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ABSTRACT: As the scope and scale of New Zealand (NZ) dairy farming increases, farmers and the industry are being challenged by Government and the New Zealand public to address growing environmental concerns. Dairying has come under increasing scrutiny from local authorities tasked with sustainable resource management. Despite recent efforts of farmers and industry to improve resource use efficiency, there is increasing likelihood of further regulatory constraints on water use and nutrient management. This study uses available data on farm-gate nitrogen (N) surpluses and milk production from the Waikato, New Zealand's largest dairying region, together with a farm scale modeling exercise, to provide a perspective on the current situation compared to dairy farms in Europe. It also aims to provide relevant guidelines for N surpluses and efficiencies under NZ conditions. Waikato dairy farms compare favorably with farms in Europe in terms of N use efficiency expressed as L milk/kg farm-gate N surplus. Achievable and realistic good practice objectives for Waikato dairy farmers could be 15,000 L milk/ha (1200 kg milk fat plus protein/ha) with a farm-gate N surplus of 100 kg/ha giving an eco-efficiency (L milk/kg N surplus) of 150, and long-term average nitrate leaching losses of approximately 25-30 kg/ha/yr. This can be achieved by increasing the N conversion efficiency through lower replacement rates (16 versus 22%), lower stocked (< 3 cows/ha) high genetic merit cows (30 L milk/day at peak) milked for longer (277 versus 240 days), feeding effluent-irrigated, home-grown, low-protein supplements to cows on high-protein, grass-clover pastures to dilute N concentration in the diet, removing some of the urinary N from the paddocks during critical times by standing cows on a loafing pad for part of the day, and through lower N fertilizer rates (50-70 kg/ha/yr compared to the norm of 170-200 kg/ha/yr) and using a nitrification inhibitor and gibberellins to boost pasture growth and the former to reduce N leaching.
Journal of Environmental Management 01/2012; 93(1):44-51. · 3.24 Impact Factor
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Environmental Modelling and Software. 01/2011; 26:2-7.
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ABSTRACT: Methodological problems occur in measuring herbage intake and diet quality during short-term (4-24h) progressive defoliations by grazing. Several models were developed to describe pasture component selection by grazing ruminants, particularly sheep. These models contain empirical coefficients to determine preferences that require laborious and data-demanding calibration. The objective was to develop a simple and practical model of changes in diet composition (green:dead) of pastures strip-grazed by dairy cows. The model was based on 3 premises when cows are strip-grazed in relatively homogeneous swards: 1) cows eat dead material only when green leaf and uncontaminated material have been removed; 2) dead material increases toward the bottom of the sward canopy; and 3) cows progressively defoliate pasture in layers. The main simplification in this model was assuming a linear decrease of green mass from the top to the bottom of the sward canopy. Thus, the proportion of green mass in the stratum eaten depended on the proportion of green in the entire sward canopy and its vertical profile. The model offers a simple solution to estimate changes in dietary compositions in pastures strip-grazed by dairy cattle during progressive pasture defoliations. It uses 2 inputs, the green mass proportion of the total herbage mass and the proportion of total herbage mass eaten during grazing. This can be optionally complemented with inputs of herbage chemical composition. The main outputs of the model are the proportions of green and dead herbage mass in the diet. For example, if the green proportion in the sward was 0.5 and the proportion of herbage mass eaten was 0.5, then the diet would be 0.75 green:0.25 dead; assuming 0.8 and 0.4 digestibility for green and dead material, respectively, the diet digestibility would be 0.7.
Journal of Dairy Science 07/2010; 93(7):3074-8. · 2.56 Impact Factor
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ABSTRACT: This study investigated the effect of restricting grazing time on circulating concentrations of ghrelin, nonesterified fatty acids (NEFA), and glucose before, and foraging behavior of dairy cows during, the first grazing session of the day (GS, 0800-1200 h). Forty-eight Holstein-Friesian cows (470 +/- 47 kg of BW; 35 +/- 9 d in milk) were strip-grazed on a perennial ryegrass pasture for either 4 h after each milking (2 x 4), 8 h between milkings (1 x 8), or the 24-h period excluding milking times (CTL). Cows were bled before the GS; plasma was analyzed for ghrelin and serum for glucose and NEFA. Herbage mass was measured pregrazing (0730 h), during and at the end of the GS (1200 h), and postgrazing (24 h after the first measurement). Herbage mass data were fitted to a model to estimate herbage disappearance rates. Herbage intake and bite mass were calculated using herbage mass disappearance and behavioral measurements. Bite rate, eating, searching, ruminating, and idling time were determined during the GS for each cow. No difference in glucose concentration was found between treatments. Concentrations of NEFA and ghrelin were the greatest for cows in the 1 x 8 treatment. Daily herbage intake did not differ between treatments; however, during the GS 1 x 8 had a greater herbage intake than 2 x 4 and CTL. Bite mass differed between treatments and throughout the GS. Bite mass was smallest for CTL during the first 60 min and greatest during the last 90 min, when cows in the 2 x 4 treatment had the smallest bite mass. Cows in 1 x 8 spent the longest time eating and the least time searching and ruminating. Eating time was greatest for 1 x 8 during the first 60 and last 90 min of the GS. Searching time only differed in the second 60 min, when it was the lowest for 1 x 8. Cows from all treatments did not ruminate during the first 120 min. Cows in CTL had the greatest rumination time during the last 90 min. The model fitted to represent dynamics of herbage mass disappearance presented differences in the fractional herbage disappearance rate. There was an interaction between treatment and time in herbage depletion rate. The results of this study present a fuller picture of foraging dynamics during the first 4 h of grazing and its potential relationship with physiological markers of hunger as affected by grazing management.
Journal of Dairy Science 10/2009; 92(9):4572-80. · 2.56 Impact Factor
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ABSTRACT: EXTENDED ABSTRACT Nitrogen discharge from pastoral farming is a major non-point source pollution in some Waikato water bodies. Increases in nitrogen fertilizer use and animal stocking rate of animals have the potential to increase the nitrogen discharge into water. Farms are heterogeneous in terms of their production perspective and pollution potential, which may contribute to differences in nitrogen discharge abatement cost. This article focuses on the economic and environmental impact of agri-environmental policies to abate nitrogen discharges on representative farm types in a Waikato river sub-catchment. Dexcel's WFM is used to simulate various scenarios given spatial and farm system variations. The empirical focus is on a Waikato River Sub catchment, where dairy farming is the predominant land use. Mapping techniques are used to create representative farms within the catchment for simulation. Implementation of agri-environmental policies is likely to be a costly exercise. Hence enforcement demands careful analysis of policies. Extensive evaluation of alternative policies through experiments and monitoring is not feasible at reasonable cost within a foreseeable time span, therefore a modelling approach has considerable promise in informing policy formulations. The objective of this paper is to explore the whole farm model as a potential policy analysis tool in a spatial context with special reference to nitrogen discharge problem from farms in Waikato. This has been achieved by integrating a nitrogen discharge function into the whole farm model. The Dexcel WFM is used for evaluation of the environmental and economic consequences of implementing different nitrogen taxes in heterogeneous farming systems in terms of soil physical variables as well as production structure. The WFM is calibrated to represent the each farming system. Taxation policies are implemented on nitrogen discharges. Three farming systems are considered. Impacts of taxes for each farm type on stocking rate, nitrogen fertiliser applied and nitrogen discharge are estimated by the optimisation module of the WFM. Nitrogen discharge for various policies are estimated by incorporating the estimated meta model for nitrogen discharge as a penalty function in the optimisation process. Optimisation of the WFM has been performed with a specific evolutionary algorithm, a variant of a more common genetic algorithm, known as differential evolution. The strength of the heuristic optimisation adopted is the capability of generating new set of optimum activities under new constraint. This is in contrast to activity analysis, where the optimum is selected among the pre existing activities. The results indicate the heterogeneity among farms in terms of environmental and economic impact of nitrogen policies. The magnitude of the differences in response for a policy among farming systems depends on farm size parameters such as area of farm number of animals and fertilizer use and soil physical parameters such as variability of soil type, topography which influences the input productivity and nitrogen discharge potential. The analytical framework developed aims at general policy implications in the presence of farm heterogeneity. Efficient taxation schemes for reduction of nitrogen discharge should differentiate between farm types rather than use uniform taxes. Environmental policies may provide incentives to adopt best management practices for reducing nitrogen discharges. Future work will integrate this paper's considerations to many more soil and topographic categories and farming systems and extend the optimization routines to accommodate constraint optimisation of physical units of nitrogen discharge.
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ABSTRACT: New Zealand dairy farmers face a tradeoff between profit maximisation and environmental performance. The integrated simulation model presented here enables assessment of the economic and environmental impact of dairy farming with a focus on nitrogen pollution at the catchment level. Our approach extends the value of the DairyNZ Whole Farm Model (Beukes et al., 2005) as an environmental policy tool by building and integrating nitrogen discharge functions for specific soil types and topography using a metamodelling technique. A hybrid model is created by merging the merits of differential evolution and non-linear optimisation to expedite policy simulations, in which farm profits and nitrogen discharges obtained from the differential evolution optimisation process are assembled to form a profit–pollution frontier. This frontier is then subject to constrained optimisation based on non-linear optimisation in order to predict producer responses to alternative pollution control policies. We apply this framework to derive marginal abatement costs for heterogeneous farm types and find that abatement costs for intensive farms are lower than for moderate and extensive farming systems. We further conclude that abatement can be achieved more cheaply using a compulsory standard or threshold tax than using a standard emissions tax.
Environmental Modelling & Software.
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ABSTRACT: New Zealand's commitment to the Kyoto Protocol requires agriculture, including dairy farming, to reduce current greenhouse gas (GHG) emissions by about 20% by 2012. A modeling exercise to explore the cumulative impact of dairy management decisions on GHG emissions and profitability is reported. The objective was to maintain production, but reduce GHG emissions per unit of land and product by improving production efficiency. A farm-scale computer model that includes a mechanistic cow model was used to model an average, pasture-based New Zealand farm over different climate years. A mitigation strategy based on reduced replacement rates was first added to this baseline farm and modeled over the same years. Three more strategies were added, improved cow efficiency (higher genetic merit), improved pasture management (better pasture quality), and home-grown maize silage [increased total metabolizable energy (ME) yield and reduced nitrogen intake], and modeled to predict milk production, intakes, methane, urinary-nitrogen, and operational profit. Profit was calculated from 2006/2007 economic data, where milksolids (fat + protein) payout was NZ$ 4.09 kg−1.1 A nutrient budget model was used with these scenarios and two more strategies added: cows standing on a loafing pad during wet conditions and application of a nitrification inhibitor to pasture (DCD). The nutrient budget model predicted total GHG emissions in CO2 equivalents and included some life cycle analysis of emissions from fertilizer manufacturing, fuel and electricity generation. The simulations suggest that implementation of a combination of these strategies could decrease GHG emissions by 27–32% while showing potential to increase profitability on a pasture-based New Zealand dairy farm. Increasing the efficiency of milk production from forage may be achieved by a combination of high (but realistic) reproductive performance leading to low involuntary culling, using crossbred cows with high genetic merit producing 430 kg milksolids yr−1, and pasture management to increase average pasture and silage quality by 1 MJ ME kg dry matter−1. These efficiency gains could enable stocking rate to be reduced from 3 to 2.3 cows ha−1. Nitrogen from fertilizers would be reduced to less than 50 kg ha−1 yr−1 and include “best practice” application of nitrification inhibitors. Considerable GHG mitigation may be achieved by applying optimal animal management to maximize efficiency, minimize wastage and target N fertilizer use.
Agriculture, Ecosystems & Environment.
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ABSTRACT: A survey amongst stakeholders in 2007 identified wintering systems with less environmental impact and a reliable supply of high quality feed, which are cost effective and simple to implement, as one of the top three issues requiring research and demonstration in the Southland region of New Zealand. This study used a modelling approach to examine the cost effectiveness, exposure to climate-induced risk and major economic drivers of four selected wintering strategies, i.e. (1) grazing a forage brassica crop on support land (Brassica system), (2) grazing pasture on support land (All pasture system), (3) cows fed grass silage, made on the support land, on a loafing pad where effluent is captured (Standoff system), and (4) cows fed grass silage, made on the support land, in a housed facility where effluent is captured (Housed system). The model was driven by virtual climate data generated by the National Institute of Water and Atmospheric Research and economic input data from the DairyNZ Economics Group for the 08/09 season with a milk price of NZ$4.551/kg milksolids (fat + protein). The Housed system had the highest average (± STDEV) operating profit (profit after depreciation but before interest charges) over 35 independently simulated climate years (NZ$743 ± 122/ha), followed by All pasture (NZ$681 ± 197/ha), Standoff (NZ$613 ± 135/ha) and Brassica (NZ$599 ± 212/ha). This ranking was sensitive to the assumptions and treatment of capital costs. The Housed system was the least exposed to climate-induced risk with a coefficient of variation of operating profit of 16% compared to 35% of the Brassica system. The four systems demonstrated different financial strengths and weaknesses that largely balanced out in the end. The Brassica system is a high risk system from an environmental perspective and the All pasture system an unlikely alternative because of scarcity of suitable land. Both the Housed and Standoff systems appear to be cost effective alternatives that allow high control over cow feeding, body condition and comfort over winter. Furthermore, both systems have the potential to provide high control over the storage and release of animal effluent onto land, thus saving fertiliser costs and reducing environmental footprint.
Agricultural Systems 104(7):541-550. · 2.90 Impact Factor
