Intake By Lactating Goats Browsing On Mediterranean Shrubland,
2023
Istituto Zootecnico e Caseario per la Sardegna, Italy
Intake By Lactating Goats Browsing On Mediterranean Shrubland, M. Decandia, G. Pinna, A. Cabiddu, G. Molle
International Grassland Congress Proceedings
In Mediterranean regions goat feeding systems are mainly based on shrubland that contain a wide variety of species. There are only a few equations for predicting feed intake of stall-fed goats (Luo et al., 2004). The objective of this study was to develop a model for predicting the intake of lactating goats browsing on Mediterranean shrubland.
Adapting The Cropgro Model To Predict Growth And Perennial Nature Of Bahiagrass,
2023
University of Florida
Adapting The Cropgro Model To Predict Growth And Perennial Nature Of Bahiagrass, S. J. Rymph, K. J. Boote, J. W. Jones
International Grassland Congress Proceedings
The objective of this research was to modify an existing crop growth model for ability to predict growth and composition of bahiagrass (Paspalm notatum Flügge) in response to daily weather and management inputs. The CROPGRO–CSM cropping systems model has a generic, process-oriented structure that allows inclusion of new species and simulating cropping sequences and crop rotations. An early adaptation of CROPGRO-CSM “species files” for bahiagrass over-predicted growth during late fall through early spring, and totally failed in re-growth if all foliage was lost from freeze damage. Revised species parameters and use of “pest damage” offered only a partial solution. …
The Impact Of Concentrate Price On The Utilization Of Grazed And Conserved Grass,
2023
Teagasc, Ireland
The Impact Of Concentrate Price On The Utilization Of Grazed And Conserved Grass, P. Crosson, P. O'Kiely, F. P. O'Mara, M. J. Drennan, M. Wallace
International Grassland Congress Proceedings
A linear programming model was designed and constructed to facilitate the identification of optimal beef production systems under varying technical and policy scenarios. The model operates at a systems level and most activities that could occur in Irish spring-calving, suckler beef production systems are included. In this paper, the components of the model are described together with a simple application of the model involving changing concentrate prices.
Modelling Urine Nitrogen Production And Leaching Losses For Pasture-Based Dairying Systems,
2023
Massey University, New Zealand
Modelling Urine Nitrogen Production And Leaching Losses For Pasture-Based Dairying Systems, I. M. Brookes, D. J. Horne
International Grassland Congress Proceedings
Urine from dairy cattle grazing pastures with high crude protein (CP) concentrations is a major source of N lost in drainage water from New Zealand farms. This paper provides predictions of urinary N leaching losses for a range of stocking rates and levels of supplementation.
A Model To Evaluate Buying And Selling Policies For Growing Lambs On Pasture,
2023
Massey University, New Zealand
A Model To Evaluate Buying And Selling Policies For Growing Lambs On Pasture, P. C. H. Morel, B. Wildbore, I. M. Brookes, P. R. Kenyon, R. W. Purchas, S. Ramaswami
International Grassland Congress Proceedings
In pastoral sheep finishing systems, farmers aim to maximize profitability by deciding on when and how many animals to buy and/or sell, while taking into account feed availability and current prices. This paper describes a stochastic lamb growth simulation model with a set of heuristic rules, which has been developed to financially evaluate different management strategies for growing lambs on pasture.
Sensitivity Analysis Of A Growth Simulation For Finishing Lambs,
2023
Massey University, New Zealand
Sensitivity Analysis Of A Growth Simulation For Finishing Lambs, P. C. H. Morel, B. Wildbore, I. M. Brookes, P. R. Kenyon, R. W. Purchas, S. Ramaswami
International Grassland Congress Proceedings
A stochastic lamb growth simulation model with a set of heuristic rules has been developed to evaluate management strategies for a solely pastoral grazing system in New Zealand (Morel et al., 2005). In the present paper the results of a sensitivity analysis for this model are presented.
Modelling Winter Grass Growth And Senescence,
2023
Teagasc, Ireland
Modelling Winter Grass Growth And Senescence, D. Hennessy, S. Laidlaw, M. O'Donovan, P. French
International Grassland Congress Proceedings
In temperate climates, because net grass growth in winter is low, most grass growth models deal with the main growing season (Mar-Oct in the N Hemisphere), with little emphasis on grass growth in winter (Nov-Feb). However, grass tissue turns over continuously (Hennessy et al., 2004) and the fate of herbage entering the winter is important in extended grazing season systems. This study aimed to model winter grass growth for the period 15 Oct 2001 to 28 Jan 2002 for a range of autumn closing dates (1 Sep, 20 Sep and 10 Oct) by modifying an existing model, so that …
Effect Of Nitrogen On The Radiation Use Efficiency For Modelling Grass Growth,
2023
Catholic University of Louvain, Belgium
Effect Of Nitrogen On The Radiation Use Efficiency For Modelling Grass Growth, R. Lambert, A. Peeters
International Grassland Congress Proceedings
When nitrogen (N) is not at a sufficient level to permit maximum growth rate, dry matter production is reduced. Models of plant growth in relation to solar radiation intercepted by the crop have been largely used. According to these models, N deficiency can act on the leaf extension and thus on the quantity of radiation intercepted by the crop, but also by reducing the radiation use efficiency of the crop (RUE) (Bélanger, 1990). The effect of N on the RUE of ryegrass swards is determined and discussed.
The Meal Criterion Estimated In Grazing Dairy Cattle: Evaluation Of Different Methods,
2023
Wageningen University, The Netherlands
The Meal Criterion Estimated In Grazing Dairy Cattle: Evaluation Of Different Methods, P. A. Abrahamse, D. Reynaud, J. Dijkstra, S. Tamminga
International Grassland Congress Proceedings
The meal criterion (MC) has been found a useful tool to pre-treat intake behaviour data in dairy cows. It was defined as the longest interval between bouts that belong to the same meal (Tolkamp & Kyriazakis, 1999), necessary to cluster bouts to meals. The method of Yeates et al. (2001) calculating the loge-transformed intervals between bouts and using the Gaussian-Gaussian-Weibull (GGW) model to calculate the MC was found to provide the best estimation of the MC in biological as well as statistical terms. However, in grazing dairy cattle the MC-estimation has only been carried out by Rook …
Radiation Use Efficiency Of Ryegrass: Determination With Non Cumulative Data,
2023
Catholic University of Louvain, Belgium
Radiation Use Efficiency Of Ryegrass: Determination With Non Cumulative Data, R. Lambert, A. Peeters
International Grassland Congress Proceedings
The growth of a crop is generally described as biomass accumulation per unit time. Monteith (1977) developed a model of growth where biomass accumulation is related to solar radiation intercepted by the crop. This model has been largely used for different crops. The conversion factor between radiation absorbed or intercepted by the crop and the biomass production is called “radiation use efficiency” or “dry matter radiation quotient”. Radiation use efficiency (RUE) is usually calculated as the regression coefficient of the linear relationship between crop biomass measured repeatedly during growth and cumulated intercepted or absorbed solar radiation. Demetriades-Shah et al. …
Modelling The Digestibility Decrease Of Three Grass Species During Spring Growth According To The Age Of The Grass, The Thermal Age And The Yield,
2023
Catholic University of Louvain, Belgium
Modelling The Digestibility Decrease Of Three Grass Species During Spring Growth According To The Age Of The Grass, The Thermal Age And The Yield, M. E. Salamanca, R. Lambert, M. Gomez, A. Peeters
International Grassland Congress Proceedings
The nutritive value of forage changes during growth. For the protein content, a general evolution curve was found with the yield increase (Salette & Lemaire, 1984). The digestibility of the organic matter decreases during growth as cellulose and lignin content increase. Regrowth age is the main factor, which explains the digestibility decrease (Demarquilly & Jarrige, 1981). The crop age can be expressed in number of growth days but also in thermal age (cumulated temperature). We compared the digestibility change of three grass species during spring growth for two years as a function of yield increase, thermal age or number of …
Visual Modelling Of Alfalfa Growth And Persistence Under Grazing,
2023
University of Kentucky
Visual Modelling Of Alfalfa Growth And Persistence Under Grazing, S. R. Smith Jr., L. Muendermann, A. Singh
International Grassland Congress Proceedings
A ‘virtual’ alfalfa plant model was developed at the University of Manitoba in Canada as part of a comprehensive grazing research project. This model shows an alfalfa plant ‘growing’ on a computer screen and the plant’s response to grazing (similar to time-lapse photography). The original model was constructed by Singh (2005) to show the research potential of visually modelling alfalfa plant growth. The ability to visually ‘grow’ a plant on a computer screen also offers tremendous opportunities for teaching and extension. Detailed morphological measurements were used in the construction of Singh’s model, based on single plants subjected to the following …
A New Agro-Meteorological Simulation Model For Predicting Daily Grass Growth Rates Across Ireland,
2023
Teagasc, Ireland
A New Agro-Meteorological Simulation Model For Predicting Daily Grass Growth Rates Across Ireland, R. P. O. Schulte
International Grassland Congress Proceedings
Grass growth rates and herbage yields depend on weather conditions, soil characteristics and grassland management and differ from year to year and from site to site. In the past, grass growth has been predicted using both mechanistic and statistical models. The accuracy of mechanistic models is commonly insufficient for practical application, while statistical models generally apply to one test site only (e.g. Han et al., 2003). In this paper a semi-empirical grass growth model is presented which is numerically accurate, but which can be applied to contrasting sites across Ireland at the same time.
Pâtur’In: A User-Friendly Software Tool To Assist Dairy Cow Grazing Management,
2023
INRA, France
Pâtur’In: A User-Friendly Software Tool To Assist Dairy Cow Grazing Management, L. Delaby, J. L. Peyraud, P. Faverdin
International Grassland Congress Proceedings
The feeding of dairy cows at pasture presents many technical, economic and environmental advantages, while benefiting from a very favourable image. However, the management of grazed land is a complex game of strategy in which the farmer applies decisions in order to manage two unstable and uncertain fluxes of change: growth of grass and intake of the herd. Many tools (platemeter, etc.) and overall methods (local stocking rate references, farm cover, etc.) have been developed as aids to grazing management. Nevertheless, few decision-support systems are currently available that make it possible to anticipate and assess the consequences of a given …
A Farmer-Based Decision Support System For Managing Pasture Quality On Hill Country,
2023
Massey University, New Zealand
A Farmer-Based Decision Support System For Managing Pasture Quality On Hill Country, I. M. Brookes, D. I. Gray
International Grassland Congress Proceedings
Despite considerable effort to promote formal feed budgeting in New Zealand, survey data suggests it is only adopted by 20% of farmers (Nuthall & Bishop-Hurley, 1999). Recent work (Gray et al., 2003) has identified that farmers may use a different approach - micro-budgeting - to manage feed. Rather than operate at a whole farm level, micro-budgeting focuses at the paddock level. This paper describes micro-budgeting as used by a high performing hill country sheep and cattle farmer to manage pasture quality over spring and a decision support model developed to help other farmers undertake this process
Understanding Livestock Grazing Impacts: A Decision Support Tool To Develop Goal-Oriented Grazing Management Strategies,
2023
University of California
Understanding Livestock Grazing Impacts: A Decision Support Tool To Develop Goal-Oriented Grazing Management Strategies, S. J. Barry, K. Guenther, G. Hayes, R. Larson, G. Nader, M. Doran
International Grassland Congress Proceedings
Managing grasslands in the western United States has become much more complex over the last few decades. A century ago the goal was to survive as a livestock producer, and grassland management involved using forage effectively and overcoming obstacles such as predators and shortages of water and feed. Today the successful grassland manager also needs to consider the diversity and health of the ecosystem as a whole. Livestock grazing can negatively and/or positively affect riparian areas, sensitive plants, and endangered wildlife. Since the impact on a specific factor will vary depending on the timing, intensity and class of livestock grazed, …
Enhancing Grasslands Education With Decision Support Tools,
2023
University of New England, Australia
Enhancing Grasslands Education With Decision Support Tools, H. G. Daily, J. M. Scott, J. M. Reid
International Grassland Congress Proceedings
We have successfully used Decision Support Tools (DST) relevant to the management of grazing enterprises to enhance problem solving skills of undergraduates in Australia. Tools such as GrassGro™ (Moore et al., 1997) and GrazFeed™ (Freer et al., 1997) are accessed from a central server by authorised users at many widely dispersed Universities across Australia using remote access to thin-client technology via an Internet portal. This has been supplemented with training for lecturers. Experience in developing appropriate teaching and learning materials and the reliable delivery of simulation software to many clients has enhanced learning outcomes at tertiary level. We …
A Farmer Friendly Feed Budget Calculator For Grazing Management Decisions In Winter And Spring,
2023
Department of Agriculture Western Australia
A Farmer Friendly Feed Budget Calculator For Grazing Management Decisions In Winter And Spring, M. Curnow, M. W. Hyder
International Grassland Congress Proceedings
The Western Australian (WA) environment is Mediterranean with annual legume/grass pastures and a 6 month growing season. In autumn where over grazing can impact pasture establishment and in spring, prior to senescence, when under grazing can mean significant losses of efficiency are crucial times for grazing management. Pasture utilisation is typically low (25-35%) due to conservative stocking regimes; key to increasing productivity is increasing pasture utilisation (Grimm, 1998). Increased levels of productivity require farmer sophistication in the way they feed budget. To this end, satellite technology is being used to provide farmers in southern Australia with weekly estimates of pasture …
Simulation Of Pasture Phase Options For Mixed Livestock And Cropping Enterprises,
2023
CSIRO Plant Industry, Australia
Simulation Of Pasture Phase Options For Mixed Livestock And Cropping Enterprises, L. Salmon, A. D. Moore, J. F. Angus
International Grassland Congress Proceedings
In southern Australia, 50% of grain-producing farms also run beef and/or sheep enterprises. Legume pasture leys are used to replace soil nitrogen and manage crop disease risks. Deep-rooted perennials, predominantly lucerne (Medicago sativa), are replacing annual Trifolium subterraneum-based leys to increase pasture production. They also have the environmental benefits of limiting soil acidity, rising water tables and dryland salinity. After recent droughts depletion of soil water by lucerne has penalised wheat yields. Decision support tools can help farmers evaluate the long-term effects of grazed annual and perennial leys on animal and crop production at the whole farm …
Grasscheck: Monitoring And Predicting Grass Production In Northern Ireland,
2023
Agricultural Research Institute of Northern Ireland, UK
Grasscheck: Monitoring And Predicting Grass Production In Northern Ireland, P. D. Barrett, A. S. Laidlaw
International Grassland Congress Proceedings
No abstract provided.
