crossbred steers weighing 211 ± 19.3 (± s.d.) kg were used in a double 4 x 4 Latin square design. Steers were allocated to one of four total mixed rations: control (pangola hay only), 25M (25% molasses/urea mix + 75% hay), 50M (50% molasses/urea + 50% hay), and 75M (75% molasses/urea + 25% hay). The production and efficiency of production of MCP (EMCP) of the diet increased quadratically as the level of molasses in the diet increased. The EMCP from the molasses/urea mix was estimated as 166 g MCP/kg digestible organic matter (DOM), a relatively high value. Intake of dry matter (DM) and DOM increased quadratically, reaching a peak when molasses was ∼50% (as fed) of the ration. Digestibility of DM increased quadratically and that of neutral detergent fibre decreased linearly with increasing level of molasses in the diet. Molasses inclusion in the diet had no effect on rumen pH, ammonia and VFA concentration in the rumen fluid, plasma urea-N, urine pH or ruminal fractional outflow rate of ytterbium-labelled particles and Cr-EDTA. It was concluded that a diet with a high level of molasses (>50%) and supplemented with adequate N had high EMCP, and that low MCP production was not a factor limiting intake or performance of cattle consuming high-molasses diets.

Production attributes of Merino sheep genetically divergent for wool growth are reflected in differing rumen microbiotas

Divergent genetic selection for wool growth as a single trait has led to major changes in sheep physiology and metabolism, including variations in rumen microbial protein production and uptake of α-amino nitrogen in portal blood. This study was conducted to determine if sheep with different genetic merit for wool growth exhibit distinct rumen bacterial diversity. Eighteen Merino wethers were separated into groups of contrasting genetic merit for clean fleece weight (CFW; low: WG− and high: WG+) and fed a blend of oaten and lucerne chaff diet at two levels of intake (LOI; 1 or 1.5 times maintenance energy requirements) for two seven-week periods in a crossover design. Bacterial diversity in rumen fluid collected by esophageal intubation was characterized using 454 amplicon pyrosequencing of the V3/V4 regions of the 16S rRNA gene. Bacterial diversity estimated by Phylogenetic distance, Chao1 and observed species did not differ significantly with CFW or LOI; however, the Shannon diversity index differed (P=0.04) between WG+ (7.67) and WG− sheep (8.02). WG+ animals had a higher (P=0.03) proportion of Bacteroidetes (71.9% vs 66.5%) and a lower (P=0.04) proportion of Firmicutes (26.6% vs 31.6%) than WG− animals. Twenty-four specific operational taxonomic units (OTUs), belonging to the Firmicutes and Bacteroidetes phyla, were shared among all the samples, whereas specific OTUs varied significantly in presence/abundance (P<0.05) between wool genotypes and 50 varied (P<0.05) with LOI. It appears that genetic selection for fleece weight is associated with differences in rumen bacterial diversity that persist across different feeding levels. Moderate correlations between seven continuous traits, such as methane production or microbial protein production, and the presence and abundance of 17 OTUs were found, indicating scope for targeted modification of the microbiome to improve the energetic efficiency of rumen microbial synthesis and reduce the greenhouse gas footprint of ruminants.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.