This article has been made according to my dissertation in which I present some opportunity of risk analysis and risk management in the decision support of crop production. Plant production is one of the most hazardous agricultural enterprises. Among risk sources seasonal fluctuation of average yields plays an important role in the assessment o...f enterprises. Therefore, I analyzed the production risk of the produced crops in Hungary compared to the European Union’s, after that I took into consideration the production site’s circumstances as well. Decision-makers must possess such means, by which they can measure, oversee and manage the effects and consequences of risk. In crop production linear programming models can be used to determine the optimal crop structure, by which income-sensitivity can be taken into account, but it does not reflect the behavior to risk. This deficiency can be avoided by using risk programming models. By the complementary usage of linear programming and risk programming models the optimizing and adaptive planning can be executed. It often causes a problem for the producers to decide when and how much to sell to realize a maximum turnover. The decision is mostly influenced by the selling prices, but also important factors are the financial status of the business, the amount of credit and its conditions, the stock piling opportunities and costs, and the short-term investment opportunities as well. For the resolution of the problem I set up a dynamic, simultaneous financial model by which the system-conceptual analysis of the above mentioned factors and a sound decision-making can be executed.
Agricultural production is among the riskiest production activities. Similarly to other branches of agriculture in animal breeding the finished product is the result of complex procedures. The biological technological procedure, the creation of the product is affected by an outstanding number of environmental factors which also cause uncertaint...ies. In the North Great Plain Region of Hungary, sows, gilts and slaughter pigs are produced on a corporate farm. The reliable operation data of this company provide a stable basis for and estimating future costs and revenue and their distributions. Monte Carlo methods are one of the generally accepted tools for modeling risks. The significant independent variables, their ranges and probability distributions, and the correlation between them were inputs to the model. The values of the variables were produced using a random number generator. The computer simulation was performed using @Ris (PalisadeCorporation) software. The study concentrates on the factors affecting the number of off spring (piglets). Model inputs were the mating, mortality and farrowing rates; the costs and the income values based on these rates have been analysed as the output data of the model.