The effect of a commercial probiotic product on the milk quality of dairy cows

Probiotics intended to improve plant health and productivity of pastures grazed by dairy cow are becoming commercially available in Australia. Great Land (GL; Terragen Biotech Pty Ltd., Coolum Beach, QLD, Australia) is one such biologic soil conditioner and spray-on probiotic with a label claim of "acting to improve plant health and productivity." The objective of this study was to quantify the effect of GL on the milk quality of cows grazing pasture top-dressed with GL. Lactating dairy cows of mixed age and breed (primarily Holstein-Friesian), in their second lactation or greater, and at least 80 d in milk were enrolled and randomly allocated into 1 of 2 study groups: a treatment cow group (n = 98; cows grazed pasture that was top-dressed with GL according to the product label) and a control cow group (n = 114; cows grazed untreated pasture). As required, both groups were supplemented at the same rate with a mixed ration during the grazing period. Composite milk samples were collected weekly from each cow during the study and analyzed to determine milk components. Milk volumes were recorded at each milking using the herd management software of the study farm. Mean differences in the milk component variables were compared using mixed-effects linear regression models. After controlling for the effect of days in milk, cow lactation, and time since a cow entered the study, the treatment cows produced an average of 1.21 L/cow per day more milk (95% confidence interval: 0.34-2.08 L/cow per day) and more milk protein (0.03 kg/d; 95% confidence interval: 0.01-0.05 kg/d) than the control cows. Pasture cover and pasture consumption did not differ between the GL-treated and the untreated study paddocks grazed by the treatment or control cows. A limited amount of published data have examined the effect of probiotic pasture treatment on the milk quality of dairy cows. This study suggests that application of such products may be beneficial. The mechanisms associated with this type of outcome remain to be investigated.

Digestion and nitrogen excretion by Holstein-Friesian cows fed grasses with lucerne or lucerne and plantain

Forages and forage mixtures with greater tolerance of dry conditions than perennial ryegrass (Lolium perenne L.) are desirable for dairy farming in New Zealand, and a low urinary nitrogen (N) excretion is desirable to lessen pollution of waterways and ground water, and nitrous oxide emissions. Measurements were undertaken with late-lactation Holstein-Friesian cows (5/treatment) fed tall fescue (Festuca arundinacea Schreb.) with a substantial incursion of weed grasses, as either a sole diet (Grass), or with lucerne (Medicago sativa L.) or lucerne and plantain (Plantago lancelota L.), in metabolism stalls. Approximate ratios (DM basis) of Grass with lucerne (GL) were 55:45, and Grass with lucerne and plantain (GLP) were 55:25:20. Measurements included intakes, production, digestion, rumen function, and urinary excretion, including the circadian patterns of metabolite excretion with a focus on nitrogenous aspects. The DM intakes (kg/day) of cows fed Grass, GL and GLP were 14.9, 12.7 and 15.0 (P = 0.006), and DM digestibility (%) was 58.0, 59.8 and 61.9 (P = 0.006), respectively. Milk yields (kg/day) were Grass, 9.0; GL, 8.7 and GLP, 11.7 (P = 0.003) but composition was not affected by diet. Rumen digesta weight was greatest in cows fed Grass, averaging 23.4% of liveweight after morning feeding. The microbial growth (g/kg organic matter digested) was 16.8 in cows fed Grass and ~24.0 in the other diets. Dietary crude protein concentrations (g/100 g DM) were Grass, 15.4, GL, 20.1 and GLP, 18.3 and urinary N excretion (g/day) was lowest with the Grass diet but urinary N concentration was lowest from cows fed GLP. Daily creatinine excretion was unaffected by diet but there was a 2-fold range in excretion rates within 24 h and values from cows fed fresh forages are lower than published values from cows fed dry diets. Results showed that supplementation of poor quality pasture with lucerne or lucerne with plantain had minor effects on digestibility, and measurements of urinary N suggest a need for caution when predicting urinary N excretion from spot urine sampling in grazing trials.

Regular estimates of herbage mass can improve profitability of pasture-based dairy systems

Paddock selection is an important component of grazing management and is based on either an estimate of herbage mass, or the interval since last grazing for each paddock. Obtaining estimates of herbage mass to guide grazing management can be a time consuming task. A value proposition could therefore assist farmers in deciding whether to invest resources in obtaining such information. A farm-scale simulation exercise was designed to estimate the effect of three levels of knowledge of individual paddock herbage mass on profitability of two typical pasture-based dairy systems in New Zealand; a medium input system stocked at 3.2 Friesian-Jersey cross bred cows/ha with ~15% imported feed, and a high input system stocked at 4.5 Friesian cows/ha with ~40% imported feed. The three levels of knowledge were: (1) ‘perfect knowledge’, where herbage mass per paddock is known with perfect accuracy, (2) ‘imperfect knowledge’, where herbage mass per paddock is estimated with an average error of 15%, (3) ‘low knowledge’, where herbage mass is not known, and paddocks are selected based on longest time since last grazing. In both systems, grazing management based on imperfect knowledge increased farm operating profit by ~NZ$385/ha at a milk price of NZ$6.33/kg milksolids (fat + protein) compared with low knowledge. Perfect knowledge added a further NZ$155/ha to profit. The main driver of these results is the level of accuracy in daily feed allocation, which increases with improved knowledge of herbage availability. This allows feed supply and demand to be better matched, resulting in less incidence of under- and over-feeding, higher milk production, and more optimal post-grazing residual herbage mass to maximise herbage regrowth.

The performance of an efficient dairy system using a combination of nitrogen leaching mitigation strategies in a variable climate

An efficient dairy system, that implemented a combination of nitrogen (N) leaching mitigation strategies including lower N fertilizer input, standing cows off pasture for part of the day in autumn and winter (stand-off), and importing limited amounts of low protein supplements was evaluated over four consecutive years of a farmlet study. This efficient system consistently demonstrated a lower measured annual N leaching of 40 to 50% compared with a baseline system representing current practice with no mitigations. To maximize return from this system fewer cows but of higher genetic merit were used resulting in an average decrease in milk production of 2% and operating profit by 5% compared with the baseline system. The magnitude of the N leaching reduction from mitigation strategies was predicted in pre-trial modelling. Using similar mechanistic models in a post-trial study, we were able to satisfactorily predict the trends in the observed N leaching data over the four years. This enabled us to use the calibrated models to explore the contributions of the different mitigation strategies to the overall leaching reduction in the efficient system. In one of the years half of the leaching reduction was achieved by the 'input' component of the strategy (less feed N flowing through the herd from lower fertilizer use, less grass grown, and low-protein supplement use), while the other half was achieved by the stand-off strategy. However, these contributions are determined by the weather of a particular year. We estimate that on average stand-off would contribute 60% and 'input' 40% to the reduction. The implication is that farmers facing nutrient loss limitations have some current and some future technologies available to them for meeting these limitations. A shift towards the mitigations described here can result in a downward trend in their own N-loss metrics. The challenge will be to negate any reductions in production and profit, and remain competitive.

Screening for diets that reduce urinary nitrogen excretion and methane emissions while maintaining or increasing production by dairy cows

Farmers face complex decisions at the time to feed animals, trying to achieve production goals while contemplating social and environmental constraints. Our purpose was to facilitate such decision making for pastoral dairy farmers, aiming to reduce urinary N (UN) and methane emissions (CH4), while maintaining or increasing milk production (MP). There is a number of feeds the farmers can choose from and combine. We used 50 feeds (forages and grains) combined systematically in different proportions producing 11,526 binary diets. Diets were screened, using an a posteriori approach and a Pareto front (PF) analysis of model (Molly) outputs. The objective was to identify combinations with the best possible compromise (i.e. frontier) between UN, CH4, and MP. Using high MP and low UN as objective functions, PF included 10, 14, 12 and 50 diets, for non-lactating, early-, mid- and late-lactation periods, with cereals and beets featuring strongly. Using the same objective functions, but including ryegrass as dietary base PF included 2, 4, 8 and 4 diets for those periods. Therefore, from a wide range of diets, farmers could choose from few feeds combined into binary diets to reduce UN while maintaining or increasing MP. If the intention is maintaining pasture-based systems, there are fewer suitable options. Reducing UN will simply require dilution of N supplied by pasture by supplementing low N conserved forages. The results also evidence the risk of pollution swapping, reaching the frontier means arriving at a point where trade-off decisions need to be made. Any further reduction in UN implies an increment in CH4, or reduction in CH4 emissions increases UN. There is no perfect diet to optimize all objectives simultaneously; but if the current diet is not in the frontier some options can offset pollution swapping. The choice is with the farmers and conditioned by their context.