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
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.
Authors
Leif Jarle Asheim Ivar MysterudAbstract
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
Abstract
The rationale for stand growth modelling is often either grounded in a search for improved scientific understanding or in support for management decisions. The ultimate goal under the first task is seen in mechanistic models, i.e. models that represent the stand structure realistically and predict future growth as a function of the current status of the stand. Such mechanistic models tend to be over-parameterized with respect to the data actually available for a given stand. Calibration of these models may lead to non-unique representations and unreliable predictions. Empirical models, the second major line of growth modelling, typically match available data sets as well as do process-based models. They have less degrees of freedom, hence mitigate the problem of non-unique calibration results, but they employ often parameters without physiological or physical meaning. That is why empirical models cannot be extrapolated beyond the existing conditions of observations. Here we argue that this widespread dilemma can be overcome by using interactive models as an alternative approach to mechanistic (algorithmic) models. Interactive models can be used at two levels: a) the interactions among trees of a species or ecosystem and b) the interactions between forest management and a stand structure, e.g. in thinning trials. In such a model data from a range of sources (scientific, administrative, empirical) can be incorporated into consistent growth reconstructions. Interactive selection among such growth reconstructions may be theoretically more powerful than algorithmic automatic selection. We suggest a modelling approach in which this theoretical conjecture can be put to a practical test. To this end growth models need to be equipped with interactive visualization interfaces in order to be utilized as input devices for silvicultural expertise. Interactive models will not affect the difficulties of predicting forest growth, but may be at their best in documenting and disseminating silvicultural competence in forestry.