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Simple Summary: Mitigating methane emissions from ruminants requires strategies that are sustainable and acceptable to both consumers and producers. Direct-fed microbials could meet these requirements. Forty Holstein-Friesian cows were randomly allocated one of two treatments, a control or control plus a direct-fed microbial (MYLO®—a mixture of Lactobacillus species; Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia). Adding the direct-fed microbial had no significant effect on feed intake, milk yield, feed conversion efficiency, or methane parameters. While these results are contrary to our expectations, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems. Using direct-fed microbials to mitigate enteric methane emissions could be sustainable and acceptable to both consumers and producers. Forty lactating, multiparous, Holstein-Friesian cows were randomly allocated one of two treatments: (1) a base of ad libitum vetch (Vicia sativa) hay and 7.0 kg DM/d of a grain mix, or (2) the basal diet plus 10 mL of MYLO® (Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia) delivering 4.17 × 108 cfu of Lactobacillus per mL. Neither feed intake (25.4 kg/d vs. 24.8 kg/d) nor milk yield (29.9 vs. 30.3 kg/d) were affected by treatment. Feed conversion efficiency was not affected by treatment when expressed on an energy-corrected milk basis (1.15 vs. 1.18 kg/kg DMI). Neither methane yield (31.6 vs. 31.1 g/kg DMI) nor methane intensity (27.1 vs. 25.2 g/kg energy corrected milk) were affected by treatments. While these results are contrary to our expectations and not significant, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems. [ABSTRACT FROM AUTHOR]

Context: Dingoes and hybrid domestic dogs (wild dogs) are lethally managed, principally by large-scale baiting programs, to protect Australia's AU$11.4 billion beef cattle industry from predation. This strategy is promoted by pest management agencies as best practice. Aim: To investigate the impact of baiting frequency and rainfall on percentage fetal and calf loss. Methods: Using 64 property-years of data from 31 properties located across Queensland and the Northern Territory, 14 171 mating outcomes were investigated to assess whether annual rainfall, relative to 124-year mean annual rainfall, and the frequency that wild dogs were lethally controlled on each property, influenced predicted fetal and calf loss. Key results: No effect of baiting frequency on fetal and calf loss in mature cows was observed. Predicted fetal and calf loss was significantly higher in dry and very wet years than in moderate-rainfall years (P < 0.001). Losses were observed to be higher in first-lactation cows when baiting was either: not conducted, conducted every 2–5 years or several times per year (P < 0.05) when compared with baiting annually, suggesting that factors other than baiting frequency are likely to have a stronger impact on calf loss. Conclusions: Only limited empirical evidence was found to support lethal control. Further investigations may clarify whether the calves of first-lactation cows experience increased predation risk and whether the effect that dry conditions have on cow nutrition, milk supply and, consequently, the vigour of the cow and calf, may also increase predation risk. Implications: Lethal control of wild dogs to protect calves is mostly unnecessary. We examined fetal and calf loss on 31 properties from 14 171 mating outcomes in relation to baiting frequency and rainfall and found that higher losses occurred in dry and very wet years than in moderate-rainfall years, but there was no association between baiting frequency and percentage fetal and calf loss. Only limited empirical evidence was found to support the lethal control of wild dogs [ABSTRACT FROM AUTHOR]

In pasture-based dairy systems, feeding a complex concentrate mix in the parlor during milking that contains cereal grains and protein supplements has been shown to have milk production advantages over feeding straight cereal grain. This experiment had the aim of testing whether further milk production advantages could be elicited by adjusting the composition of the concentrate mix in an attempt to match the expected nutrient intake from pasture during late spring. The experiment used 96 lactating dairy cows, grazing perennial ryegrass pasture offered at a target allowance of 30 kg of dry matter/cow per day (to ground level) during late spring (mid October to November) in southeastern Australia. Cows were allocated into 3 replicates of 4 treatment groups, with 24 cows in each treatment. Each treatment group was offered 1 of 4 dietary treatments in the parlor at milking: control consisting of crushed wheat and barley grains; formulated grain mix (FGM) consisting of crushed wheat, barley, and corn grains and canola meal; designer grain mix 1 (DGM1) consisting of the same ingredients as the FGM grain mix but formulated using the CPM Dairy nutrition model to take into account the expected nutrient intake from pasture; and designer grain mix 2 (DGM2) consisting of the same ingredients as DGM1 but with canola meal replaced by urea and a fat supplement (Megalac, Volac Wilmar, Gresik, Indonesia). Concentrate mixes were offered at 8.0 kg of dry matter/cow per day, except for DGM2 cows, which were offered 7.5 kg of dry matter/cow per day. The experiment ran for a total of 28 d; after a 14-d adaptation period, nutrient intake, milk production, and body weight were measured over a 14-d measurement period. Milk yield (kg) of cows fed the FGM diet was greater than that of the control cows but was not different from that of the DGM1 and DGM2 cows. However, milk fat and protein yields (kg) were greater for cows fed the FGM diet than for all other diets. There was no difference in estimated daily pasture or total dry matter intakes between the 4 treatment groups, despite cows fed the DGM2 treatment consuming less of the concentrate mix (average 6.5 kg of dry matter/cow per day when offered 7.5 kg of dry matter/cow per day). This research has demonstrated the potential for using a nutrition model to take into account the expected nutrient intake from pasture to formulate a concentrate mix (DGM1) to achieve similar milk yields, but also highlighted the need for near real-time analyses of the pasture to be grazed so as to also capture benefits in terms of milk fat and protein yield. [ABSTRACT FROM AUTHOR]

Wheat is the most common concentrate fed to grazing dairy cows in Australia, but no studies have examined the effects of wheat proportion in a pasture-based diet on milk production and methane emissions. In this 47-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets during d 1 to 36. Cows in each of the dietary treatment groups were individually offered no wheat (W0) or wheat at 3 kg of dry matter (DM)/d (W3), 6 kg of DM/d (W6), or 9 kg of DM/d (W9). The remainder of the diet was 2.2 kg of DM of concentrate mix and freshly harvested perennial ryegrass (Lolium perenne) such that all individual cows were offered a total diet of approximately 20.2 kg of DM/d. From d 37 to 47 the diets of cows receiving treatments W0 and W3 remained unchanged, but cows in treatments W6 and W9 received the W3 diet. Individual cow feed intakes, milk yields, milk compositions, and methane emissions were measured for d 31 to 35 (period 1) and d 45 to 47 (period 2). During period 1, the mean intakes of cows offered the W0, W3, W6, and W9 diets were 19.2, 20.4, 20.2, and 19.8 kg of DM/d. Diet caused differences in energy-corrected milk, and means for W0, W3, W6, and W9 were 29.5, 32.4, 33.0, and 32.9 kg/d, respectively. Milk fat percentage differed with respective means of 3.93, 3.94, 3.69, and 3.17. Diets also caused differences in methane emissions, with means for W0, W3, W6, and W9 of 440, 431, 414, and 319 g/d. During period 1, the cows fed the W9 diet produced less methane and had lower methane yields (g/kg of DMI) and intensities (g/kg of energy-corrected milk) than cows fed the W3 diet. However, in period 2 when the wheat intake of cows in the W9 treatment was reduced to the same level as in the W3 treatment, their methane emissions, yields, and intensities were similar to those offered the W3 treatment, yet protozoa numbers in ruminal fluid were still much lower than those in cows offered the W3 treatment. Our research shows that for diets based on perennial ryegrass and crushed wheat, only the diet containing more than 30% crushed wheat resulted in substantially depressed milk fat concentration and reduced methane emissions, methane yield, and methane intensity. Thus, although feeding a diet with a high proportion of wheat can cause substantial methane mitigation, it can come at the cost of depression in milk fat concentration. [ABSTRACT FROM AUTHOR]

The aim of this observational study was to identify the influence of key nongenetic factors such as month of kidding, parity, and litter size on milk yield and composition of Australian dairy goats throughout lactation. The study was conducted over 4 consecutive kidding seasons from June 2016 to March 2017. Data from 940 lactations of Saanen goats from a commercial herd were used to observe the effects of month of kidding, parity number, and litter size on total milk yield (L/goat) in early lactation (kidding to 90 d in milk; DIM), mid lactation (91–180 DIM), and late lactation (181–270 DIM), cumulative milk yield (from kidding to 270 DIM; CMY), average lactation length, proportion (%) of does reaching their target lactation length (270 DIM), somatic cell count (SCC), and percentages of milk fat and protein in early lactation. The mean herd responses throughout the entire study were as follows: CMY = 519 L/goat; lactation length = 233 d, with 70% of does reaching 270 DIM; milk fat = 4.2%; milk protein = 2.9%; and SCC = 6.2 × 105 cells/mL. Average milk production peaked in February and was lowest in June (2.4 vs. 1.8 L/goat per day, respectively). Milk yield was affected by month of kidding, parity number, and litter size in all phases of lactation. November kidders had the greatest CMY, and March kidders had the lowest CMY. March kidders had the shortest lactation length and the lowest proportion of does reaching 270 DIM. June kidders had the longest lactation length, whereas September kidders had the highest proportion of does reaching 270 DIM. Maximum milk yield was attained in third parity. Goats in fourth or greater parity had the shortest lactation length, the lowest proportion of does reaching 270 DIM, and the highest SCC. Goats delivering single kids had lower CMY, lower SCC, and higher percentages of fat and protein than does delivering multiple kids. Our findings indicate that milk yield was primarily influenced by month of kidding, and the effects of month of kidding on milk yield were accentuated during mid lactation. However, the effects of month of kidding on milk yield varied significantly among parities. [ABSTRACT FROM AUTHOR]

Mid-infrared spectroscopy (MIRS) is traditionally used for analysing milk fat, protein and lactose concentrations in dairy production, but there is growing interest in using it to predict difficult, or expensive-to-measure, phenotypes on a large scale. The resulting prediction equations can be applied to MIRS data from commercial herd-testing, to facilitate management and feeding decisions, or for genomic selection purposes. We investigated the ability of MIRS of milk samples to predict milk fatty acids (FAs) and energy balance (EB) of dairy cows in Australia. Data from 240 Holstein lactating cows that were part of two 32-day experiments, were used. Milk FAs were measured twice during the experimental period. Prediction models were developed using partial least-square regression with a 10-fold cross-validation. Measures of prediction accuracy included the coefficient of determination (R 2cv) and root mean-square error. Milk FAs with a chain length of ≤16 were accurately predicted (0.89 ≤ R 2cv ≤ 0.95), while prediction accuracy for FAs with a chain length of ≥17 was slightly lower (0.72 ≤ R 2cv ≤ 0.82). The accuracy of the model prediction was moderate for EB, with the value of R2cv of 0.48. In conclusion, the ability of MIRS to predict milk FAs was high, while EB was moderately predicted. A larger dataset is needed to improve the accuracy and the robustness of the prediction models. The present study demonstrated the potential of using mid-infrared spectroscopy of milk samples for predicting milk fatty acids and energy balance of dairy cows in Australia. Using a comparatively small dataset of 240 cows from a single research herd, the results showed that milk fatty acids were accurately predicted, while the prediction accuracy for energy balance was moderate. [ABSTRACT FROM AUTHOR]

The concept of path dependence is central to the current discourse on evolutionary approaches in regional transformations. Along the subtropical coastlands of eastern Australia, low‐input, low‐income, and labour‐intensive dairy farms were subject to prolonged dysfunction. Their creation and entrenchment serve as a potent case study of path dependence and lock‐in that were driven by mutually reinforcing attributes—behavioural, socio‐economic, cultural, political, and infrastructural. Functional rigidification and incipient dissolution were scrutinised in farm surveys undertaken from 1952 to 1954 in the Moruya and Copmanhurst districts of coastal New South Wales. At both locales, the dairy industry comprised a core of long‐term stable producers located mainly on the more accessible and productive alluvial soils, together with a fluctuating number of marginal producers motivated by a variable mix of personal, locational, and temporal influences. The demise of dairying was prolonged, in part by the industry's exceptional survival capabilities and in part by the lack of any viable alternative farming staple. The belated collapse of dairy farming in the 1960s and 1970s has facilitated the emergence and lock‐in of an alternative multifunctional pathway, driven primarily by consumption with subordinate production and protection values. The two case studies reveal synergies between the closely aligned path dependence and the multifunctional trajectory/transition concepts in yielding insights into the dynamics of rural change and in offering guidelines for further research within evolutionary economic geography. [ABSTRACT FROM AUTHOR]

This study comprises an update of the economic values for dairy traits for the Australian industry and the formulation of updated selection indices. An economic model, which calculates partial economic values for each trait individually, was developed to determine the economic implications of selective dairy breeding, based on the effect of trait changes on the profit of commercial dairy farms in Australia. Selection indices were developed from economic values, which were transformed into base economic weights by including the discounted genetic expressions coefficients. Economic weights (in Australian dollars) were 1.79, 6.92, -0.10, -5.44, 8.84, 7.68, 1.07, 4.86, 1.91, 3.51, 4.90, 0.31, 2.03, 2.00, and 0.59, for milk fat (kg), milk protein (kg), milk volume (L), body weight (kg), survival (%), residual survival (%), somatic cell count (cells/mL), fertility (%), mammary system [Australian Breeding Value (ABV) unit], temperament (ABV unit), milking speed (ABV unit), udder depth (%), overall type (%), fore udder attachment (%), and pin set (%), respectively. The updated economic weights presented in this study constituted the basis of the definition for 3 new indices. These indices were developed from combination of bioeconomic principles, patterns of farmer preferences for trait improvements, and desired gains approaches. The 3 indices, Balanced Performance Index, Health Weighted Index, and Type Weighted Index, have been released to the industry. [ABSTRACT FROM AUTHOR]

Simple Summary: In Australia, feeding grazing dairy cows concentrate and forage supplements is common. Dairy farmers face the challenge of profitably feeding their cows in situations where there is significant variation in feed costs and milk price. We used the results of grazing experiments to develop equations that predict the yield of milk fat and milk protein when different combinations of concentrates and pasture + forage are fed to grazing lactating dairy cows. We applied economic principles to these predictions to estimate the optimal combination of these feeds for given costs and prices. Feed is the largest variable cost in dairying. The allocation of pasture and supplements that are based on better estimates of milk responses to supplements should lead to increased profit for farmers. Feed is the largest variable cost for dairy farms in Australia, and dairy farmers are faced with the challenge of profitably feeding their cows in situations where there is significant variation in input costs and milk price. In theory, the addition of 5.2 MJ of metabolisable energy to a lactating cow's diet should be capable of supporting an increase in milk production of one litre of milk of 4.0% fat, 3.2% protein and 4.9% lactose. However, this is almost never seen in practice, due to competition for energy from other processes (e.g., body tissue gain), forage substitution, associative effects and imbalances in rumen fermentation. Pasture species, stage of maturity, pasture mass, allowance and intake, stage of lactation, cow body condition and type of supplement can all affect the milk protein plus fat production response to additional feed consumed by grazing dairy cows. We developed a model to predict marginal milk protein plus fat response/kg DM intake when lactating dairy cows consume concentrates and pasture + forages. Data from peer reviewed published experiments undertaken in Australia were collated into a database. Meta-analysis techniques were applied to the data and a two-variable quadratic polynomial production function was developed. Production economic theory was used to estimate the level of output for given quantities of input, the marginal physical productivity of each input, the isoquants for any specified level of output and the optimal input combination for given costs and prices of inputs and output. The application of the model and economic overlay was demonstrated using four scenarios based on a farm in Gippsland, Victoria. Given that feed accounts for the largest input cost in dairying, allocation of pasture and supplements that are based on better estimates of marginal milk responses to supplements should deliver increased profit from either savings in feed costs, or in some cases, increased output to approach the point where marginal revenue equals marginal costs. Such data are critical if the industry is to take advantage of the opportunities to use supplements to improve both productivity and profitability. [ABSTRACT FROM AUTHOR]

Milk fat whiteness is the key to the uniqueness of Western Australian milk. Following a controlled feeding regime, milk was collected fortnightly for 6 mo from 2 treatment groups: dryland and irrigation. The results showed that it was possible to produce high-quality milk with whiter fat by a controlled feeding regime and diet while maintaining the health of Holstein-Friesian cows. The reflectance method using infinite optical thickness showed milk fat color differences due to feed could be measured. After 8 wk of the study, milk fat from the dryland treatment was significantly whiter ( P < 0.05) than the irrigation treatment with area under curve total reflectance of 902.8 and 838.3, respectively. The official Japanese industry method, Agriculture and Livestock Industries Corp. (ALIC) butter tone, showed that from the 2nd to the 5th collections the color of milk fat from cows fed silage and grain (dryland treatment) was significantly whiter ( P < 0.01) with an average butter tone of 0.15 absorbance per gram compared to cows fed green pasture and grain (irrigation treatment) with a butter tone of 0.21 absorbance per gram. Protein and riboflavin levels also affect the whiteness of milk. The study followed the main feeding protocol of dryland dairies and suggests the majority of milk from Western Australia would receive a grade 1 classification, as dryland dairies dominate supply. [ABSTRACT FROM AUTHOR]