Records |
Author |
Özkan, Ş.; Hill, J. |
Title |
Implementing innovative farm management practices on dairy farms:a review of feeding systems |
Type |
Journal Article |
Year |
2015 |
Publication |
Turkish Journal of Veterinary and Animal Sciences |
Abbreviated Journal |
Turkish Journal of Veterinary and Animal Sciences |
Volume |
39 |
Issue |
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Pages |
1-9 |
Keywords |
australia; dairy; double-cropping; feeding system; pasture-based; profitability; forage crop systems; south-west victoria; nutritive characteristics; interannual variation; botanical composition; herbage accumulation; growth-rates; pasture; australia; cows |
Abstract |
The Australian dairy industry relies primarily on pasture for its feed supply. However, the variability in rainfall negatively affects plant growth, leading to uncertainty in dryland feed supply, especially during periods of high milk price. New feeding (complementary) systems combining perennial ryegrass with another crop and/or pasture species may have the potential to mitigate this seasonal risk and improve productivity and profitability by providing off-season feed. To date, the majority of research studying the integration of alternative crops into pasture-based systems has focused on substitution and utilization of alternative feed sources. There has been little emphasis on the impacts of integration of forage crops into pasture-based systems. This review focuses on pasture-based feeding systems in southeastern Australia and how transitioning of systems contributes to improved productivity leading to improved profitability for dairy farmers. |
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English |
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Edition |
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ISSN |
1300-0128 |
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Notes |
LiveM |
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no |
Call Number |
MA @ admin @ |
Serial |
4577 |
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Author |
Özkan, Ş.; Farquharson, R.J.; Hill, J.; Malcolm, B. |
Title |
A stochastic analysis of the impact of input parameters on profit of Australian pasture-based dairy farms under variable carbon price scenarios |
Type |
Journal Article |
Year |
2015 |
Publication |
Environmental Science & Policy |
Abbreviated Journal |
Environmental Science & Policy |
Volume |
48 |
Issue |
|
Pages |
163-171 |
Keywords |
carbon tax; operating profit; stochastic dominance; dairy; feeding system; mitigation; cows; systems; efficiency; risk |
Abstract |
The imposition of a carbon tax in the economy will have indirect impacts on dairy farmers in Australia. Although there is a great deal of information available regarding mitigation strategies both in Australia and internationally, there seems to be a lack of research investigating the variable prices of carbon-based emissions on dairy farm operating profits in Australia. In this study, a stochastic analysis comparing the uncertainty in income in response to different prices on carbon-based emissions was conducted. The impact of variability in pasture consumption and variable prices of concentrates and hay on farm profitability was also investigated. The two different feeding systems examined were a ryegrass pasture-based system (RM) and a complementary forage-based system (CF). Imposing a carbon price ($20-$60) and not changing the systems reduced the farm operating profits by 28.4% and 25.6% in the RM and CF systems, respectively compared to a scenario where no carbon price was imposed. Different farming businesses will respond to variability in the rapidly changing operating environment such as fluctuations in pasture availability, price of purchased feeds and price of milk or carbon emissions differently. Further, in case there is a carbon price imposed for GHG emissions emanated from dairy farming systems, changing from pasture-based to more complex feeding systems incorporating home-grown double crops may reduce the reductions in farm operating profits. There is opportunity for future studies to focus on the impacts of different mitigation strategies and policy applications on farm operating profits. (C) 2015 Elsevier Ltd. All rights reserved. |
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ISSN |
1462-9011 |
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LiveM |
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no |
Call Number |
MA @ admin @ |
Serial |
4574 |
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Author |
Wallach, D. |
Title |
Developing skills: how to train adaptive modelers |
Type |
Journal Article |
Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
Volume |
6 |
Issue |
01 |
Pages |
52-53 |
Keywords |
capacity building; skills development; training; integrated modeling |
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English |
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Edition |
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ISSN |
2040-4700 |
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Notes |
Hub, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4683 |
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Author |
Shrestha, S.; Abdalla, M.; Hennessy, T.; Forristal, D.; Jones, M.B. |
Title |
Irish farms under climate change – is there a regional variation on farm responses? |
Type |
Journal Article |
Year |
2015 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
Volume |
153 |
Issue |
03 |
Pages |
385-398 |
Keywords |
change impacts; elevated co2; potential impacts; maize production; united-states; winter-wheat; plant-growth; adaptation; ireland; yield |
Abstract |
The current paper aims to determine regional impacts of climate change on Irish farms examining the variation in farm responses. A set of crop growth models were used to determine crop and grass yields under a baseline scenario and a future climate scenario. These crop and grass yields were used along with farm-level data taken from the Irish National Farm Survey in an optimizing farm-level (farm-level linear programming) model, which maximizes farm profits under limiting resources. A change in farm net margins under the climate change scenario compared to the baseline scenario was taken as a measure to determine the effect of climate change on farms. The growth models suggested a decrease in cereal crop yields (up to 9%) but substantial increase in yields of forage maize (up to 97%) and grass (up to 56%) in all regions. Farms in the border, midlands and south-east regions suffered, whereas farms in all other regions generally fared better under the climate change scenario used in the current study. The results suggest that there is a regional variability between farms in their responses to the climate change scenario. Although substituting concentrate feed with grass feeds is the main adaptation on all livestock farms, the extent of such substitution differs between farms in different regions. For example, large dairy farms in the south-east region adopted total substitution of concentrate feed while similar dairy farms in the south-west region opted to replace only 0.30 of concentrate feed. Farms in most of the regions benefitted from increasing stocking rate, except for sheep farms in the border and dairy farms in the south-east regions. The tillage farms in the mid-east region responded to the climate change scenario by shifting arable production to beef production on farms. |
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ISSN |
0021-8596 1469-5146 |
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Notes |
CropM, TradeM |
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no |
Call Number |
MA @ admin @ |
Serial |
4542 |
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Author |
Ben Touhami, H.; Bellocchi, G. |
Title |
Bayesian calibration of the Pasture Simulation model (PaSim) to simulate European grasslands under water stress |
Type |
Journal Article |
Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
Volume |
30 |
Issue |
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Pages |
356-364 |
Keywords |
Bayesian calibration framework; Grasslands; Pasture Simulation model; (PaSim); integrated assessment models; chain monte-carlo; climate-change; computation; impacts; vulnerability; likelihoods; france |
Abstract |
As modeling becomes a more widespread practice in the agro-environmental sciences, scientists need reliable tools to calibrate models against ever more complex and detailed data. We present a generic Bayesian computation framework for grassland simulation, which enables parameter estimation in the Bayesian formalism by using Monte Carlo approaches. We outline the underlying rationale, discuss the computational issues, and provide results from an application of the Pasture Simulation model (PaSim) to three European grasslands. The framework was suited to investigate the challenging problem of calibrating complex biophysical models to data from altered scenarios generated by precipitation reduction (water stress conditions). It was used to infer the parameters of manipulated grassland systems and to assess the gain in uncertainty reduction by updating parameter distributions using measurements of the output variables. |
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English |
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Edition |
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ISSN |
1574-9541 |
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Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4697 |
Permanent link to this record |