Search

Search Results

• Economic analysis of some agrotechnical factors in maize production - a Hungarian case study

  5-16

  Attila Bai

  Zoltán Gabnai

  Imre Kovách

  Ibolya Czibere

  János Nagy

  Dénes Sulyok

  Donika Maloku

  Péter Balogh

  Views:

  450

  This paper focuses on the economic and statistical evaluation of the production technology findings of the polyfactorial maize production experiments carried out between 2015-2017 at the Látókép Experiment Site of the University of Debrecen, Faculty of Agricultural and Food Sciences and Environmental Management. The examined agrotechnical factors included irrigation, previous crop, tillage, crop density, hybrid and N nutrient supply, while the effect of different crop years was taken into consideration. In addition to descriptive statistical methods, we used multivariate regression analysis during the statistical evaluation. In the course of the evaluation, we examined three models that differed in terms of tillage methods and the consideration of crop year. In our best fit model, the factors were 71% responsible for the change in yield value. We carried out efficiency and comparative analyses in the course of the economic evaluation.
  Averaged over the three examined years, it can be stated that nutrient supply and crop year had an outstanding effect on yield, while irrigation had a minimal effect. However, global warming may justify irrigation in the future, not only from a biological point of view, but also from an economic aspect.
  Ideal tillage is also greatly affected by crop year, too. Altogether, of the examined tillage systems, subsoiling proved to be the best from an economic point of view.
  Our investigations confirm that it is better to perform intensive farming under more favourable market conditions. The optimum of N fertilisation is probably outside of the range we examined, if the extreme changes in maize and fertiliser prices are ignored.

  JEL Classification: Q16, Q12, Q13, O32

• POTENTIAL USES OF BLOCKCHAINS IN HUMAN RESOURCES

  Peter Nagy

  Views:

  92

  Blockchain technology offers businesses many opportunities for more efficient operation and safer data management. It also becomes easy tostore and share employee data, while the blockchain guarantees that it does not fall into unauthorized hands. The management of financial transactions and the automation of the payment process are also a great advantage for businesses, which can manage the payment of wages andbenefits more efficiently. Another area of application of blockchain technology is the creation of more efficient workflows that can improve productivity and reduce costs. The management of work schedules and optimized work processes will also be easier with the help of the blockchain, so businesses can become more efficient and effective. In this article, the relationship between HR and blockchains was explored through a meta-analysis based on available related publications.

• Examination of pig farm technology by computer simulation

  25-29

  Szilvia Szőke

  Lajos Nagy

  Sándor Kovács

  Péter Balogh

  Views:

  162

  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 uncertainties. 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.