Inter-Annual Variability in Pasture Herbage Accumulation in Temperate Dairy Regions: Causes, Consequences, and Management Tools

Inter-annual variation in pasture herbage accumulation rate (HAR) is common in temperate dairy regions, posing challenges for farmers in the management of dairy cow feeding and of pasture state. This paper reviews the biophysical factors that cause inter-annual variation, considers some of its consequences for the efficient harvest of pasture, and discusses the basis for decision rules and support tools that are available to assist New Zealand and Australian farmers to help manage the consequences of an imbalance between feed supply and demand. These tools are well-grounded in scientific research and farmer experience, but are not widely used in the Australasian dairy industries. Some of the reasons for this are discussed. Inter-annual variability in HAR cannot be removed, even with inputs such as irrigation, but reliable forecasts of pasture HAR for a month or more could greatly improve the effectiveness of operational and tactical decision-making. Various approaches to pasture forecasting, based on pasture growth simulation models, are presented and discussed. Some of these appear to have reasonable predictive ability. However, considerably more development work is needed to: (1) prove their effectiveness; and (2) build the systems required to capture real-time, on farm data for critical systems variables such as pasture herbage mass and soil water content to combine with daily weather data. This technology presents an opportunity for farmers to gain greater control over variability in pasture-based dairy systems and improve the efficiency of resource use for profit and environmental outcomes

Modelling dairy grazing systems: an integrated approach

This thesis describes a management décision-support system for dairy grazing systems based on simulation and multiple criteria decision-making (MCDM) models.Appropriate selection of holistic management strategies for livestock farming systems requires: 1) understanding of the behaviour of, and interrelations between, the different parts of the system, 2) knowledge of the basic objectives of the decision-maker managing such enterprise, and 3) understanding of the system as a whole in its agro-ecoregional context.Increasing economic and environmental pressures on livestock production systems have created the need to re-evaluate current management practices and to study new alternatives to ensure their sustainability. As a consequence, the demand for décision-support systems based on mathematical models has increased in the past years. Validated simulation models provide cost-effective means to represent the dynamics of the system and its components, while MCDM models allow for appropriate selection of resource allocation strategies depending on the different objectives and management 'styles' of particular individuals. Integration of both mechanisms provides the necessary elements for efficient décision- support at farm or ecoregional level.A décision-support system based on these techniques has been built to represent pastoral dairy production systems. The biological aspects (grass growth; grazing; digestion and metabolism; animal performance, and herd dynamics) are represented by simulation studies under a variety of management regimes. The outputs from the simulation runs (such as pasture utilisation, stocking rates, milk yields, fertilizer use, etc.) are used as data input to the MCDM models, and the latter have been used to select the management strategies which make the most efficient use of the farm's resources (i.e. land, animals, pastures).Examples are given with reference to highland dairy farming in Costa Rica. Nevertheless, the model frameworks are generic and can be adapted to different farming systems or ruminant species. The effect of model formulation and sensitivity, different decision-maker objectives, and/or activity or constraint definitions on management strategy selection are analysed. Future areas of research to expand this work to other livestock farming systems and to integrate other related disciplines into this décision-support framework are also discussed

Quantitative analysis of behaviour of grazing dairy cows

This research thesis describes the quantitative analysis of behaviour of grazing dairy cows in terms of sward height (SH) in combination with the length of the grazing session (grazing duration, GD), the time of allocation of fresh pasture and the type of carbohydrate supplement offered. A review of the literature (Chapter 2) identified that there was limited information on the combined affects of SH and GD on behaviour, herbage dry matter intake (DMI) and intake rate (IR) of dairy cows grazing sub-tropical pastures and how these interact to influence sward structure. Also, there was limited information on how SH x GD, time of allocation of fresh pasture and type of carbohydrate supplement offered affects the temporal patterns of behaviour and the subsequent time-dependent probabilities. In this current study, 2 levels of SH (10 and 13cm) and 5 levels of GD (1, 2, 4, 8 and 15h) were used to quantify the effects of SH and GD on dairy cow grazing behaviour, IR and herbage DMI. Sward height significantly (P70% of their total herbage DMI within the first 4h GD. Quantification of the sward profiles after each SH x GD combination showed that dairy cows grazing kikuyu using the management described in this current study did not graze at random. ... The results from this current thesis highlight the factors that either encourage or discourage grazing by dairy cows and should also help to improve decision tools used for pasture rotation, supplementary feeding and stocking density

Modeling Greenhouse Gas Emissions and Net Return Implications for Cow-Calf Producers in the Ozark Highlands

Cow-calf producers in the Ozark Highlands region are under continuous pressure to improve economic efficiency. Additionally, estimating greenhouse gas (GHG) emissions from cow-calf and forage production processes may become increasingly important as policy makers seek to mitigate or reduce agriculture\u27s role in climate change. As such, this analysis had three objectives. Objective 1: Provide a model that could be used by cow-calf producers, extension agents, and researchers to evaluate GHG and net return (NR) repercussions when modifying site characteristics, production methods, and inputs. Objective 2: Develop a user guide such that the methodology for estimating cow-calf GHG emissions and NR can be adapted to other regions and livestock / cropping enterprises based on different site characteristics, production methods, and inputs. Objective 3: Using the tool, estimate the profit-maximizing hay and pasture forage species composition, cow stocking rate, and seasonal calving distribution for three sizes of operations under four fertilization strategies. A spreadsheet-based model was developed at the University of Arkansas as part of this dissertation and an M.Sc thesis. It lends itself for extension to the Ozark Highlands eco-region by helping producers analyze changes in GHG emissions and NR that result when production methods, inputs, and site characteristics are changed. Benchmark farm operations and default parameters were provided to represent three sizes of farm operations (Small, Medium, and Large). The reference manual, developed as part of this analysis, outlines the scientific principles and methodology utilized to estimate GHG emissions and NR. In addition to the producer and extension use, the tool allows researchers to estimate profit-maximizing inputs or production methods for specific farm parameters and scenarios. Using the profit-maximizing function of the model the optimal forage species composition, calving distribution, and stocking rate were estimated for three operation sizes (Small, Medium, and Large) and four fertilization strategies (Lime, Low, Medium, and High). For the scenarios modeled, results revealed that a January-February calving season provided the greatest NR and that matching forage species composition with calving distribution was an important factor in determining operation profitability. Additionally, result from the optimization of calving season, forage species composition, and stocking rate suggested that GHG emissions from cow-calf production can be reduced

Cow breed, stocking rate, and calving date affect the profitability of pasture-based dairy farms

Data from two multi-year experiments undertaken at the DairyNZ research farm, No 2. Dairy were collated and analysed. The effects of: 1) Breed (Jersey or Holstein-Friesian; JER, HF) at optimum or high comparative stocking rates (CSR; 80 or 100 kg body weight (BW)/t dry matter (DM) of feed available; CSR80 and CSR100, respectively); and 2) Changing the mean calving date (January, April, July, or October; JAN, APR, JUL, OCT) on biophysical measurements (i.e., milk production, pasture growth) and farm profitability were determined. Changing these strategic management variables affected the amount of pasture grown and consumed. For example, there was an interaction between breed and CSR in many of the measured pasture and milk production variables in experiment one; whilst, in experiment two, changes in the month of calving affected pasture dry matter intake (DMI) in early-mid and mid-late lactation, and annual milk production. Annual pasture production was greatly reduced at CSR100 on the HF farmlet, but not on the JER farmlet. Month of calving affected pasture DMI during early-mid lactation and mid-late lactation. A breed x CSR interaction reduced milk production per cow at CSR100, an effect that was greater in the HF breed than in the JER. Month of calving affected milk production per cow with the JUL herd producing the highest yield, compared with the JAN, APR and OCT herds. Other breed x CSR interactions were also detected: JER cows had the lowest mean days in milk (DIM) to first heat at both CSR80 and 100; furthermore, there were negative effects of an increase in CSR from 80 to 100 kg body weight/t DM feed in the HF breed on DIM to first heat. Total metabolisable energy (ME) requirements per cow was affected by a breed x CSR interaction. At CSR80, the HF used more ME per cow than the JER, whilst at CSR100, both breeds used less total ME per cow than at CSR80, but the HF again used more than the JER. From a profitability perspective, HF cows had a greater operating profit per hectare than JER at CSR80; however, JER cows were more profitable at CSR100. The JUL herd had the most profitable farm system, in both the base economic model and stochastic model. Results of the stochastic modelling with no premium included in the milk payment (NZ$/kg fat and protein) variable revealed the operating profit per hectare was greatest for the JUL herd, compared with the JAN, APR, and OCT herds. Inclusion of a premium for milk supplied during 16 May to 15 July in the milk payment (NZ$/ kg fat and protein) variable as well as a downward adjustment in milk price for JUL calving cows because of the high milk production peak in spring did not overcome this difference in profitability. Therefore, the JUL calving scenario was most profitable. The APR seasonal calving strategy resulted in a 10% reduction in operating profit per hectare, compared with the JUL herd, while the JAN and OCT strategy had the lowest operating profit per hectare

Source-tracking cadmium in New Zealand agricultural soils: a stable isotope approach

Cadmium (Cd) is a toxic heavy metal, which is accumulated by plants and animals and therefore enters the human food chain. In New Zealand (NZ), where Cd mainly originates from the application of phosphate fertilisers, stable isotopes can be used to trace the fate of Cd in soils and potentially the wider environment due to the limited number of sources in this setting. Prior to 1997, extraneous Cd added to soils in P fertilisers was essentially limited to a single source, the small pacific island of Nauru. Analysis of Cd isotope ratios (ɛ114/110Cd) in Nauru rock phosphate, pre-1997 superphosphate fertilisers, and Canterbury (Lismore Stony Silt Loam) topsoils (Winchmore Research Farm) has demonstrated their close similarity with respect to ɛ114/110Cd. We report a consistent ɛ114/110Cd signature in fertiliser-derived Cd throughout the latter twentieth century. This finding is useful because it allows the application of mixing models to determine the proportions of fertiliser-derived Cd in the wider environment. We believe this approach has good potential because we also found the ɛ114/110Cd in fertilisers to be distinct from unfertilised Canterbury subsoils. In our analysis of the Winchmore topsoil series (1949-2015), the ɛ114/110Cd remained quite constant following the change from Nauru to other rock phosphate sources in 1997, despite a corresponding shift in fertiliser ɛ114/110Cd at this time. We can conclude that to the present day, the Cd in topsoil at Winchmore still mainly originates from historical phosphate fertilisers. One implication of this finding is that the current applications of P fertiliser are not resulting in further Cd accumulation. We aim to continue our research into Cd fate, mobility and transformations in the NZ environment by applying Cd isotopes in soils and aquatic environments across the country