Scoring body condition and assessing changes in the body condition of dairy cattle have become strategic tools in both farm management and research. Consequently, body condition score (BCS) is being researched extensively throughout the world. However, international sharing, comparing, and use of data generated are limited because different BCS systems exist. In the United States and Ireland a 5-point BCS system is used for dairy cows, whereas Australia and New Zealand use 8- and 10-point scales, respectively. The New Zealand 10-point scale was compared with the scoring systems in the United States, Ireland, and Australia by trained assessors. Cows were assessed visually in the United States and Australia, and in Ireland, cows were assessed by palpating key areas of the cow's body (n = 154, 110, and 120, respectively). Data were analyzed by regression. Significant positive linear relationships were found between the New Zealand 10-point scale and the other scoring systems: US 5-point scale, r(2) = 0.54; Irish 5-point scale, r(2) = 0.72; and Australian 8-point scale, r(2) = 0.61. Those relationships must be interpreted cautiously because respective BCS within a given country were by just one experienced evaluator in each country in comparison to a separate evaluator scoring all cows in all counties using the New Zealand 10-point scale. Also, few very thin or very fat cows limit evaluation across extremes of BCS. However, differences between systems were not accurately predicted by simple mathematical calculations. The relationship may be closer for New Zealand and Ireland (r(2) = 0.72) because both of those scoring systems include palpation of individual body parts, whereas visual evaluation is done in Australia and the United States. The current study is the first to examine relationships among differing BCS systems. These results may be useful for comparing/extrapolating research findings from different countries.

Intake of metabolisable energy (ME) when forages and grains are fed together to ruminants may, due to digestive and metabolic interactions, be lower or higher than expected from feeding these components separately. These interactions, or associative effects, are due primarily to changes in the intake and/or the digestibility of the fibrous components of forage. Effects on voluntary forage intake (substitution effects) are usually much larger than on the digestibility of fibrous components, although the changes in forage intake may be a consequence of changes in the rate of digestion of the fibrous components. Positive associative effects, where grains increase voluntary intake and/or digestion of forage, are usually due to the provision of a limiting nutrient (eg. nitrogen, phosphorus) in the grain which is deficient in the forage. Negative associative effects, where grains decrease voluntary intake and/or digestion of forage, occur frequently and can cause low efficiency of utilisation of grain. Rate of substitution of grain for forage is related to forage intake, forage digestibility, the proportion of grain in the diet, and the maturity of the animal. Substitution rates are usually high in ruminants consuming high intakes of forage of high digestibility, probably due to the metabolic mechanisms which control voluntary intake reducing forage intake. Substitution rates are often low when animals are consuming forage of low to medium digestibility. Since voluntary intake of such forages is most likely determined by the capacity of the rumen to accommodate and pass to the lower gastrointestinal tract undigested forage residues, and of the rate of forage fibre digestion in the rumen, substitution is likely to be determined by changes in these processes. Reduced rate of fibre digestion in the rumen is often due to low rumen pH and/or an insufficiency of essential substrates for rumen microorganisms. Use of grains for lactating dairy cows involves an additional constraint since dietary grain may severely reduce milk fat content. Negative associative effects can be alleviated by ensuring supply of essential microbial substrates, feeding management, and modification of grain to minimise their adverse effects on fibre digestion, while ensuring satisfactory digestion of the grain and efficient microbial protein production.

This paper aims to provide information for farmers and their advisers to predict levels of substitution that might be occurring under various feeding conditions in northern Victoria. The approach taken involved compiling data from research conducted in northern Victoria and subjecting these to multiple regression analysis to define the key variables affecting substitution and marginal responses in milk production when concentrates are fed. A significant relationship was obtained between level of substitution (kg DM reduction in pasture intake/kg DM of concentrates eaten) and unsupplemented pasture intake (PI, kg DM/100 kg liveweight) when concentrates are fed. The regression relationship also included species composition of the sward being grazed (species: +1 grass, 0 clover), season of the year (season: +1 spring, 0 summer, –1 autumn) and concentrate intake (kg DM/cow.day). The equation is: Substitution = –0.34 + 0.16 ( 0.035) PI + 0.16 ( 0.053) species + 0.11 ( 0.024) season+ 0.03 ( 0.014) concentrate intake [100R 2 = 50.9 (P<0.01); r.s.d. = 0.14; CV = 37.7%]. Substitution increased by 0.16 kg DM/kg DM for each increment of pasture intake. At any pasture intake, grass-dominant pastures, regardless of whether the grass was perennial ryegrass (Lolium perenne) or paspalum (Paspalum dilatatum), resulted in 0.16 kg DM/kg DM more substitution than white clover (Trifolium repens)-dominant pastures. In addition, substitution was 0.11 kg DM/kg DM higher in spring than in summer, and 0.11 kg DM/kg DM higher in summer than in autumn. Finally, substitution increased by 0.03 kg DM/kg DM for each additional kg DM of concentrates offered. Marginal returns in milk production (MR, kg extra milk/kg DM of concentrates eaten) were negatively related to substitution according to the following regression equation: MR = 2.62 – 0.80 ( 0.216) substitution – 0.28 ( 0.084) season – 0.34 ( 0.086) body condition[100R2 = 62.9 (P<0.01); r.s.d. = 0.23; CV = 29.6%]. Marginal responses were 0.28 kg/kg DM lower in spring than in summer and autumn (season: +1 spring, 0 summer–autumn), and each unit improvement in body condition reduced expected marginal returns by 0.34 kg/kg DM. These relationships, together with those developed to aid estimates of unsupplemented pasture intake, can be used as background information in decision support systems to help farmers and their advisers make more informed decisions about feeding strategies when supplements are fed than has hitherto been possible.duct

Two experiments examining the effects of herbage mass and herbage allowance on the consumption of nutrients by lactating dairy cows were conducted on irrigated perennial pasture swards in northern Victoria. Experiment 1 was conducted in early lactation (spring) with a perennial ryegrass (Lolium perenne L.)–white clover (Trifolium repens L.) sward at herbage masses of 3.1 (low) or 4.9 (medium) t dry matter (DM)/ha and herbage allowances of about 20, 35, 50 and 70 kg DM/cow.day. Within each herbage mass treatment, there were no significant differences between herbage allowance treatments in nutritive characteristics of pregrazing herbage. Daily DM intake increased linearly from 7.1 to 16.2 (low mass) or 9.9 to 19.3 (medium mass) kg DM/cow, as herbage allowance increased which was equivalent to 2.29 kg DM/t DM increase in herbage mass and 0.18 kg DM/kg DM increase in herbage allowance. This was associated with a decrease in utilisation of herbage from 35 to 23% and from 52 to 29%. Also, milk production increased linearly from 21.8 to 27.1 (low mass) or 24.7 to 32.0 (medium mass) kg/cow.day as herbage allowance increased. Experiment 2 was conducted in mid lactation (summer) with a paspalum (Paspalum dilatatum L.)-dominant sward at herbage masses of 3.0 (low) or 4.7 (medium) t DM/ha and herbage allowances of about 25 and 45 kg DM/cow.day and either 0 or 5 kg DM concentrate/cow.day. Within each herbage mass treatment, there were no significant differences between herbage allowance treatments in nutritive characteristics of pregrazed herbage. Daily DM intake increased by 0.13 kg DM for every 1 kg DM increase in herbage allowance. Over the 2 herbage masses, 2 herbage allowance treatments and 2 concentrate treatments, cows consistently selected a diet about 1.03 higher in in vitro DM digestibility and 1.24 higher in crude protein than that in the herbage on offer. Substitution rate increased from 0.20 to 0.42 (low mass) and from 0.34 to 0.44 (medium mass) kg DM reduction in herbage intake/kg DM of concentrates consumed, with increasing herbage allowance. Along with these changes, marginal returns to supplements decreased from 1.38 to 0.95 (low mass) and 1.07 to 0.97 (medium mass) kg milk/kg DM of concentrates with increasing herbage allowance. Dairy farmers should consider the effects of herbage allowance and herbage mass on intake, nutrient selection and milk production when allocating pasture to dairy cows. Herbage mass and allowance had a greater effect on intake in spring than in summer, principally due to the decline in nutritive characteristics that occurs in summer. Cows selected nutrients to varying degrees depending on the composition of the pasture sward and this selection may result in seasonal nutrient imbalances. Finally, it appears that the best use of supplements will occur when pastures are short in height because this will minimise substitution of supplement for pasture and maximise marginal returns in milk production.

Two experiments were conducted to establish responses in milk Se concentrations in grazing dairy cows to different amounts of dietary Se yeast, and to determine the effects of the Se concentration of the basal diet. The hypothesis tested was that the response in milk, blood, and tissue Se concentrations to supplemental Se would not be affected by whether the Se was from the basal diet or from Se yeast. In addition, by conducting a similar experiment in either early (spring; experiment 1) or late (autumn; experiment 2) lactation, we hypothesized that different Se input-output relationships would result. Both 6-wk experiments involved 60 multiparous Holstein-Friesian cows, all of which had calved in spring. They were allocated to 1 of 10 dietary Se treatments that included 2 types of crushed triticale grain (low Se, approximately 165 microg of Se/kg of DM; or high Se, approximately 580 microg/kg of DM) fed at 4 kg of DM/d, and 1 kg of DM/d of pellets formulated to carry 5 quantities of Se yeast (0, 4, 8, 12, or 16 mg of Se). Daily total Se intakes ranged from <2 to >18 mg/cow in both experiments. Milk Se concentrations plateaued after 15 and 7 d of supplementation in experiments 1 and 2, respectively, and then remained at plateau concentrations. Average milk Se concentrations for the plateau period increased as the amount of Se yeast increased, and low- and high-Se grain treatments were different at all quantities of Se yeast, although there was a tendency for this difference to diminish at the greatest concentrations of yeast. There were significant positive, linear relationships between Se intake and the concentrations of Se in milk, which were not affected by the source of Se, and the relationships were similar for both experiments. Therefore, the output of Se in milk in experiment 1 was greater than that in experiment 2 because the milk yield of the cows in early lactation was greater. The estimated proportions of Se partitioned to destinations other than milk and feces increased with the amount of Se in the diet and were greater in experiment 2 than in experiment 1, a result that was supported by Se concentrations in whole blood and plasma and in semitendinosus muscle tissue. If high-Se products are to be produced for human nutrition, it is important to be able to develop feeding systems that produce milk with consistent and predictable Se concentrations so that products can consistently meet specifications. The results indicate that this objective is achievable.