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Statistical comparison of coverage data of disturbed habitats in the Hajdúság
171-178Views:87Between 2002 and 2006 we made the coenological survey of five disturbed habitats marked as grasslands. With our coenological examinations and the statistical analyses we wanted to make the detailed botanical survey of the given five habitats in order to verify that the maintenance of habitats amongst agricultural lands – and considered as less valuable – is of high importance and necessary from an environmental point of view, since these habitats are often living and feeding areas of many rare and/or protected plant- and animal species.
As a result of the statistical analyses we have pointed out that number of species in case of all the five habitats extreme fluctuation characterizes the statistical universe. As regards the
average of the coverage it is the highest in case of the third habitat (degraded Puccinellia grassland), and the coefficient of variation shows homogenity as well. In examining the Shannon-value the average is the highest in case of the second habitat (Alopecurus meadow), and the statistical dispersion is the smallest. The coefficient of variation shows medium variability. The median of evenness is the lower in case of the third habitat (degraded
Puccinellia meadow) and the statistical is the highest here as well.
We have done the Hierarchical and the K-Means Cluster Analyses for the 21 plant associations of the five habitats. Both cluster analyses put the same associations into the same cluster, so
one can state that the associations in each cluster are different from the associations of the other ones according to the coverage data of the plant families. -
The Examination of the Effects of Value Modifying Factors on Dairy Farms
36-40Views:76We 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 out 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. -
Comparison of growth parameters of 40 varieties/clones short rotation coppice willow (Salix)
99-104Views:136The plantation of willow varieties was established in 2009. The 40 different varieties and clones of Salix were planted at a research field in Kolíňany (Nitra district). The paper evaluates results from the first growing season in 2009. The survival rate of planted cuttings ranged from 55.56 % to 100.00 % after the first year. The lowest survival rate was reached by Terra Nova variety. The stem numbers per plant ranged from 1.17 ±0.37 to 2.53 ±0.98. The average height of one-year old stem varied from 65.82 ±36.60 cm to 225.58 ±68.61 cm. The average stem diameter ranged from 6.90 ±2.63 mm to 14.34 ±3.39 mm. There were statistically very significant differences in parameters of stem height stem diameter and stem numbers per plant among studied varieties/clones. The statistic method used was analysis of variance ANOVA. The varieties were then divided into 6 groups according to their similarity in observed parameters after the first growing season by cluster analysis. The best results were reached by varieties/clones classified in the second group. The survival rate, stem diameter and stem height values of these varieties/clones were above average.
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Clusteranalysis as a swine farm qualifying method
165-174Views:108Cluster Analysis is one of the most favorite multivariable statistical methods, which is actually a special type of aggregating method. Observations are clustered by variables belonged to the observations. Our purpose is to create such clusters, in which the elements are the most similar, and between the clusters they are the most variant. For example these clusters could be the qualitative classifications of farms.
There have been several methods in Cluster Analysis as well as numerous distance measures, which could be used. In this article, we study all of these methods and measures. After we show the theoretical background, we apply the method in a given casestudy to control the qualitative classifications of experts. In this study, we use both the hierarchical and the non-hierarchical method, and also compare them. We would like to attract the attention that the most important problem of the analysis is to determine the optimal of clusters. -
Morphological diversity of current melons (Cucumis melo) compared to a medieval type
84-90Views:159Morphological diversity of melon (Cucumis melo); phenotype reconstruction of a medieval sample. Morphological diversity among 47 melon (Cucumis melo) cultivars and landraces from Hungarian germplasm collection (ABI, Tápiószele) were analyzed with an ultimate aim to characterize morphologically cv. Hógolyó, which showed the closest genetic similarity to a medieval melon recovered from the 15th century. Cultivars based on fruit morphology were grouped into the three main types of melon as reticulatus, cantalupensis and inodorus. Cluster analysis (by SPSS-11) based on 23 morphological (quantitative and qualitative) traits recorded revealed an extreme diversity among accessions, nevertheless cultivars were clustered into main melon clusters with only two exceptions of inodorus type cv. Zimovka J. and Afghanistan. Cultivars Sweet ananas and Ezüst ananász; and two Hungarian landraces Kisteleki and Nagycserkeszi showed close similarity. Cultivars Hógolyó and Túrkeve of inodorus type
were also grouped in one cluster, which provide insight into the morphological reconstruction of the medieval melon recovered from the 15th century. These results also indicate that old Hungarian landraces could be re-introduced into breeding programs for broadening genetic base of melon. -
The economic risk analysis in the case of agricultural enterprises
107-116Views:130The company’s activity, profitability and growth potential are influenced by risk and uncertainty derived from the economic environment. The principal thing that makes difference between risk and uncertainty is the capacity to be quantified, and then the risk can be measured, whereas uncertainty is not. Specific risk types of agricultural enterprises are on the one hand the economic risk and specific risk arising from the main agricultural activity. The economic risks include financial risk categories like market risk, liquidity risk, credit risk and operational risk. Macroeconomic risk manifest also a significant influence to the company and the importance of taking into account of this, importantly increased in recently years. In present paper, I quantified the total risk of company by using financial and operating leverage indicators. The company’s growth was characterized with internal growth rate and sustainable growth rate. The present research aims to explore risk and growth level of agricultural companies and grouping companies by different characteristics. In present analysis I have used cluster analysis. From the results I can summarize, that the agricultural enterprises growth is made by using internal financing resources and their financial leverage level is lower that operating leverage level.
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An Analysis of Rotational Line Mating Using Computer Simulation
35-39Views:134In a simulation examination, we analyzed the effect of the family size and the rate of pairing on the survival of rare genes, to keep the level of variation of the genepool and to avoid the loss of alleles.
The population size was 360 animals. In the simulation, we calculated on the basis of a discrete population. We placed the 360 animals into different clusters, with 3 types of frequencies of alleles and 3 types of groups. We assumed 2, 3 or 4 alleles in 8 loci. We generated 15 generations using the same mating and selection system used in practise. The simulation was written with Scilab 2.7.2 software, and evaluated with SPSS software.
There were significant changes in the effect of family size on the genetic variation in the following cases: when the base population had the same gene frequencies in all loci, and when the gene frequencies were between 0.125-0.75. In these cases, we found that the smaller families (10 animals/cluster) were better than the larger families (30 or 90 animals/cluster). The first generation where there accured a loss of alleles was averagely earliest in larger families (90 animal/cluster). This average was 3.37 generations. When we are searched the effects of the different rates of pairing we found those cases most favourable when the ratio of males and females was 1:2 or 1:4 as compared to 1:9. The first generation where there was a loss of alleles was averagely earliest at the ratio of pairing male and females of 1:9 (the mean was 3.05 generations) when the frequency of the rarest allele was 0.0069.
The recently introduced rotating-random mating system is an eligible method for small populations for the preservation of genes. -
Application of microsatellite fingerprints for pedigree analysis of Hungaricum grapevine varieties
71-77Views:150the Carpathian Basin were involved into our examination, which aimed at genotyping their accessions. DNA fingerprints of 101 varieties were determined with 6 microsatellite markers till 2005, resulting in successful discrimination of the accessions. Based on these results for pedigree determination, even more cultivars and primers were involved into the analyses. For studying the origin of Csabagyöngye and for proving the parent-progeny relations of Irsai Olivér and Mátrai muskotály, 19 microsatellite markers were applied, while 11 were selected for tracing the origin of Királyleányka. Genetic distances between the varieties were estimated with cluster analysis and demonstrated by dendrogram, proving that the varieties can be discriminated from each other based on the microsatellite allele sizes. Pedigree of Irsai Olivér and Mátrai muskotály has been confirmed by microsatellite allele size results, searching for the parents of Csabagyöngye and Királyleányka is in progress, since the molecular-marker based pedigree does not correspond with the putative origin of these cultivars. Our results excluded progeny-parent relationships in the
Csabagyöngye-Bronnerstraube-Muscat ottonel (Ottonel muskotály) and the Királyleányka-Kövérszőlő combinations.