Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2003
Authors
Grete StokstadAbstract
Several factors influence the value of a lamb carcass throughout the slaughtering season, and therefore have implications for the optimal slaughtering time of lambs. The expected price of the carcass varies through the season due to: Variations in the weight of the lambs, and the growth through the season. The classification of the carcass, i.e., the price per kg changes as the lambs grow. The prices of the various quality changes throughout the season. The quality of the grazing fields limits the possible weight gain and influences the classification of lams. The grazing resources are in general limited, and will affect the possibility of fattening lambs in the fall. The objective with this study is to come up with a tool to help in determining when to slaughter which lambs in the fall when resources are limited. In order to make good decisions, the first step is to calculate the profitability of various slaughtering decisions. I use known characteristics of the lambs as weight, sex etc. to determine expected value of the carcass if slaughtered at various point in time in the future. In order to determine expected quality for the carcasses I have used a multinomial ordered probit regression model to determine the probability for obtaining a particular classification. A linear programming model is used to choose the best alternatives given limited grassing resources. The model can be used to determine optimal slaughtering decisions given a particular group of lambs and resources. By limiting the possible choices in the model, the model user may also investigate the losses associated with alternative slaughtering schemes. In this paper I describe the forecasting models for determining the value of the carcass, I describe the general linear programming model and show some results from running the model.
Abstract
The Norwegian Ministry of Agriculture (1999) has announced its goal of converting 10% of the total agricultural area to organic farming methods by the year 2009. Considerations of profitability and risk will be especially important, when the conversion of a farm is planned. Studies of risk and risk management in organic farming have been lacking in Norway. Only very few such studies have been carried out internationally, thus showing that there is a definite need for more risk and risk management research in organic farming. The project aims to increase knowledge about risks and risk management in organic farming systems. It is a co-operation between NILF, NORSK, and NVH. Both biological and economic aspects of risk will be taken into consideration. We wish to test and apply acknowledged statistical and risk analysis theories and methods on issues related to organic farming. The project will deal with the extent of risk in organic farming, strategies used by organic farmers to handle risk and whole-farm models to analyse optimal economic solutions under uncertainty in organic farming. The project will cover farms that are still in conversion and completely converted farms. Results from the project will directly benefit farmers and farm advisers. Politicians and public administrators will receive access to significant information for the design of future policies.
Authors
Christian Noell Mogens LundAbstract
Nowadays agricultural firms are more often than in the past decades forced to adapt operations, plans, strategies etc. to changes and uncertainties in their legal and business environment. The Balanced Scorecard (BSC) as an approach to strategic controlling in agriculture is discussed as an answer to the growing management demands in Danish farms. A brief description of the BSC-concept, its development process as well as principle potentials and limitations is given. In a case example on a dairy farm the current Danish strategic planning framework and the BSC are compared. The need for a stricter orientation of strategic planning to external demands (customers, stakeholders) is emphasised. Necessary prerequisites for the implementation of the BSC-concept into practical farming are discussed. Finally five critical success factors to the BSC adoption by Danish farmers are identified.
Editors
Agnar HegrenesAbstract
No abstract has been registered
Authors
J. Brian Hardaker Gudbrand LienAbstract
No abstract has been registered
Abstract
Wintering ability in the field and resistance to different winter-stress factors under controlled environmental conditions were studied in a full-sib family of perennial ryegrass (Lolium perenne L.). Significant variation in tolerance to freezing and ice encasement, resistance to pink snow mould (Microdochium nivale) and also in winter survival and spring growth were found between the different genotypes. No strong correlations were found between the resistances to the different stress factors. These results indicate that resistance to different winter-stress factors is controlled by separate genes in perennial ryegrass. A low but significant positive correlation was found between spring growth of plants in the field after the first winter and both freezing tolerance and M. nivale resistance measured in controlled environments. Cold hardening seemed to influence freezing tolerance and M. nivale resistance differently in the different genotypes, since no distinct correlation in tolerance to freezing or resistance to M. nivale was found between unhardened and hardened plants. Tolerance or resistance to most of the winter stress factors measured was positively correlated with plant size.
Abstract
No abstract has been registered
Authors
Gudbrand LienAbstract
Stochastic budgeting is used to simulate the business and financial risk and the performance over a 6-year planning horizon on a Norwegian dairy farm. A major difficulty with stochastic whole-farm budgeting lies in identifying and measuring dependency relationships between stochastic variables. Some methods to account for these stochastic dependencies are illustrated. The financial feasibility of different investment and management strategies is evaluated. In contrast with earlier studies with stochastic farm budgeting, the option aspect is included in the analysis.
Abstract
A model is presented to investigate the optimal economic life cycle of grass leys with winter damage problems in northern Norway and to determine the threshold of winter damage before it is profitable to reseed. A two‐level hierarchic Markov process has been constructed using the MLHMP software (the MLHMP software and the plug‐in constructed for this model are available for download at http://www.prodstyr.ihh.kvl.dk/software/mlhmp.html). The model takes uncertainty concerning yield potential, damage estimation and weather‐dependent random fluctuations into account. A Kalman filter technique is used for updating the knowledge of yield potential and damage level. The application of the model is demonstrated using data from two commercial Norwegian farms. As parameter estimates vary considerably among farms, it is concluded that decision support concerning optimal economic life cycle of grass leys should be done at farm level. The results also show the importance of using a flexible dynamic replacement strategy. Use of the model for specific farm situations is illustrated.
Abstract
No abstract has been registered