The dry matter intake (DMI) of forage-fed cattle can be used to predict their methane emissions. However, many cattle are fed concentrate-rich diets that decrease their methane yield. A range of equations predicting methane yield exist, but most use information that is generally unavailable when animals are fed in groups or grazing. The aim of this research was to develop equations based on proportions of ruminal volatile-fatty-acids to predict methane yield of dairy cows fed forage-dominant as well as concentrate-rich diets. Data were collated from seven experiments with a total of 24 treatments, from 215 cows. Forage in the diets ranged from 440 to 1000 g/kg. Methane was measured either by open-circuit respiration chambers or a sulfur hexafluoride (SF₆) technique. In all experiments, ruminal fluid was collected via the mouth approximately four hours after the start of feeding. Seven prediction equations were tested. Methane yield (MY) was equally best predicted by the following equations: MY = 4.08 × (acetate/propionate) + 7.05; MY = 3.28 × (acetate + butyrate)/propionate + 7.6; MY = 316/propionate + 4.4. These equations were validated against independent published data from both dairy and beef cattle consuming a wide range of diets. A concordance of 0.62 suggests these equations may be applicable for predicting methane yield from all cattle and not just dairy cows, with root mean-square error of prediction of 3.0 g CH₄/kg dry matter intake.

Globally, annual production of grape marc (GM), the residue of skins, seeds and stems remaining after making wine, has been estimated to be approximately nine million tonnes. No previous studies have compared effects on milk production and methane emissions when GM from either red or white grapes was fed to dairy cows. This experiment examines the effects of partial replacement of a perennial ryegrass (Lolium perenne L.) based diet with GM from either red or white grapes on yield and composition of milk and methane emissions. Thirty-two Holstein dairy cows in early lactation were offered either a control diet containing 15.0 kg dry matter (DM) of freshly harvested perennial ryegrass and 5.2 kg of a concentrate mix, or a diet similar to the control diet but with 5 kg DM of ryegrass replaced with 5 kg DM of GM from red grapes (RGM), or a diet similar to the RGM diet except the GM was from white grapes (WGM). Individual cow feed intakes, milk yields, and methane emissions were measured. Both diets containing GM decreased milk yields by approximately 10% and methane emissions by 15%. When fed to dairy cows, GM reduces methane emissions but at the cost of decreased milk production.

Body condition scoring is a valuable tool used to assess the changes in subcutaneous tissue reserves of dairy cows throughout the lactation resulting from changes to management or nutritional interventions. A subjective visual method is typically used to assign a body condition score (BCS) to a cow following a standardized scale, but this method is subject to operator bias and is labor intensive, limiting the number of animals that can be scored and frequency of measurement. An automated three-dimensional body condition scoring camera system is commercially available (DeLaval Body Condition Scoring, BCS DeLaval International AB, Tumba, Sweden), but the reliability of the BCS data for research applications is still unknown, as the system’s sensitivity to change in BCS over time within cows has yet to be investigated. The objective of this study was to evaluate the suitability of an automated body condition scoring system for dairy cows for research applications as an alternative to visual body condition scoring. Thirty-two multiparous Holstein-Friesian cows (9 ± 6.8 days in milk) were body condition scored visually by three trained staff weekly and automatically twice each day by the camera for at least 7 consecutive weeks. Measurements were performed in early lactation, when the greatest differences in BCS of a cow over the lactation are normally present, and changes in BCS occur rapidly compared with later stages, allowing for detectable changes in a short timeframe by each method. Two data sets were obtained from the automatic body condition scoring camera: (1) raw daily BCS camera values and (2) a refined data set obtained from the raw daily BCS camera data by fitting a robust smooth loess function to identify and remove outliers. Agreement, precision, and sensitivity properties of the three data sets (visual, raw, and refined camera BCS) were compared in terms of the weekly average for each cow. Sensitivity was estimated as the ratio of response to precision, providing an objective performance criterion for independent comparison of methods. The camera body condition scoring method, using raw or refined camera data, performed better on this criterion compared with the visual method. Sensitivities of the raw BCS camera method, the refined BCS camera method, and the visual BCS method for changes in weekly mean score were 3.6, 6.2, and 1.7, respectively. To detect a change in BCS of an animal, assuming a decline of about 0.2 BCS (1–8 scale) per month, as was observed on average in this experiment, it would take around 44 days with the visual method, 21 days with the raw camera method, or 12 days with the refined camera method. This represents an increased capacity of both camera methods to detect changes in BCS over time compared with the visual method, which improved further when raw camera data were refined as per our proposed method. We recommend the use of the proposed refinement of the camera’s daily BCS data for research applications.

There has been little research that has quantified methane (CH4) yields when dairy cows consume diets containing wheat grain. Furthermore, although rumen-fistulated animals have been used in many experiments concerned with measuring CH4 emissions, no research has examined the effect of rumen fistulation on in vivo CH4 emissions and yield. This experiment examined the effects of including either wheat or corn grain in the diet and the effects of rumen fistulation on yields of milk and milk components, CH4 emissions, yields, and intensities. Eight rumen-fistulated and six non-fistulated Holstein dairy cows in late lactation were offered a wheat-based diet (WHT) and a corn-based diet (CRN) in a crossover design. For the WHT diet, cows were offered daily, 22.4 kg DM containing 45.5% lucerne hay, 8.9% canola meal, 0.5% mineral mix, 0.5% molasses powder and 44.6% rolled wheat. The CRN diet was similar to the WHT diet except that rolled corn replaced the wheat. There was no difference between the WHT and CRN diets on mean milk yields (27.8 vs 27.9 kg/day), but the WHT diet substantially reduced milk fat concentration (2.76 vs 4.23%) and milk fat yield (0.77 vs 1.18 kg/day). Methane emissions (218 vs 424 g/day), CH4 yield (11.1 vs 19.5 g/kg dry matter intake) and CH4 intensity (7.6 vs 15.7 g/kg milk) were all reduced ~45% by the WHT diet compared with the CRN diet. Rumen fistulation did not affect dry matter intake, milk production, milk composition or CH4 emissions, but decreased CH4 yield and intensity. Including wheat in the diet of dairy cows has the potential to be an effective strategy to reduce their greenhouse gas emissions. In addition, rumen fistulation was associated with a small reduction in CH4 yield and intensity, and this should be considered when using rumen-fistulated cows in research concerned with CH4 emissions.

Nine pasture soils from high rainfall zones of southern Victoria were analysed for a range of chemical and physical properties before receiving a single application of P fertiliser in the form of triple superphosphate (TSP), single superphosphate (SSP), or TSP and lime (5 t/ha) at amounts ranging from 0 to 280 kg P/ha. Soils were analysed for bicarbonate-extractable P concentration, using both the Olsen P and Colwell P methods, 6 and 12 months after fertiliser application. A strong positive linear relationship existed at all sites between the amount of P applied and both the Olsen P and Colwell P concentrations. The slopes of these relationships measured the change in extractable P concentration (Δ EP) per unit of P applied, whilst the inverse of the ΔEP value indicated the amount of P fertiliser required above maintenance to increase the extractable P concentration by 1 mg/kg. These values ranged from 5 to 15 kg P/ha, depending on soil type. The ΔEP measured by the Olsen (Δ EP Olsen ) method was closely related to selected soil properties and P sorption measures, whilst the ΔEPColwell values were also closely related to selected soil properties and P sorption measures, but only when one particular site, an acidic sand, with a high organic carbon content was excluded from the analysis. In general, simple, direct measures of soil P sorption could allow the estimation of ΔEP values on different soil types. The application of P in the form of SSP resulted in a trend for higher ΔEP values than occurred with TSP. This difference was significant on 3 sites ( P < 0.05), but depended on the method of extraction and the time after fertiliser application. The application of lime significantly ( P < 0.001) increased soil pH (H2 O and CaCl 2 ) and decreased the concentration of exchangeable Al, 6 months after treatments were applied, but generally had little impact on ΔEP values.