We wish to present a method to quantify the value modifying effects when comparing animal farms. To achieve our objective, multi-variable statistical methods were needed. We used a principal component analysis to originate three separate principal components from nine variables that determine the value of farms. A cluster analysis was carried o...ut in order to classify farms as poor, average and excellent. The question may arise as to which principal components and which variables determine this classification.
After pointing out the significance of variables and principal components in determining the quality of farms, we analysed the relationships between principal components and market prices. Some farms did not show the expected results by the discriminant analysis, so we supposed that the third principal component plays a great role in calculating prices. To prove this supposition, we applied the logistic regression method. This method shows how great a role the principal components play in classifying farms on the basis of price categories.
The characterization of heavy metal polluted abandoned mining sites is a complicated assignment due to the variable spatial distribution of the pollutants, therefore complex integrated method is required in order to assess precisely the amount and the distribution of the contaminants. The examined area is flotation sludge reservoir of abandoned... Pb-Zn mining site with serious heavy metal contamination. located in Gyöngyösoroszi, Northern Hungary.
The hyperspectral image of the flotation sludge is obtained by using a Digital Airborne Imaging Spectrometer DAIS 7915, in the frame of DLR HySens first Hungarian hyperspectral flight campaign (21/08/2002). Parallel to the flight campaign heavy metal content of soil samples were examined from the area of the flotation sludge. The analysis of hyperspectral data was verified by the examination of mine tailing samples by FPXRF (Field Portable X-ray Fluorescence spectrometry) (NITON XL-703).
Determinations of heavy metal containing minerals are based on the spectral profiles of the pixels of the area with using USGIS standard spectral profiles of the examined materials (galena, pyrite, sphalerite, goethite and jarosit).
Applying the Spectral Angle Mapper with BandMax classification the distribution of minerals (galena, pyrite, sphalerite, goethite, jarosit) in the area was defined. The mineral formation occurs especially at the levees and the barren places of the Szárazvölgyi flotation sludge reservoir. Based on the statistic results of the samples, principal component analysis and correlation coefficient between the different metal content of the samples were calculated. The highest correlations were found between Pb-Zn, Fe-Zn and between Fe-Pb. This prove the results of the principal component analysis, where usually Pb, Zn, Fe introduce the main component.
Canopy analysis was also carried out with the hyperspectal image in order to classify the differences between vegetation types at the Szárazvölgy flotation sludge reservoir and analyse the applicability of it. Supervised classification methods were used to distinguish 8 vegetation types based on the spectral properties of the area. The results of the classifications were compared to a ground truth image, based on ortophoto, topographic map, and GPS based field data collection. According to results of the comparison, the paralellpiped classification method is proved to be appropriate method based on the overall accuracy of canopy classification, which was 54% due to heterogeneity of the vegetation.
The results of hyperspectral data and FPXRF analysis suggest that Pb, Zn and Fe containing minerals have similar spatial distribution in the examined and barren area.
Based on this study hyperspectral remote sensing is likely to be an effective tool for the characterization and modeling the distribution of Pb, Zn and Fe containing minerals at the examined heavy metal polluted sites. Further more, based on the vegetation analysis plant species for phytoremediation can be defined.
The Collared Dove conquered continent areas within a few decades. Causes and dispersion pattern of expansion has been investigated in several studies. However, the relationship between the geographic distribution and genetic structure of populations has not been researched. We used 152 individuals from 19 countries in this study. We analyze a 6...50 bp long mitochondrial COI sequences of each individuals. We were performed Spatial Autocorrelation Analysis, Principal Component Analysis and analysis of the genetic discontinuity in this study. Under 2500 km distance was a positive correlation between the genetic differentiation and different geographical areas. Hidden genetic barriers were found only Carpatian Basin. Could not be detected signs of genetic isolation in other regions. This will probably due to the unevenness of the sample collection, because these areas proportionally much fewer sequences were available. Therefore, is worth repeat this analysis after further sample collection, in the future.
technical and economic characteristics, which give rise to high levels of uncertainty and greater control in the supply chain. In order to investigate the role of different transaction costs in marketing behavior, we carried out research in the central region of Hungary among beef retailers and wholesalers. This research is based on primary dat...a collection and examines the motivation of choices in the beef sector on distinction among different marketing channels and the role of transaction costs in procurement. Since this case can be regarded as a qualitative choice situation the hypothesis that transaction cost’s variables are significant is judged by the application of multinomial logit model in order come up with the variables that can influence the supply chain structure and the choice of different marketing channels. This analysis enabled us to explore the structure in data and confirm or reject the expected interrelations of causative variables. Our
1 A szerző témavezetője Dr. Fertő Imre.
2 A kutatás az OTKA F038082 sz. „Vertikális koordinációs és integrációs modellek az élelmiszer-gazdaságban” c. programja keretében valósult meg.
3 A szerző köszöni Dr. Fertő Imrének és Dr. Szabó G. Gábornak, a Magyar Tudományos Akadémia Közgazdaságtudományi Kutatóközpont tudományos főmunkatársainak a kutatás során nyújtott nagy értékű segítséget. results partly support and contradict the basic predictions of transaction cost economics.
The near infrared spectroscopy is widely used in the different industries as a rapid, non-invasive analitical tool. It is suitable for identification, qualification and quantitative analysis as well. As this technique is indirect, to make accurate calibration equations we need a proper sample population. Before the quantitaive analysis, develop...ing calibiration modells we have to collect and examine the spectra. In our study we examined wheat samples with known origins to find if there is any effect of the growing area on the NIR spectra.
Processing large amounts of data provided by automated analytical equipment requires carefulness. Most mathematical and statistical methods have strict application conditions. Most of these methods are based on eigenvalue calculations and require variables to be correlated in groups. If this condition is not met, the most popular multivaria...te methods cannot be used. The best procedure for such testing is the Kaiser-Meyer-Olkin test for Sampling Adequacy. Two databases were examined using the KMO test. One of them resulted from the sweet corn measured in the scone of the study, while the other from the 1979 book of János Sváb. For both databases, MSA (measures sampling adequacy) was well below the critical value, thus they are not suitable e.g. for principal component analysis. In both databases, the values of the partial correlation coefficients were much higher than Pearson’s correlation coefficients. Often the signs of partial coefficients did not match the signs of linear correlation coefficients. One of the main reasons for this is that the correlation between the variables is non-linear. Another reason is that control variables have a non-linear effect on a given variable. In such cases, classical methods should be disregarded and expert models better suited to the problem should be chosen in order to analyse the correlation system.