Appraisal of the environmental sustainability of milk production systems in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Science in Life Cycle Management at Massey University, Manawatū, New Zealand

Life Cycle Assessment (LCA) plays an important role in the environmental assessment of agricultural product systems, including dairy farming systems. Generally, an LCA study accounts for the comprehensive resource use and environmental emissions associated with the life cycle of a studied product system. The inventoried inputs and outputs are then transformed into different environmental impact categories using science-based environmental cause-effect mechanisms. There are different LCA modelling approaches (e.g. attributional LCA [ALCA] and consequential LCA [CLCA]) that can be used to address different research questions; however, there is currently no consensus on the most appropriate approach and when to use it. These LCA approaches require different types of data and methodological procedures and, therefore, generate different sets of environmental information which may have different implications for decision-making. In the present research, a series of studies utilising different LCA modelling approaches were undertaken of pasture-based dairy farming systems in the Waikato region (the largest dairy region in New Zealand). The purposes of the studies were to: (i) assess the environmental impacts and identify environmental hotspots of current pasture-based dairy farming systems, (ii) compare environmental hotspots between high and low levels of dairy farm intensification, (iii) investigate the environmental impacts of potential alternative farm intensification methods to increase milk productivity, and (iv) assess the environmental impacts of different future intensified dairy farming scenarios. Twelve midpoint impact categories were assessed: Climate Change (CC), Ozone Depletion Potential (ODP), Human Health Toxicity - non-cancer effects (Non-cancer), Human Health Toxicity - cancer effects (Cancer), Particulate Matter (PM), Ionizing Radiation - human health effects (IR), Photochemical Ozone Formation Potential (POFP), Acidification Potential (AP), Terrestrial Eutrophication Potential (TEP), Freshwater Eutrophication Potential (FEP), Marine Eutrophication Potential (MEP) and Ecotoxicity for Aquatic Freshwater (Ecotox). Firstly, the environmental impacts of 53 existing pasture-based dairy farm systems in the Waikato region were assessed using ALCA. The results showed that both the offfarm and on-farm stages made significant contributions to a range of environmental impacts per kg of fat- and protein-corrected milk (FPCM), and the relative contributions of the stages varied across different impact categories. Farms classified as high intensification based on a high level of farm inputs (i.e. stocking rate, level of nitrogen (N) fertiliser and level of brought-in feeds) had higher impact results than low intensification farms for 10 of 12 impact categories. This was driven mainly by the offfarm stage, including production of brought-in feeds, manufacturing of agrichemicals (e.g. fertilisers and pesticides), and transport of off-farm inputs for use on a dairy farm. The exceptions were the environmental indicators PM, POFP, AP and TEP; their results were determined mainly by ammonia emissions from the on-farm activities. Secondly, environmental consequences resulting from meeting a future increase in demand for milk production (i.e. 20% more milk production per hectare relative to that in 2010/11) by using different farm intensification scenarios for dairy farming systems in the Waikato region were assessed using CLCA. In this study, only technologies/flows that were actually affected by use of different intensification options to increase milk production were accounted for. The identified intensification methods were: (i) increased pasture utilisation efficiency, (ii) increased use of N fertiliser to boost on-farm pasture production, and (iii) increased use of brought-in feed (i.e. maize silage). The results showed that improved pasture utilisation efficiency was the most effective intensification option since it resulted in lower environmental impacts than the other two intensification options. The environmental performance between the other two intensification options varied, depending on impact categories (environmental tradeoffs). Thirdly, prospective ALCA was used to assess the environmental impacts of six prospective (future) dairy farming intensification scenarios in the Waikato region, primarily involving increased stocking rate, that were modelled to increase milk production per hectare by 50% in 2025. In this study, prospective (future) average flows that were derived from extrapolation were accounted for. The potential intensification scenarios were: (i) increased animal productivity (increased milk production per cow), (ii) increased use of mixed brought-in feed, (iii) improved pasture utilisation efficiency, (iv) increased use of N fertiliser to boost on-farm pasture production, (v) increased use of brought-in maize silage, and (vi) replacement of total mixed brought-in feed in the second scenario by wheat grain. The results showed that, apart from improved animal productivity which was considered the best option, improved pasture utilisation efficiency was the second environmentally-preferential option compared with other intensification options for pasture-based dairy farming systems in the Waikato region. There were environmental trade-offs between other intensification options. The present research demonstrated that pasture-based dairy farming systems in the Waikato region contribute to a range of environmental impacts. More intensive farming systems not only have increased milk productivity (milk production per hectare) but also increased environmental impacts (per kg FPCM) in most environmental impact categories. Farm intensification options associated with improved farm efficiency (e.g. animal productivity or pasture utilisation efficiency) are promising as they have lower environmental indicator results (per kg FPCM) compared with other intensification methods. Increased use of off-farm inputs (e.g. N fertilisers and brought-in feeds) increases some, and decreases other, environmental indicator results. Therefore, decision-making associated with choice of alternative farm intensification options beyond farm efficiency improvements will require prioritisation between different environmental impacts and/or focusing on the ability of key decision-makers to effect change (for example, by distinguishing between local and global activities contributing to environmental impacts). The present research has shown that different LCA modelling approaches can be used in a sequential manner to maximise the usefulness of environmental assessment. Initially, ALCA (based on current average flows) can be used to identify environmental hotspots in the life cycle of dairy farming systems. This will generate environmental information that can assist in selection of improvement options. Subsequently, the improvement options selected should be evaluated using CLCA (based on marginal flows). This will produce comparative environmental information resulting from implementing the selected improvement options, strategies or policies in relation to a non-implementation scenario, when the wider contribution of co-products is accounted for. Finally, prospective ALCA (based on future average flows) can be used to assess total or net environmental benefits

Change in dry matter and nutritive composition of Brachiaria humidicola grown in Ban Thon soil series

This experiment was conducted to determine the change in dry matter and nutritive composition of Humidicola grass (Brachiaria humidicola) grown in Ban Thon soil series (infertility soil) as a function of growth age. One rai (0.16 ha) of two-year-old pasture of fertilised Humidicola grass was uniformly cut and the regrowth samples were collected every twenty days. The samples were subjected to analysis for dry matter content and nutritive composition, i.e. crude protein, ash, calcium, phosphorus, neutral detergent fibre, acid detergent fibre, and acid detergent lignin. The results showed that while the yields of available forage and leaves increased curvilinearly (quadratic, p<0.05), the stem yield increased linearly (p<0.05) over sampling dates. The highest biomass accumulation rate was numerically observed between 40-60 days of regrowth. The concentrations of crude protein, ash, calcium and phosphorus decreased curvilinearly (quadratic, p<0.05) with advancing maturity and reached the lowest flat after 60 days of regrowth. The cell wall components, i.e. NDF, ADF and ADL, increased over the experimental period and reached the highest plateau at 40 days of regrowth. It was concluded that Humidicola grass should be grazed or preserved at the regrowth age of not over 60 days to maximise the utilisation of the grass

The Need and Potential of Biosensors to Detect Dioxins and Dioxin-Like Polychlorinated Biphenyls along the Milk, Eggs and Meat Food Chain

Dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) are hazardous toxic, ubiquitous and persistent chemical compounds, which can enter the food chain and accumulate up to higher trophic levels. Their determination requires sophisticated methods, expensive facilities and instruments, well-trained personnel and expensive chemical reagents. Ideally, real-time monitoring using rapid detection methods should be applied to detect possible contamination along the food chain in order to prevent human exposure. Sensor technology may be promising in this respect. This review gives the state of the art for detecting possible contamination with dioxins and DL-PCBs along the food chain of animal-source foods. The main detection methods applied (i.e., high resolution gas-chromatography combined with high resolution mass-spectrometry (HRGC/HRMS) and the chemical activated luciferase gene expression method (CALUX bioassay)), each have their limitations. Biosensors for detecting dioxins and related compounds, although still under development, show potential to overcome these limitations. Immunosensors and biomimetic-based biosensors potentially offer increased selectivity and sensitivity for dioxin and DL-PCB detection, while whole cell-based biosensors present interpretable biological results. The main shortcoming of current biosensors, however, is their detection level: this may be insufficient as limits for dioxins and DL-PCBs for food and feedstuffs are in pg per gram level. In addition, these contaminants are normally present in fat, a difficult matrix for biosensor detection. Therefore, simple and efficient extraction and clean-up procedures are required which may enable biosensors to detect dioxins and DL-PCBs contamination along the food chain

Pangola grass as forage for ruminant animals: a review

Abstract This review focuses on the introduction and investigation of pangola grass as a tropical forage species especially in Thailand. Pangola grass (Digitaria eriantha Steud., synonym D. decumbens) is one of recent examples of grasses that have been successfully introduced to Southeast Asia and is often considered as one of the highest quality tropical grasses popularly grown as pasture. Pangola grass is utilized extensively as grass for animal grazing, hay and silage making. Its crude protein content is commonly in the order of 5 to 14% of dry matter and may exceed 15% of dry matter with young regrowth under high fertilization. It has been documented that the type and number of ruminants receiving pangola grass can determine the success of its use. Results obtained when pangola grass in fresh, hay or silage form was fed to ruminant animals as supplements showed better performances in body weight gain, feed conversion ratio, carcass yield, meat quality, and milk yield and composition. In conclusion, pangola grass is a promising forage and a source of high quality feed for ruminant animals in tropical countries.</jats:p

Life cycle environmental impacts of future dairy farming intensification scenarios: A comparison of intensified systems based on nitrogen fertiliser versus maize silage

This study compared multiple life cycle environmental impacts derived from two prospective farm intensification methods to support potential increased milk production in the Waikato region of New Zealand in 2025: (i) extra nitrogen (N) fertiliser at 137 kg N per ha (N scenario), and (ii) extra brought-in maize silage at 2,275 kg dry matter per ha (MS scenario). The cradle-to-farm gate perspective (i.e. environmental emissions starting from an extraction of raw material through to production of milk at the farm gate were accounted for) was used as a system boundary with 1 kg of fat- and protein-corrected milk as a functional unit. Allocation of environmental burdens between co-products of the inflows were based on an economic relationship, and for the outflow (i.e. milk and dairy meat), allocation was based on biophysical relationship (i.e. relative feed requirement for each of co-products). The results demonstrate environmental trade-offs between the two farm intensification methods, highlighting the relevance to assess a wide range of environmental impact indicators when doing an environmental assessment. The environmentally preferable intensification method will depend on priority and scale of environmental indicators of concern.falsePublishedPalmerston North, New Zealan

Life cycle assessment of dairy production systems in New Zealand

Life Cycle Assessment (LCA) is a standardised approach to evaluate resource use and environmental emissions of a production system or product. It covers multiple stages including raw material extraction, production of farm inputs and farm emissions (i.e. cradle-to-farm-gate stages), and can extend to milk processing, transport, consumer use and waste stages. LCA has been applied in agriculture over the past decade to examine the total greenhouse gas (GHG) emissions associated with products such as milk. More recently it has been applied in assessing a range of environmental emissions. For example, the current European Product Environmental Footprinting initiative covers multiple environmental impact categories. This paper reports on studies using LCA to evaluate effects of dairy intensification in the Waikato region of New Zealand (NZ; using DairyNZ DairyBase farm survey data) covering cradle-to-farm-gate stages. Initial focus was on the carbon footprint of milk (total GHG emissions) and the effects of intensification using different brought-in supplementary feeds. While GHG emissions per on-farm hectare increased with dairy intensification, there was little difference in GHG emissions per kg milk. However, the results depended on the type of feed used, with highest emissions from use of palm kernel expeller. Recent research extended the use of LCA to evaluate a wider range of environmental impact indicators (up to 12) across the range of intensification levels on the Waikato farms. This evaluation showed an increase in emissions per kg milksolids for the high intensification level compared to the low intensification level of 5-32% depending on the impact indicator, with the highest increase for Freshwater Ecotoxicity. Across many environmental impact indicators, the off-farm stages of agrichemical (fertilisers and pesticides) production and production of off-farm feeds were significant contributors to total environmental emissions. This has implications for practices to reduce the environmental impacts from NZ agricultural products