Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing

Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this is often overlooked because existing approaches are labour-intensive, need calibration, and are commonly perceived as inaccurate. Machine-learning processes harnessing big data, including remote sensing, can offer a new era of decision-support tools (DST) for pasture monitoring. Its application on-farm remains poor because of a lack of evidence about its accuracy. This study aimed at evaluating and quantifying the minimum data required to train a machine-learning satellite-based DST focusing on accurate pasture biomass prediction using this approach. Management data from 14 farms in New South Wales, Australia and measured pasture biomass throughout 12 consecutive months using a calibrated rising plate meter (RPM) as well as pasture biomass estimated using a DST based on high temporal/spatial resolution satellite images were available. Data were balanced according to farm and week of each month and randomly allocated for model evaluation (20%) and for progressive training (80%) as follows: 25% training subset (1W: week 1 in each month); 50% (2W: week 1 and 3); 75% (3W: week 1, 3, and 4); and 100% (4W: week 1 to 4). Pasture biomass estimates using the DST across all training datasets were evaluated against a calibrated rising plate meter (RPM) using mean-absolute error (MAE, kg DM/ha) among other statistics. Tukey's HSD test was used to determine the differences between MAE across all training datasets. Relative to the control (no training, MAE: 498 kg DM ha-1) 1W did not improve the prediction accuracy of the DST (P > 0.05). With the 2W training dataset, the MAE decreased to 342 kg DM ha-1 (P < 0.001), while for the other training datasets, MAE decreased marginally (P > 0.05). This study accounts for minimal training data for a machine-learning DST to monitor pastures from satellites with comparable accuracy to a calibrated RPM which is considered the 'gold standard' for pasture biomass monitoring.

Graduate Student Literature Review: System, plant, and animal factors controlling dietary pasture inclusion and their impact on ration formulation for dairy cows

Diet formulation in a pasture-based dairy system is a challenge as the quality and quantity of available pasture, which generally constitutes the base diet, is constantly changing. The objective of this paper is to cover a more in-depth review of the nutritional characteristics of pasture-based diets, identifying potential system, plant, and animal factors that condition pasture dietary inclusion in dairy cows. In practice, there is a wide diversity of pasture-based systems with predominant to minimal use of pasture requiring a more specific classification that potentially considers the amount and time of access to pasture, access to housing, length of grazing season, seasonality of calving, and level and method of supplementation. There are important differences in the nutritional quality between pasture species and even cultivars. However, under management practices that promote maintenance of pasture in a vegetative state as well as controlling the availability of pasture, it is possible to achieve high dry matter intakes (∼2.9%-3.4% of live weight) of pasture with moderate to high diet energy density, protein supply, and digestibility. The amount of pasture to include in the diet will depend on several factors, such as the type of production system, the cost of supplementary feeds, and the farmer's objectives, but inclusions of ∼40% to 50% of the diet seem to potentially reduce costs while apparently not limiting voluntary feed intake. Considering that there seems to be a continuum of intermediate management systems, a better understanding of the factors inherent to the feed ingredients used, as well as the use of nutrients by cows, and potential interactions between animal × system should be addressed in greater depth. This requires a meta-analysis approach, but given the diversity of the pasture-based system in practice, the existing information is highly fragmented. A clear definition of "subsystems" is necessary to direct the future research and development of mechanistic models.

Optimising profitability and productivity of pasture-based dairy farms with automatic milking systems

There is a large variability in profitability and productivity between farms operating with automatic milking systems (AMS). The objectives of this study were to identify the physical factors associated with profitability and productivity of pasture-based AMS and quantify how changes in these factors would affect farm productivity. We utilised two different datasets collected between 2015 and 2019 with information from commercial pasture-based AMS farms. One contained annual physical and economic data from 14 AMS farms located in the main Australian dairy regions; the other contained monthly, detailed robot-system performance data from 23 AMS farms located across Australia, Ireland, New Zealand, and Chile. We used linear mixed models to identify the physical factors associated with different profitability (Model 1) and partial productivity measures (Model 2). Additionally, we conducted a Monte Carlo simulation to evaluate how changes in the physical factors would affect productivity. Our results from Model 1 showed that the two main factors associated with profitability in pasture-based AMS were milk harvested/robot (MH; kg milk/robot per day) and total labour on-farm (full-time equivalent). On average, Model 1 explained 69% of the variance in profitability. In turn, Model 2 showed that the main factors associated with MH were cows/robot, milk flow, milking frequency, milking time, and days in milk. Model 2 explained 90% of the variance in MH. The Monte Carlo simulation showed that if pasture-based AMS farms manage to increase the number of cows/robot from 54 (current average) to ∼ 70 (the average of the 25% highest performing farms), the probability of achieving high MH, and therefore profitability, would increase from 23% to 63%. This could make AMS more attractive for pasture-based systems and increase the rate of adoption of the technology.

ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: Opportunities and Challenges of Confined and Extensive Precision Livestock Production

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative five-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSMs). This five-step process acts as a guide to realize anticipated benefits from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confined and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in more challenging and harsh, extensive systems, it is likely that confined operations will benefit from required advances in precision technology and PSMs, ultimately strengthening the benefits from precision technology to achieve short- and long-term goals.

Performance and feeding behavior of Holstein and Holstein × Gyr crossbred heifers grazing temperate forages

This study aimed to investigate the difference between Holstein and Holstein × Gyr breeds on feeding behavior and performance of heifers grazing temperate pasture. The experiment was carried out in 89 days, split into 14 days of adaptation, and 3 periods of 25 days. Two treatments were used: Holstein (HOL; n = 7) and Holstein × Gyr (HG; n = 7). Heifers grazed a consortium of ryegrass and bristle oats and were supplemented individually daily with cornmeal at 0.33% of body weight plus 5 kg/day of corn silage. For 3 consecutive days, feeding behavior was observed for individual animals from direct visual observation recording at 10-min intervals. The digestibility trial was performed on day (d) 16 to d24 of each period. Body measurements and weight were taken at d0 and at d23, 24, and 25 of each period. Grazing duration, grazing frequency, and bite rate were greater for HOL than those for HG. Rumination characteristics, intake, digestibility, and body measurements were not affected by breed. Breeds had differences in grazing characteristics, but they did not influence performance or intake parameters. Therefore, HOL and HG heifers managed under temperate pasture in tropical countries have similar performances.

Prior Forage Type Influences Ruminal Responses to a Wheat Grain Challenge in Lactating Dairy Cows

Simple Summary

High-producing dairy cows require more than just pasture to meet the energy demands of milk production. Wheat is an excellent energy source for milk production; however, cows require careful adaptation and monitoring to avoid ruminal upset when large amounts of wheat are introduced. The results of this study show that careful selection of the forage that precedes wheat could allow safer and more aggressive grain introduction strategies to be used in the dairy industry.

Abstract

To increase the dry matter and metabolisable energy intake of cows, dairy farmers often supplement pasture with concentrates and conserved fodder. Feeding large amounts of highly fermentable concentrates to cows can result in metabolic issues, such as ruminal acidosis, and thus safer but more efficient introduction strategies are desirable. We assessed the role that forages play in ruminal, behavioural and production responses to a wheat grain challenge in dairy cows with no previous wheat adaptation. Multiparous lactating Holstein dairy cows (n = 16) were fed a forage-only diet of either lucerne (Medicago sativa) hay, perennial ryegrass (Lolium perenne L.) hay or one of two cultivars of zero-grazing fresh perennial ryegrass herbage (Bealey or Base), for 3 weeks. The forage diet was then supplemented with crushed wheat grain at 8 kg dry matter/cow day⁻¹, with no adaptation period. Wheat comprised between 32 and 43% of total dry matter intake. Cows fed hay maintained a higher mean ruminal fluid pH than those fed herbage, on both the forage-only diet (6.43 vs. 6.17) and the forage plus wheat diet (6.03 vs. 5.58). Following supplementation of wheat, cows fed herbage exhibited minimum ruminal fluid pH levels indicative of acute ruminal acidosis, at 5.15 and 5.06 for cultivars Bealey and Base, respectively. Furthermore, for both herbage cultivars, adding wheat resulted in a ruminal fluid pH under 6 for >20 h/day. The ruminal environment of cows fed lucerne hay remained most stable throughout the grain challenge, spending the least amount of time below pH 6.0 (9.0 h/day). Hay created a ruminal environment that was better able to cope with the accumulation of acid as wheat was digested. A combination of increased ruminating time and a slower rate of fermentation, due to higher neutral detergent fiber and lower metabolisable energy concentrations in the hays, is likely responsible for the higher ruminal fluid pH values. Forage plays a critical role in wheat introduction strategies; aggressive adaptation strategies could be implemented when a hay such as lucerne is used as the base forage.

Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence

New and emerging technologies, especially those based on non-invasive video and thermal infrared cameras, can be readily tested on robotic milking facilities. In this research, implemented non-invasive computer vision methods to estimate cow's heart rate, respiration rate, and abrupt movements captured using RGB cameras and machine learning modelling to predict eye temperature, milk production and quality are presented. RGB and infrared thermal videos (IRTV) were acquired from cows using a robotic milking facility. Results from 102 different cows with replicates (n = 150) showed that an artificial neural network (ANN) model using only inputs from RGB cameras presented high accuracy (R = 0.96) in predicting eye temperature (°C), using IRTV as ground truth, daily milk productivity (kg-milk-day^-1), cow milk productivity (kg-milk-cow^-1), milk fat (%) and milk protein (%) with no signs of overfitting. The ANN model developed was deployed using an independent 132 cow samples obtained on different days, which also rendered high accuracy and was similar to the model development (R = 0.93). This model can be easily applied using affordable RGB camera systems to obtain all the proposed targets, including eye temperature, which can also be used to model animal welfare and biotic/abiotic stress. Furthermore, these models can be readily deployed in conventional dairy farms.

Intensification strategies for temperate hot-summer grazing dairy systems in South America: Effects of feeding strategy and cow genotype

Pasture-based dairy systems present the opportunity to increase productivity per hectare through increasing stocking rate and forage utilization. However, in the temperate hot-summer region of South America, different productive strategies are being adopted by farmers. The aim of this study was to quantify the effect of feeding strategy (FS) and cow genotype (G) on individual animal and whole-farm biophysical performance. A design with 2 × 2 levels of intensification aiming to increase home-grown forage utilization and milk output per hectare was evaluated. The experiment was a randomized complete block design with a 2 × 2 factorial arrangement of treatments, combining 2 feeding strategies with varying proportions of grazing in the annual feeding budget [grass fixed (GFix) and grass maximum (GMax)] and 2 Holstein Friesian cow genotypes [New Zealand (NZHF) or North American Holstein Friesian (NAHF)]. The effects of FS, G, and their interaction were analyzed using mixed models. New Zealand Holstein Friesian cows presented lower individual milk yield and higher milk component concentrations, maintained higher average body condition score, and increased body weight (BW) throughout the experiment, while presenting a better reproductive performance compared with the NAHF cows. Although all farmlets were planned at the same stocking rate on a per kilogram of BW basis, the current stocking rate changed as a result of animal performance and grass utilization resulting in NZHF cows achieving greater BW per hectare. The superior stocking rate led to greater milk solids production and feed consumption per hectare for the systems with NZHF cows. The GFix feeding strategy resulted in greater total home-grown forage harvest and conserved forage surplus than GMax. Overall, it was feasible to increase stocking rate and increase milk production per hectare from home-grown forage with differing feeding strategies and Holstein Friesian cow genotypes within grazing systems located in the temperate hot-summer climate region of South America. The interactions reported between FS × G highlight the superior productivity per hectare of NZHF cows within the GMax feeding strategy based on maximizing grazed pasture, which could represent a competitive intensification strategy in terms of cost of production for this region.

Physical and economic comparison of pasture-based automatic and conventional milking systems

Automatic milking systems (AMS) have the potential to increase dairy farm productivity and profitability; however, adoption rates, particularly in pasture-based systems, have been lower than expected. The objectives of this study were to compare the physical and economic performance of pasture-based AMS with conventional milking systems (CMS) and to identify gaps for improving AMS productivity and profitability. We used data from 14 AMS and 100 CMS located in the main Australian dairy regions and collected over 3 yr (2015-2016, 2016-2017, 2017-2018). Farms within similar regions and herd sizes were compared. Results showed that all the main physical performance indicators evaluated such as milk production per cow, milk production per hectare, pasture grazed per hectare, or milk solids per full-time equivalent were similar between systems. The AMS farms had higher overhead costs such as depreciation and repairs and maintenance; however, no differences in total labor costs were observed between systems. Profitability, measured as earnings before interest and tax, operating profit margin, and return on total assets, was not significantly different between AMS and CMS. Opportunities for improving pasture utilization, labor efficiency, and robot utilization in AMS farms were identified. Improving efficiency in these areas could improve productivity and profitability of these systems, and therefore increase the interest of this technology.

Animal science Down Under: a history of research, development and extension in support of Australia’s livestock industries

This account of the development and achievements of the animal sciences in Australia is prefaced by a brief history of the livestock industries from 1788 to the present. During the 19th century, progress in industry development was due more to the experience and ingenuity of producers than to the application of scientific principles; the end of the century also saw the establishment of departments of agriculture and agricultural colleges in all Australian colonies (later states). Between the two world wars, the Council for Scientific and Industrial Research was established, including well supported Divisions of Animal Nutrition and Animal Health, and there was significant growth in research and extension capability in the state departments. However, the research capacity of the recently established university Faculties of Agriculture and Veterinary Science was limited by lack of funding and opportunity to offer postgraduate research training. The three decades after 1945 were marked by strong political support for agricultural research, development and extension, visionary scientific leadership, and major growth in research institutions and achievements, partly driven by increased university funding and enrolment of postgraduate students. State-supported extension services for livestock producers peaked during the 1970s. The final decades of the 20th century featured uncertain commodity markets and changing public attitudes to livestock production. There were also important Federal Government initiatives to stabilise industry and government funding of agricultural research, development and extension via the Research and Development Corporations, and to promote efficient use of these resources through creation of the Cooperative Research Centres program. These initiatives led to some outstanding research outcomes for most of the livestock sectors, which continued during the early decades of the 21st century, including the advent of genomic selection for genetic improvement of production and health traits, and greatly increased attention to public interest issues, particularly animal welfare and environmental protection. The new century has also seen development and application of the ‘One Health’ concept to protect livestock, humans and the environment from exotic infectious diseases, and an accelerating trend towards privatisation of extension services. Finally, industry challenges and opportunities are briefly discussed, emphasising those amenable to research, development and extension solutions.

Defining the key attributes of resilience in mixed ration dairy systems

Dairy feeding systems in Australia and New Zealand have seen an increase in the use of mixed rations to manage variability in climate and market conditions and enable a certain degree of resilience in the operating environment. In this review, resilience was defined as the ability of the farm system to respond to challenges, optimise productivity and profitability for a given set of circumstances, and persist over time. Specific attributes of a dairy system that contribute to resilience were considered as flexibility, consistency, adaptation, sustainability and profitability. A flexible forage base that uses water efficient forage species provides a consistent supply of nutrients from home-grown forages across the year and is a key driver of resilience. Consistent milk production from purchased concentrates adds value to the forage base and will ensure that the system is profitable in the long term. Appropriate investment in infrastructure and careful management of debt has a positive impact on technical and financial efficiency and improves overall economic performance and resilience of the system. Nutrients, feed wastage, cow comfort and welfare were also identified as key areas to focus on for improved sustainability. Future research investigating the interaction between forages and concentrates, and the subsequent milk production response will be important for the future resilience of mixed ration systems. Adaptive management at a tactical and strategic level across several technical areas will further underpin the resilience of a mixed ration dairy system, and minimise the impact of climate and price variability. This will have flow on benefits to animal welfare and resource sustainability, which will have a positive impact of the public perception of these systems within the Australian and New Zealand dairy industries.

Prediction of quarter level subclinical mastitis by combining in-line and on-animal sensor data

We investigated the potential for automatic detection of subclinical mastitis (SCM) in pasture-based automatic milking systems. The objective of the study was to determine the ability of electrical conductivity (EC), together with relative changes in daily activity (activity) and daily rumination (rumination) recorded using heat and rumination–long-distance tags, to predict quarter-level SCM. Activity (arbitrary unit/day) and rumination (min/day) data were determined across 21 days using heat and rumination–long-distance tags for 170 cows. Cows were allocated into the following three groups: SCM (n = 32, EC ≥ 7.5 millisiemens/cm (mS/cm) in one or more quarters and a positive bacteriological culture in the corresponding quarter(s)); true-negative (TN, n = 9, EC ≥ 7.5 mS/cm and a negative culture in all four quarters); and apparently healthy (n = 129, no culture test and EC &lt; 7.5 mS/cm). Group mean differences in activity and rumination were compared using Welch’s t-tests. Logistic mixed models were used to predict SCM by EC, activity and rumination changes before mastitis detection, including parity information between SCM and TN groups. Cow- and quarter-specific information were included as random effects, followed by model assessment by producing receiver operating-characteristic curve and area under the curve (AUC) value. In total, 287 quarters were used in the prediction model, including 143 quarters with a positive culture (Gram-positive; n = 131, Gram-negative; n = 6, mixed; n = 6) and 144 quarters with a negative culture. On average, SCM group had 4.65% greater (P &lt; 0.01) activity and 9.89% greater (P &lt; 0.001) rumination than did the TN group and 11.70% greater (P &lt; 0.001) activity than did the apparently healthy group. A combined model with terms for EC, activity changes, rumination changes prior to detect SCM and parity had a better SCM prediction (AUC = 0.92) ability than did any of them separately (all AUC &lt; 0.8). Hence, we conclude that EC in combination with activity and rumination information can improve the accuracy of prediction of quarter-level SCM.

Artificial Grass as an Alternative Laneway Surface for Dairy Cows Walking to Pasture

Softer surfaces can alleviate pressure on the claw during claw-surface contact, which is especially important for cows with painful claws. The benefits of softer barn floors are well known, but as cows often walk long distances twice daily between pasture and parlour, laneway surfaces are also important. In trial 1, we evaluated the gait of 69 cows on a standard (stone dust-over-gravel) laneway and an artificial grass laneway. Greater speed and longer strides were interpreted as indicators of a more suitable surface. Walking speed was greater on artificial grass than on the standard laneway (p = 0.001, median artificial grass: 1.46 m/s [interquartile range (IQR): 1.39-1.54], standard 1.40 m/s [IQR: 1.30-1.48]). No significant stride length increase was detected (p > 0.10, 158 cm [IQR:151-166] versus 155 cm [IQR:149-164]). In trial 2, we evaluated cow preference by giving 66 pairs of cows four consecutive choices between the standard laneway and artificial grass. Artificial grass was preferred overall (median stretches of artificial grass used out of a maximum of 4: 3 [IQR:2-4], p < 0.001). This preference was significantly (p = 0.001) stronger in lame cows (median: 3 [IQR:3-4]), than in sound ones (median: 2 [IQR:2-3]). Preference was also affected by the side of the laneway covered with artificial grass. Our results suggest that artificial grass improves the welfare of dairy cows walking to and from pasture, with lame cows benefiting to a greater extent.

Suitability of somatic cell count, electrical conductivity, and lactate dehydrogenase activity in foremilk before versus after alveolar milk ejection for mastitis detection

Mastitis is responsible for substantial economic loss and significant animal welfare concerns for the dairy industry. Sensors that measure electrical conductivity (EC) and enzyme concentrations of lactate dehydrogenase (LDH) are presently used for automatic detection of mastitis. However, EC is not sensitive enough to detect mastitis, and the ability of LDH activity to identify mastitis caused by different pathogens is a potential option that needs to be investigated. This study was conducted to test the following hypotheses: (a) strict foremilk before milk ejection is more informative in detecting mastitis, in general, than foremilk removed after cows were stimulated for milk ejection; and (b) the value of LDH activity as a mastitis indicator depends on the type of pathogen associated with the infection. Milk samples (before afternoon milking) from 48 Holstein-Friesian cows at the University of Sydney's dairy farm (Camden, New South Wales, Australia) with EC > 7.5 mS/cm in any of the 4 quarters were collected over a period of 2 mo. Quarter milk samples (n = 343) from 48 cows were collected manually in the automatic milking rotary in 3 steps: foremilk before (strict foremilk) and after milk ejection, followed by an aseptic sample for bacteriological culture. The EC (mS), LDH (U/L), SCC (cells/mL), and milk protein and fat content (%) of foremilk in both sampling times were compared and used as predictors for gram-positive and gram-negative mastitis. Quarter (n = 515) observations from 44 cows were analyzed using a logistic mixed or linear mixed model, with cow and quarter nested within cow as random effects. Milk from both sampling times was also assessed by producing a receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC) to determine ability to detect mastitis. Overall, EC and LDH were greater and milk protein (%) was lower in strict foremilk than in milk fractions obtained after milk ejection. Data from strict foremilk samples had slightly higher AUC values (0.98 to 0.99 vs. 0.97 to 0.98, respectively) than did the after-ejection milk samples. Although gram-negative coliform mastitis had significantly higher LDH activity than did gram-positive mastitis (6.19 vs. 5.34 log₁₀ U/L), the robustness of this result is questionable due to limited sample size. We concluded that milk samples taken before ejection can influence major mastitis indicators, suggesting that automatic milking system sensors could be modified to monitor milk before ejection for more efficient mastitis detection.

The Behaviour and Productivity of Mid-Lactation Dairy Cows Provided Daily Pasture Allowance over 2 or 7 Intensively Grazed Strips

Research into the effects of intense grazing regimes on cattle behaviour and productivity will support the ethical intensification of pastoral dairy production. Two treatments were applied to two herds of 30 mid-lactation cows over 28 days. Cows were offered an estimated 12 kg DM/cow (above 5 cm from ground level) of irrigated pasture per day. The control herd received their daily pasture allocation in two equal grazings while the experimental herd received theirs over seven smaller grazings. Backgrazing beyond the current allocation (morning or afternoon) was prevented. Individual records were taken daily for milk production and behaviour (MooMonitor⁺). Milk composition, energy corrected milk (ECM), and live weight were recorded weekly. Feeding mid-lactation dairy cows over seven smaller grazing allocations reduced the time cows spent ruminating (p < 0.001), milk yield (p < 0.001), and ECM (p < 0.05). However, milk composition, live weight, time feeding, and pasture consumption were not affected by feeding frequency (p > 0.05). Cattle may have adapted their ingestive behaviour in response to the more intensive strip-grazing regime utilised in this study, with negative consequences for digestive processes and consequently milk production. Intense grazing regimes need to support the ingestive, digestive, and social behaviours of cattle.

The effect of temperate or tropical pasture grazing state and grain-based concentrate allocation on dairy cattle production and behavior

Grain-based concentrate (GBC) supplement is of high cost to dairy farmers as a feed source as opposed to grazed pasture. Milk production response to GBC is affected by the composition and nutritive value of the remainder of the diet, animal factors, and interactions between forage type and level of GBC. In grazing systems, dairy cattle encounter contrasting pasture states, primarily because the social structure of the herd affects the timing of when each animal accesses a paddock after milking as a result of a relatively consistent cow milking order. However, the effect of feed management, namely pasture state and GBC allocation, on dairy cattle production and behavior is unknown. We examined the effect of varying GBC allocation for dairy cattle grazing differing states of kikuyu grass (Pennisetum clandestinum, a tropical pasture species; experiment 1) and annual ryegrass (Lolium multiflorum L., a temperate pasture species; experiment 2) on dry matter intake, milk production and composition, and grazing behavior. For each experiment, 90 lactating dairy cattle were randomly allocated to 2 consistent (fresh-fresh and depleted-depleted) and 2 inconsistent (fresh-depleted and depleted-fresh pasture state treatments (defined as sequences of pasture state allocation for the morning and afternoon grazing events) and 3 GBC treatments [2.7, 5.4, and 8.1 kg of dry matter (DM)/cow per day], giving 12 treatment combinations for each experiment. The duration of each experiment was 14 d, with the first 7 d used as adaptation to treatment. In each experiment, 3 cattle were selected from each of the 12 pasture type × GBC treatment groups within the experimental herd to determine herbage intake and total DM digestibility using the n-alkanes method (n = 36). There was no interaction between kikuyu grass or ryegrass pasture state and GBC level for intake, digestibility, or milk yield or components. Dairy cattle offered fresh-fresh and depleted-fresh ryegrass produced 9% more milk yield, in line with greater pasture intakes, compared with fresh-depleted and depleted-depleted pasture states. Dairy cattle offered fresh-fresh kikuyu grass had 8% more milk yield and 14% more milk protein yield than other pastures states, but there was no effect of pasture state on milk composition. Milk yield increased with GBC level for both pasture species (∼0.7-0.8 kg of milk/kg of DM GBC) as GBC level increased from 2.5 to 5.4 kg of DM/cow per day. There was a poor response (0.3 kg of milk/kg of DM GBC), and no response, when GBC levels increased from 5.4 to 8.1 kg of DM/cow per day for kikuyu grass and ryegrass, respectively, in line with pasture DMD. Time spent grazing, lying, and ruminating were not associated with kikuyu grass pasture state, GBC, or their interaction. Despite this, there was a linear increase in grazing time in the afternoon coinciding with a linear decrease in lying and rumination time for both kikuyu grass and ryegrass pasture. Together these findings reveal the effect of pasture state and GBC allocation on dairy cattle production and behavior. Tailoring GBC allocation to the state of pasture accessed by cattle appears unwarranted, but there is an opportunity to alter the timing of pasture access to increase herd-level milk production efficiency.

Dairy farmers with larger herd sizes adopt more precision dairy technologies

An increase in the average herd size on Australian dairy farms has also increased the labor and animal management pressure on farmers, thus potentially encouraging the adoption of precision technologies for enhanced management control. A survey was undertaken in 2015 in Australia to identify the relationship between herd size, current precision technology adoption, and perception of the future of precision technologies. Additionally, differences between farmers and service providers in relation to perception of future precision technology adoption were also investigated. Responses from 199 dairy farmers, and 102 service providers, were collected between May and August 2015 via an anonymous Internet-based questionnaire. Of the 199 dairy farmer responses, 10.4% corresponded to farms that had fewer than 150 cows, 37.7% had 151 to 300 cows, 35.5% had 301 to 500 cows; 6.0% had 501 to 700 cows, and 10.4% had more than 701 cows. The results showed that farmers with more than 500 cows adopted between 2 and 5 times more specific precision technologies, such as automatic cup removers, automatic milk plant wash systems, electronic cow identification systems and herd management software, when compared with smaller farms. Only minor differences were detected in perception of the future of precision technologies between either herd size or farmers and service providers. In particular, service providers expected a higher adoption of automatic milking and walk over weighing systems than farmers. Currently, the adoption of precision technology has mostly been of the type that reduces labor needs; however, respondents indicated that by 2025 adoption of data capturing technology for monitoring farm system parameters would be increased.

Is systems research addressing the current and future needs of dairy farms?

During the past decade, Australian and New Zealand dairy farmers have been increasingly exposed to volatility in milk prices, declining terms of trade, climate variability, changing regulation, and increasing consumer demand to demonstrate their ‘social licence to farm’. In response to the varying challenges, it is not surprising that we see significant diversity in dairy-farm systems in Australia and New Zealand. Despite much research effort to address these challenges at both the component and farm-system level, the evidence of adoption and dairy farming-system change over the past 5 years has been inconclusive. The present review explores how farmers and systems research have been affected and are responding, and whether systems research is developing research in the appropriate direction, proactively researching dairy-farming systems that are resilient, profitable and sustainable into the future, notwithstanding the increased volatility that dairy farms are experiencing. While much farm systems research in Australia and New Zealand has addressed the challenges associated with improving productivity and profitability, and the known challenges such as climate variability and improving environmental outcomes, there is need to fore-sight future risk, challenges and opportunities for dairy systems. It is also important that the system researchers explore alternative approaches such as working collaboratively with the known system experts, the dairy farmer, in a participatory environment to increase rate of knowledge transfer and adoption of positive research outcome.

Challenges of feeding dairy cows in Australia and New Zealand

There is a continuing evolution of feeding systems in both Australian and New Zealand dairy industries and this presents challenges for the future. Since the turn of the century, the two countries have diverged in industry growth characteristics, with Australian dairying having contracted, with 10% less milk being produced because of 20% fewer cows producing 15% more per cow, whereas New Zealand dairying has expanded, producing 83% more milk driven by a 54% increase in cow numbers and a 31% increase in milk production per cow. Solutions to optimise feed efficiency included the common themes of (1) growing more forage on farm, (2) increasing its utilisation and (3) more efficient use of supplements resulting in increases in DM intake, and they remain relevant. In New Zealand, many of the recent research activities have aimed at improving feed supply while limiting environmental impacts driven by increasing societal concern surrounding the environmental footprint of a growing and intensifying agricultural sector. In Australia, many of the recent research activities have aimed at improving feed efficiency, with a focus on understanding situations where partial mixed ration feeding systems (Australian Farm Systems 3 and 4) are sustainable. Simply growing more feed on farm can no longer be a sole objective; farms must be operated with a view to reduce the environmental footprint, with New Zealand dairy farmers increasingly needing to farm within nitrogen limits. The present review revisits and reinforces many of the concepts developed in previous reviews, but also examines the evolution of feeding systems in both countries and opportunities to improve feed efficiency and profit, while satisfying public expectations around environmental stewardship. We also identify some of the gaps in the current knowledge that warrant further research.

Influence of pasture-based feeding systems on fatty acids, organic acids and volatile organic flavour compounds in yoghurt

The influence of different pasture-based feeding systems on fatty acids, organic acids and volatile organic flavour compounds in yoghurt was studied. Pasture is the main source of nutrients for dairy cows in many parts of the world, including southeast Australia. Milk and milk products produced in these systems are known to contain a number of compounds with positive effects on human health. In the current study, 260 cows were fed supplementary grain and forage according to one of 3 different systems; Control (a traditional pasture based diet offered to the cows during milking and in paddock), PMR1 (a partial mixed ration which contained the same supplement as Control but was offered to the cows as a partial mixed ration on a feedpad), PMR 2 (a differently formulated partial mixed ration compared to Control and PMR1 which was offered to the cows on a feedpad). Most of the yoghurt fatty acids were influenced by feeding systems; however, those effects were minor on organic acids. The differences in feeding systems did not lead to the formation of different volatile organic flavour compounds in yoghurt. Yet, it did influence the relative abundance of these components.

Modelling Pasture-based Automatic Milking System Herds: The Impact of Large Herd on Milk Yield and Economics

The aim of this modelling study was to investigate the effect of large herd size (and land areas) on walking distances and milking interval (MI), and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR) in an automatic milking system (AMS). Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as ‘moderate’; optimum pasture utilisation of 19.7 t DM/ha, termed as ‘high’) and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture) were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density) reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance (voluntary return trip from parlour to paddock) and every one hour increase in MI, respectively. The high pasture utilisation combined with 30% of the farm in CFR in the farm increased milk yield by up to 1.5 kg/cow/d, thereby reducing loss by up to $0.5/cow/d (c.f. the moderate pasture and 800 cow herd scenario). Thus, it was concluded that the successful integration of grazeable CFS with pasture has the potential to improve financial performance compared to the pasture only, large herd, AMS.

Modelling Pasture-based Automatic Milking System Herds: System Fitness of Grazeable Home-grown Forages, Land Areas and Walking Distances

To maintain a predominantly pasture-based system, the large herd milked by automatic milking rotary would be required to walk significant distances. Walking distances of greater than 1-km are associated with an increased incidence of undesirably long milking intervals and reduced milk yield. Complementary forages can be incorporated into pasture-based systems to lift total home grown feed in a given area, thus potentially ‘concentrating’ feed closer to the dairy. The aim of this modelling study was to investigate the total land area required and associated walking distance for large automatic milking system (AMS) herds when incorporating complementary forage rotations (CFR) into the system. Thirty-six scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as moderate; optimum pasture utilisation of 19.7 t DM/ha, termed as high) and 6 rates of replacement of each of these pastures by grazeable CFR (0%, 10%, 20%, 30%, 40%, 50%) were investigated. Results showed that AMS cows were required to walk greater than 1-km when the farm area was greater than 86 ha. Insufficient pasture could be produced within a 1 km distance (i.e. 86 ha land) with home-grown feed (HGF) providing 43%, 29%, and 22% of the metabolisable energy (ME) required by 400, 600, and 800 cows, respectively from pastures. Introduction of pasture (moderate): CFR in AMS at a ratio of 80:20 can feed a 400 cow AMS herd, and can supply 42% and 31% of the ME requirements for 600 and 800 cows, respectively with pasture (moderate): CFR at 50:50 levels. In contrast to moderate pasture, 400 cows can be managed on high pasture utilisation (provided 57% of the total ME requirements). However, similar to the scenarios conducted with moderate pasture, there was insufficient feed produced within 1-km distance of the dairy for 600 or 800 cows. An 800 cow herd required 140 and 130 ha on moderate and high pasture-based AMS system, respectively with the introduction of pasture: CFR at a ratio of 50:50. Given the impact of increasing land area past 86 ha on walking distance, cow numbers could be increased by purchasing feed from off the milking platform and/or using the land outside 1-km distance for conserved feed. However, this warrants further investigations into risk analyses of different management options including development of an innovative system to manage large herds in an AMS farming system.

Modelling Pasture-based Automatic Milking System Herds: Grazeable Forage Options

One of the challenges to increase milk production in a large pasture-based herd with an automatic milking system (AMS) is to grow forages within a 1-km radius, as increases in walking distance increases milking interval and reduces yield. The main objective of this study was to explore sustainable forage option technologies that can supply high amount of grazeable forages for AMS herds using the Agricultural Production Systems Simulator (APSIM) model. Three different basic simulation scenarios (with irrigation) were carried out using forage crops (namely maize, soybean and sorghum) for the spring-summer period. Subsequent crops in the three scenarios were forage rape over-sown with ryegrass. Each individual simulation was run using actual climatic records for the period from 1900 to 2010. Simulated highest forage yields in maize, soybean and sorghum- (each followed by forage rape-ryegrass) based rotations were 28.2, 22.9, and 19.3 t dry matter/ha, respectively. The simulations suggested that the irrigation requirement could increase by up to 18%, 16%, and 17% respectively in those rotations in El-Niño years compared to neutral years. On the other hand, irrigation requirement could increase by up to 25%, 23%, and 32% in maize, soybean and sorghum based rotations in El-Nino years compared to La-Nina years. However, irrigation requirement could decrease by up to 8%, 7%, and 13% in maize, soybean and sorghum based rotations in La-Nina years compared to neutral years. The major implication of this study is that APSIM models have potentials in devising preferred forage options to maximise grazeable forage yield which may create the opportunity to grow more forage in small areas around the AMS which in turn will minimise walking distance and milking interval and thus increase milk production. Our analyses also suggest that simulation analysis may provide decision support during climatic uncertainty.

Empowering farmers for increased resilience in uncertain times

As farmers continue to face increasingly uncertain and often rapidly changing conditions related to markets, climate or the policy environment, people involved in agricultural research, development and extension (RD&E) are also challenged to consider how their work can contribute to supporting farmer resilience. Research from the social sciences conducted in the past decade has focussed on adaptability or adaptive capacity as a key attribute for individuals and groups to possess for managing resilience. It is, therefore, timely to ask the following: do current ways of doing and organising RD&E in the dairy sector in New Zealand and Australia contribute to supporting farm adaptability? This paper reports on results from an examination of case studies of challenges to resilience in the dairy sector in Australia and New Zealand (i.e. dairy farm conversion, climate-change adaptation, consent to farm) and the contribution of dairy RD&E in enhancing resilience of farmers, their farms and the broader industry. Drawing on concepts from resilience studies and considering an empowerment perspective, the analysis of these cases suggest that, currently, agricultural RD&E supports adaptability in general, but varies in the strength of its presence and level of activity in the areas known to enhance adaptability. This analysis is used to generate principles for dairy scientists and others in the RD&E system to consider in (1) research designs, (2) engaging different farmers in research and (3) presenting research results differently. This represents a significant shift for the science and advisory communities to move to methods that acknowledge uncertainty and facilitate learning.

Increasing home-grown forage consumption and profit in non-irrigated dairy systems. 1. Rationale, systems design and management

The profitability of dairy businesses in southern Australia is closely related to the amount of feed consumed from perennial ryegrass-dominant pasture. Historically, the dairy industry has relied on improvements in pasture productivity and utilisation to support profitable increases in stocking rate and milk production per hectare. However, doubts surround the extent to which the industry can continue to rely on perennial ryegrass technology to provide the necessary productivity improvements required into the future. This paper describes the design and management of a dairy systems experiment at Terang in south-west Victoria (780-mm average annual rainfall) conducted over four lactations (June 2005–March 2009) to compare the production and profitability of two forage base options for non-irrigated dairy farms. These options were represented by two self-contained farmlets each milking 36 mixed-age, autumn-calving Holstein-Friesian cows at peak: (1) well managed perennial ryegrass pasture (‘Ryegrass Max’, or ‘RM’); and (2) perennial ryegrass plus complementary forages (‘CF’) including 15% of farmlet area under double cropping with annual species (winter cereal grown for silage followed by summer brassica for grazing on the same land) and an average of 25% of farmlet area in perennial pasture based on tall fescue for improved late spring–early summer feed supply. The design of these systems was informed by farming systems models (DairyMod, UDDER and Redsky), which were used to estimate the effects of introducing different forage options on farm profitability. The design of the CF system was selected based on modelled profitability increases assuming that all forage components could be managed to optimise forage production and be effectively integrated to optimise milk production per cow. Using the historical ‘average’ pasture growth curve for the Terang district and a mean milk price of $3.71 per kg milk solids, the models estimated that the return on assets of the RM and CF systems would be 9.4 and 15.0%, respectively. The objectives of the experiment described here were to test whether or not such differences in profitability could be achieved in practice, and to determine the risks associated with including complementary forages on a substantial proportion of the effective farm area. Key results of the experiment are presented in subsequent papers.

Increasing home-grown forage consumption and profit in non-irrigated dairy systems. 3. Intake, milk production and composition, bodyweight and body condition score

This paper reports the performance [intake, milk production, bodyweight and body condition score (BCS)] of cows managed under two feeding systems over 4 years (June 2005–May 2009) in south-west Victoria, Australia. The feeding systems were ‘Ryegrass Max’ (RM) a well managed perennial ryegrass pasture-based system stocked at 2.2 cows/ha, and a ‘Complementary Forage’ (CF) system based on perennial ryegrass, tall fescue and a double crop of winter-sown cereal and summer-sown brassica crops stocked at 2.82 cows/ha. There were no significant differences in milk production per lactation between feeding systems, with an average of 543 and 553 kg milk solids per cow (1246 and 1642 kg milk solids per ha) produced in the RM and CF systems, respectively. These production levels were 20.9 and 10.8% above pre-experimental model targets, respectively. The bodyweight and BCS of multiparous cows were not significantly different between the two feeding systems; however, bodyweight of heifers in early lactation declined more rapidly in the CF compared with RM feeding system. Over the 4-year study in the RM system pasture comprised 60% of total DM consumed (grazed + conserved), with 26% of the ration being concentrate and the balance being purchased hay supplements. In the CF system, home-grown forage contributed 57.9% of total DM consumed of which 46.6% was pasture (grazed + conserved) and 11.3% was from the double cropping system. These levels of home-grown forage consumption were lower than those predicted by the pre-experimental modelling, leading to higher than predicted levels of purchased concentrates and conserved forages being fed. The lower than expected levels of consumption of the forages produced in the double cropping system reflected both the low intake potential and moderate nutritive value of cereal silage, and the failure of establishment and subsequent low DM yields from the summer brassica crop. Further work is required to determine the risk of implementing CF in rain-fed dairy systems reflecting uncertainties in forage management planning and nutrient delivery to support high levels of milk production.

Use of partial mixed rations in pasture-based dairying in temperate regions of Australia

There is a growing diversity and complexity of dairy farming systems in Australia. Feeding systems based on the provision of mixed rations to dairy cows grazing perennial pastures (termed partial mixed rations or PMR systems) have emerged and present the dairy industry with opportunities for improved production and feed efficiency, but also with significant challenges. Early research results are beginning to define the situations in which PMR systems are profitable and the mechanisms responsible for the improved milk responses. This review focuses on the role of PMR feeding systems in temperate dairying regions of Australia, highlights initial research findings, and identifies some of the gaps in current knowledge that warrant further research. The key findings were that, when very low allowances of pasture are offered to cows, milk production responses were driven mostly by increases in dry matter (DM) intake, and there appeared to be a minimal contribution to increased energy supply from improved whole tract DM digestibility. Differences in milk responses became apparent when >10 kg of total supplement DM was consumed (0.75 : 0.25 concentrate to forage) as PMR. There was a consistent maintenance of milk fat concentration when increasing amounts of concentrates were consumed as PMR, in contrast with supplements consumed in the dairy. There was also a consistent finding that replacing some wheat in the PMR with canola meal resulted in cows consuming more grazed pasture despite the limitations of very low pasture allowances (10–15 kg DM/cow.day, expressed to ground level). This was accompanied by further increases in energy-corrected milk yield. The potential to improve DM intake was further highlighted when pasture allowance was increased, with intake increasing from 3.6% to 4.5% of liveweight (from 20 to 25 kg DM/day for a 550-kg cow). There was also an indication that ~50% of the milk production benefit from PMR can be captured by providing the concentrate supplement as a grain mix in the dairy. There did not appear to be negative impacts of PMR systems on the social and grazing behaviour or health of cows.

A complementary forage system whole-farm study: forage utilisation and milk production

Australian dairy farmers are facing decreasing availability of land and water and declining terms of trade. In this context, systems that are able to increase milk production per ha from home-grown feed, beyond the potential of pasture only, are sought. The complementary forage system (CFS), combining an area with a rotational sequence of two or three forage crops per year with an area of pasture in 35 and 65% of the farm area, respectively, was developed for this purpose. A 2-year whole-farm study with 100 milking cows on 21.5 ha evaluated the feasibility of achieving 25 t DM/ha.year of home-grown feed and converting this into 35 000 L of milk/ha.year by the implementation of such CFS. Utilisation and nutritive value of all forages and milk yields of individual cows were measured daily, body condition and bodyweight weekly, and milk composition fortnightly. Over 26 t DM/ha.year was utilised over the whole CFS farm for the 2 years of the study. This utilised forage had a mean metabolisable energy value of 10.2 MJ/kg DM and crude protein content of 20.5% DM. From this, a total yield of 27 835 L of milk/ha.year from home-grown feed was obtained, which is higher than any other whole-farm study reported in the literature. Daily pasture intake was the variable with the highest impact on milk yield, and significant differences were found in body condition and milk yield of cows calving in either autumn or spring. This study warrants further investigation to determine the environmental and economic sustainability of the implementation of the CFS.

Effect of setting a maximum milking time, from peak lactation, on production, milking time and udder health

AIM

To examine the effect of setting a maximum milking time, from peak lactation until drying-off, on production, duration of milking, and udder health of dairy cows.

METHODS

Forty cows were assigned in twin-pairs to be either milked until cups were removed at a milk flow-rate threshold of 0.35 kg/minute (Control), or until cups were removed at a milk flow-rate threshold of 0.35 kg/minute, or maximum time, whichever came first (MaxT). The maximum time was set by determining the milking time of the 70th percentile cow when ranked from fastest to slowest, irrespective of yield. The milking routine was typical of that practised on dairy farms in New Zealand, and involved no pre-milking preparation. The study began at peak lactation (68 (SD 7) days in milk; DIM) and continued for 26 weeks. Duration of milking and milk yield were measured for each milking. Composition of milk was determined from weekly herd tests, and milk quality from fortnightly somatic cell counts (SCC). Completeness of milking and teat condition were assessed during the study. The bacterial status of quarter milk samples was determined at the beginning and end of the study, and all treated cases of clinical mastitis recorded. ANOVA was used to examine the effect of treatment group on variables of interest.

RESULTS

Total milk, fat and protein yields during the study period did not differ between treatments. On average, 30.3% of the morning and 27.6% of the afternoon milkings of MaxT cows reached the maximum time at which cups were removed, and were therefore shortened. While the average milking time of the slowest-milking cow was longer for the Control compared with MaxT group in Weeks 1-18, the average milking time did not differ between treatments. There was no difference in overall SCC, and the incidence of clinical mastitis, or the percentage of infected quarters at drying-off, was similar for the MaxT and Control cows.

CONCLUSION

The results show that setting a maximum milking time can reduce the milking time of slower-milking cows in a herd without compromising overall herd production and udder health.

CLINICAL RELEVANCE

Although the numbers of cows in the study were small there was no evidence of a major increase in SCC, or subclinical or clinical mastitis when a maximum milking time was set for slower-milking cows.

Development of profitable milk production systems for northern Australia: a field assessment of the productivity of five potential farming systems using farmlets

Farmlets, each of 20 cows, were established to field test five milk production systems and provide a learning platform for farmers and researchers in a subtropical environment. The systems were developed through desktop modelling and industry consultation in response to the need for substantial increases in farm milk production following deregulation of the industry. Four of the systems were based on grazing and the continued use of existing farmland resource bases, whereas the fifth comprised a feedlot and associated forage base developed as a greenfield site. The field evaluation was conducted over 4 years under more adverse environmental conditions than anticipated with below average rainfall and restrictions on irrigation. For the grazed systems, mean annual milk yield per cow ranged from 6330 kg/year (1.9 cows/ha) for a herd based on rain-grown tropical pastures to 7617 kg/year (3.0 cows/ha) where animals were based on temperate and tropical irrigated forages. For the feedlot herd, production of 9460 kg/cow.year (4.3 cows/ha of forage base) was achieved. For all herds, the level of production achieved required annual inputs of concentrates of ~3 t DM/animal and purchased conserved fodder from 0.3 to 1.5 t DM/animal. This level of supplementary feeding made a major contribution to total farm nutrient inputs, contributing 50% or more of the nitrogen, phosphorus and potassium entering the farming system, and presents challenges to the management of manure and urine that results from the higher stocking rates enabled. Mean annual milk production for the five systems ranged from 88 to 105% of that predicted by the desktop modelling. This level of agreement for the grazed systems was achieved with minimal overall change in predicted feed inputs; however, the feedlot system required a substantial increase in inputs over those predicted. Reproductive performance for all systems was poorer than anticipated, particularly over the summer mating period. We conclude that the desktop model, developed as a rapid response to assist farmers modify their current farming systems, provided a reasonable prediction of inputs required and milk production. Further model development would need to consider more closely climate variability, the limitations summer temperatures place on reproductive success and the feed requirements of feedlot herds.

Effects of sowing rate and grazing management of forage rape (Brassica napus) on grazing behaviour and utilisation by dairy cattle

The increase in total factor productivity in the Australian dairy industry over the last 10 years has been low (1.5%). To help address this issue, ‘FutureDairy’ is aiming to increase the production of home-grown feed currently achieved from pastures using a complementary forage-rotation (CFR) system. Forage rape (Brassica napus) is a key component of the CFR; however, it is a complex crop to manage and feed, and the interactions between the behaviour and grazing habits of dairy cattle are unknown. The present experiment investigated the effect of the sowing rate and grazing management of forage rape on the grazing behaviour and forage utilisation of lactating dairy cattle. A field experiment was established, with a forage rape crop planted at three different sowing rates of 2, 3.5 and 5 kg/ha. The crop was grazed using either a ‘multiple grazing’ system, where the forage rape was strip-grazed in a manner to promote regrowth to allow for regrazing, or a ‘take-all grazing’ system, where the forage rape was grazed once only after reaching maximum biomass. The grazing preferences of cows for the sowing rates during the grazing sessions were visually observed and recorded, and forage utilisation was determined from pre-grazing and post-grazing forage availability. Nitrogen (N) deposition from excreta was estimated using stocking density and time spent. Cattle preferred grazing the forage rape sown at 2 kg/ha, but this preference did not result in higher forage utilisation. Grazing method had no effect on forage utilisation or N deposition. Cows should be removed after ~80 min of grazing in a multiple grazing system to ensure future regrowth. Further work is necessary to fully investigate the effects of grazing method on forage utilisation and N deposition, and more accurate external devices and internal markers should be used in the future to provide better estimates of forage utilisation.

Increasing milk production from forage: production systems and extension service preferences of the northern Australian dairy industry

Dairy farms in Queensland were stratified by six regions, three levels of enterprise size (0.25–0.69, 0.7–1.39 or >1.4 ML milk/year) and two rainfall zones (<1000 and >1000 mm/year). Thirteen percent of farmers (89 farms) were surveyed using a prepared questionnaire to ascertain the current production systems, forage management practices and preferences for extension services. Herd size, dairy area, milk production per cow, the use of cropping, pit silage, concentrate input and irrigation input all increased (P < 0.05) with larger enterprises. At the same time the stocking rate on high milk volume farms was almost twice that on smaller farms. The drier zone (<1000 mm/year) was associated with lower stocking rate, higher per cow production and a greater emphasis on cropping and feedpad usage (P < 0.05). The importance of enterprise growth through intensification of the existing farm land resource base is indicated through these findings. Apart from ration formulation, processes used to manage cropping land, irrigation and grazing were primarily based on tradition or intuition. In valuing extension activities, farmers across all enterprise sizes were in general agreement that information products warranted only a small investment. As enterprise size increased, a more individualised and focussed extension service, delivered through targeted discussion groups and personal coaches was favoured.

Feeding time and sequence of forage rape and maize silage does not affect digestibility and rumen parameters in sheep

The objective of this study was to evaluate the effect of time and sequence of feeding forage rape in relation to maize silage on whole tract digestibility and rumen parameters. Three rumen-fistulated castrated male sheep (45 ± 1.2 kg) were individually housed in metabolic crates and fed a diet comprising 25% forage rape, 25% maize silage, 10% concentrate and 40% short rotation ryegrass. The experimental design was a 3 × 3 Latin-square design and treatments were: forage rape fed after maize silage in the morning; forage rape fed before maize silage in the morning; and forage rape fed after maize silage in the afternoon. As the three treatments were identical in composition, the first experimental period comprised a 15-day adaptation period whereas the other two periods had a 7-day adaptation, each followed by 6-day sampling periods for measurement of feed intake and faeces and urine output (day 1–5). Rumen fluid was collected at day 6 of each sampling period and analysed for pH and ammonia concentration. In a subsequent experiment in sacco rumen degradation characteristics of all feeds were measured by incubating nylon bags in the rumen of each sheep. Neither dry matter (DM) intake (mean = 21.2 g/kg liveweight.day) nor whole tract in vivo DM (mean = 0.74) and neutral detergent fibre digestibility coefficients (mean = 0.69) were different (P > 0.05) among treatments. Similarly, neither rumen pH (6.19 ± 0.2) nor ammonia levels (27.2 ± 4.5 mg/100 mL) were affected (P > 0.05) by time of feeding forage rape in relation to maize silage. The calculated efficiency of microbial protein synthesis was similar (P = 0.73) for all treatments [mean = 17 g/day of microbial nitrogen (N) per kg of apparently digested organic matter in the rumen], although the excretion of urinary N was relatively high for all treatments due to high N intake and high degradation of N in forage rape. In conclusion, this study has revealed no effects of time and sequence of feeding forage rape with maize silage on rumen parameters and efficiency of feed utilisation. These results suggest that farmers using these forages can allocate these to animals based on practical convenience.

Comparing irrigated biodynamic and conventionally managed dairy farms. 1. Soil and pasture properties

Ten paired irrigated dairy farms under biodynamic (BD) and conventional (CV) management were compared over a 4-year period (1991–94). The paired farms were located in the irrigation districts of northern Victoria and southern New South Wales and were matched for soil type, climate, cattle breed and farm area. Farms had been practising BD principles for an average of 16 years before the commencement of the study and had not received phosphorus (P) fertiliser for an average of 17 years. The effects of farm management on soil chemical and biological properties and the nutritive properties and botanical composition of pasture were examined at varying sampling times during the study. Soil Olsen extractable P concentrations were consistently 2–3 times higher under CV management at various sampling depths (mean = 22 mg/kg, 0–10 cm), and were generally marginal under BD management in the surface 10 cm (mean = 8.5 mg/kg). Low soil extractable P concentrations were also reflected in consistently lower mean pasture P concentrations under BD management (0.25 compared with 0.35% on CV farms). Lower soil and pasture P concentrations under BD management were the result of a large negative P balance across BD farms (–17 kg P/ha.year). A mean negative P balance under BD management was a result of low P imports (2 kg P/ha.year) in comparison with large quantities of P (19 kg P/ha.year) effectively lost from the farming system through animal products, estimated losses in water runoff and slowly reversible soil P reactions. These results suggest that greater P imports are required to ensure the future sustainability of BD dairy pasture farming systems. There were few differences in soil biological properties, with earthworm weights significantly higher under CV management, but no difference in soil organic carbon, humus concentration, the weight of the organic mat or microbial biomass, between the two management systems.

FutureDairy: a national, multidisciplinary project to assist dairy farmers to manage future challenges - methods and early findings

FutureDairy is a national, multidisciplinary project designed to assist Australian dairy farmers to manage future challenges. FutureDairy is exploring technical, economic and social aspects of technology adoption through an innovative approach that combines methodologies of social research (‘People’), extension (‘System’) and technical research (‘Science’). The technologies being investigated revolve around increasing forage production per unit of land through a complementary forage rotation; evaluating the most efficient use of brought-in feed to increase milk production per ha; and, the incorporation of automatic milking and other technological innovations that would either reduce labour input or allow more precise agriculture. The central strategy of FutureDairy is to utilise ‘knowledge partnerships’ to co-develop knowledge around each of the key areas of investigation; thus a key feature of the project is its linkage with commercial ‘partner’ farmers that explore similar questions to those being investigated at Elizabeth Macarthur Agricultural Institute (NSW Department of Primary Industries), where the technical research is being undertaken. This paper focuses on early findings from the forages module. Work thus far has shown that forage yields in excess of 40 t DM/ha.year are achievable. However, the practicalities of implementing this technology on-farm have already identified new and diverse issues that, unless understood, will jeopardise its effective adaptation by farmers.

Influence of milking frequency on the productivity of dairy cows

Benefits and issues of changing milking frequency from the traditional twice a day are reviewed. Increased efficiency through dairy automation and mechanisation, and the desire to utilise advances in genetic selection, have made milking more frequently than twice a day an attractive option for some farmers. The size of the response to increased milking frequency appeared not to be related to existing milk yield, with the average response to increasing the frequency from 2 to 3 times a day being 3.5–3.8 kg/day. Labour is the single most important cost associated with the decision to increase milking frequency. For this reason, automated milking systems may hold the key to the long-term profitability of challenging cows to produce to their genetic potential. In contrast, reducing milking frequency to once a day has been used to reduce stress on underfed cows or for lifestyle and/or labour considerations. Short-term experiments indicate an average production loss of 21% for once daily relative to twice daily milking. Full lactation experiments suggest greater losses of 35–50%, but there is evidence that cows can adapt to longer milking intervals and this, coupled with increased stocking rate and care to maximise milk removal, may restrict yield losses to less than 10% on a whole-farm basis.

Profitable feeding of dairy cows on irrigated dairy farms in northern Victoria

Milk production per cow and per farm in the irrigated region in northern Victoria have increased dramatically over the past 2 decades. However, these increases have involved large increases in inputs, and average productivity gains on farms have been modest. Before the early 1980s, cows were fed predominantly pasture and conserved fodder. There is now large diversity in feeding systems and feed costs comprise 40–65% of total costs on irrigated dairy farms. This diversity in feeding systems has increased the need to understand the nutrient requirements of dairy cows and the unique aspects of nutrient intake and digestion in cows at grazing. Principles of nutrient intake and supply to the grazing dairy cow from the past 15 years’ research in northern Victoria are summarised and gaps in knowledge for making future productivity gains are identified. Moreover, since the majority of the milk produced in south-eastern Australia is used in the manufacture of products for export, dairy companies have increased their interest in value-added dairy products that better meet nutritional requirements or provide health benefits for humans. Finally, some examples of the impacts of farm system changes on operating profit for some case study farms in northern Victoria are presented to illustrate the need for thorough analysis of such management decisions.