Dynamic analysis of European organic agricultural areas in the context of sustainable development

2018 ◽  
Vol 47 (1) ◽  
pp. 27-35
Author(s):  
Liliana Duguleană ◽  
Marius Bălăşescu ◽  
Constantin Duguleană ◽  
Simona Bălăşescu ◽  
Nicoleta Andreea Neacşu ◽  
...  
Keyword(s):  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Eu Member States ◽  
Multiple Regression Method ◽  
Components Analysis ◽  
Main Factors ◽  
Future Economic Development ◽  
Agricultural Areas ◽  
The Eu ◽  
Comparative Manner

The aim of this research was to analyze changes in the size of the European organic agricultural areas between 2000 and 2014 and assess the factors that influenced and differentiated EU member states in this context. The analyses showed the development potential of the EU countries for extension of organic agricultural areas in a comparative manner, based on their future economic development capacities. The article used two multivariate statistical methods, principal components analysis and multiple regression method, to establish and assess the influence of the main factors that contributed to changes in the size of national organic areas. The main factors in 2014 were the European financing for agriculture and rural development, and the migration phenomenon.

scholarly journals Delimitation of Agricultural Areas with Natural Constraints in Greece: Assessment of the Dryness Climatic Criterion Using Geostatistics

Agronomy ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 161 ◽  
Author(s):  
Konstantinos Soulis ◽  
Dionissios Kalivas ◽  
Costas Apostolopoulos
Keyword(s):  
Climate Variability ◽  
Spatial Variability ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Data Series ◽  
Eu Member States ◽  
Daily Data ◽  
Agricultural Areas ◽  
Soil Climate ◽  
The Eu

The Less Favored Areas (LFAs) scheme has existed in various forms since 1975 and it is a broad mechanism supporting rural development in agricultural areas with natural constraints (ANC). Within the programme period 2014–2020, the European Commission developed a common set of biophysical criteria (soil, climate, and terrain) to meet the requirement for a robust and harmonized approach of delimiting ANC throughout the EU Member States. Soil and terrain criteria can be derived directly from soil maps using geospatial analysis techniques based on the provided guidelines. However, the assessment of climatic criteria can be challenging especially in regions characterized by increased spatial variability and data scarcity. In this paper, the assessment of the dryness climatic criterion in a data-scarce region (Greece) as well as the challenges, limitations, and solutions are presented. Daily data-series from 140 meteorological stations for a 30-year reference period were analyzed and the spatial distribution of the precipitation and the potential evapotranspiration for each year were estimated in order to make the final assessment of the dryness criterion. Climate variability and the presence of trends were investigated as well. The obtained results indicated that most of the utilized agricultural area is affected by dryness due to a combination of low precipitation and high evapotranspiration rates. The extreme spatial variability especially in precipitation was also highlighted. An important temporal variability was observed as well, including indications of decreasing trends in precipitation and aridity index. Climate variability and possible trends should be investigated in more detail using longer time series in order to evaluate their impact in agricultural production.

scholarly journals Differentiated Support of the EU Enlargement in the Public Opinion: A Multivariate LISREL Analysis

Geografie ◽  
2007 ◽  
Vol 112 (1) ◽  
pp. 1-16
Author(s):  
Veronika Tománková
Keyword(s):  
Public Opinion ◽  
Eu Enlargement ◽  
Structural Equations ◽  
The European Union ◽  
Multivariate Statistical ◽  
Member States ◽  
The Public ◽  
Eu Member States ◽  
The Eu ◽  
Clear Support

This paper provides an analysis of the public opinion in the EU countries concerning further enlargement. Public opinion plays an important role in the current integration processes and is an integral part of the research concerning the European Union. The differentiation in the support for the EU enlargement across 25 countries can be explained by the multivariate LISREL (linear structural equations) analysis that makes possible to identify a causal system through the explanatory model. The model includes structural and public opinion variables in the set of the twenty-five EU member states. Multivariate statistical analysis shows a low public opinion support for the EU enlargement in rich states and, on the other hand, a clear support in a group of post-communist member states.

scholarly journals What Remains after Brexit? A View from the Outside

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Filip Kokotovic ◽  
Peter Kurecic
Keyword(s):  
European Union ◽  
Economic Development ◽  
Foreign Policy ◽  
The European Union ◽  
Eu Member States ◽  
The United Kingdom ◽  
The Uk ◽  
Future Economic Development ◽  
Political Divide ◽  
The Eu

The British referendum result to opt for exiting the European Union (EU) has left both the United Kingdom (UK), as well as the rest of the EU with questions regarding the future of the integration and their future economic development. While the EU member-states present a united front in regards to the leave process, there are deeply rooted divisions on all other relevant policy questions. The issues of migration, foreign policy, and the level of cohesion within the EU itself represent the questions where there is little or no consensus. The paper concludes that both the UK and the EU need to address a deep political divide and find a way to coexist in the aftermath of Brexit.

scholarly journals Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students

2020 ◽  
Vol 25 (1-2) ◽  
pp. 35-56
Author(s):  
Vasil Simeonov
Keyword(s):  
Environmental Monitoring ◽  
Principal Components Analysis ◽  
Statistical Methods ◽  
Principal Components ◽  
Monitoring Data ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Introductory Course ◽  
Components Analysis ◽  
Environmental Monitoring Data

Abstract The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis, principal components analysis, principal components regression, N-way principal components analysis, partial least squares regression and self-organizing maps with respect to their possible application in intelligent analysis, classification, modelling and interpretation to environmental monitoring data. The target group of possible users is master program students (environmental chemistry, analytical chemistry, environmental modelling and risk assessment etc.).

scholarly journals Agro-Morphological Variation in Some Iranian Melon (Cucumis melo L.) Genotypes Revealed by Multivariate Analysis

2020 ◽  
Author(s):  
E Ghorbani ◽  
A Motallebi Azar ◽  
S Bolandnazar
Keyword(s):  
Cucumis Melo ◽  
Morphological Traits ◽  
Fruit Weight ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Breeding Programs ◽  
Attachment Strength ◽  
Total Variability ◽  
Components Analysis ◽  
Cucumis Melo L

Diversity of 9 local Iranian genotypes of melon was studied based on 28 quantitative and qualitative agro-morphological traits, using multivariate statistical methods. Analysis of variance showed significant differences between genotypes for all quantitative traits. However, the studied melon genotypes were previously clustered in two main groups of inodorous and cantalopensis, cluster analysis classified them in four different groups based on all traits, in particular outlaying Shadegani genotype from Inodorous group. Clustering was also supported by principal components analysis (PCA). The first two PCs contributed 60% of the total variability and demonstrated variations mainly on the basis of yield related traits including fruit number, day to flower, day to harvest, fruit weight, fruit length and other distinctive traits such as rind pattern, peduncle attachment strength, fruit firmness and aroma. Accordingly, agro-morphological traits could be used for variation studies in melons and results might be useful for improving breeding programs.

Ecological distribution of moss-dwelling tardigrades on Vancouver Island, British Columbia, Canada

1991 ◽  
Vol 69 (1) ◽  
pp. 122-129 ◽  
Author(s):  
R. Deedee Kathman ◽  
Stephen F. Cross
Keyword(s):  
British Columbia ◽  
Cluster Analysis ◽  
Vancouver Island ◽  
Ecological Distribution ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Moss Species ◽  
Components Analysis ◽  
And Cluster Analysis ◽  
The Relationship

Replicate samples of tardigrades were collected at six altitudes from five mountains on Vancouver Island, British Columbia, Canada, to determine the relationship between species of tardigrades and altitude, and between species of tardigrades and species of mosses in which they were collected. A total of 13 696 tardigrades representing 39 species were collected and identified. Thirty-seven species of mosses were identified. Data were analyzed using principal components analysis and cluster analysis. The results from both multivariate statistical methods indicated that the distribution and abundance of tardigrades were not dependent upon the altitude or moss species.

scholarly journals Methods of a Multivariate Analysis of Non-Metric Data in Evaluating the Generational Perception of Social Characteristics

2020 ◽  
Vol 20 (1) ◽  
pp. 390-407
Author(s):  
Agnieszka Stanimir
Keyword(s):  
Social Factors ◽  
Social Characteristics ◽  
Economic Aspects ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Factors Influencing ◽  
Subjective Satisfaction ◽  
Burt Matrix ◽  
The Eu

AbstractResearch background: The search for factors influencing the evaluation of the quality of life in terms of subjective and objective socio-economic aspects was the background of the study. The search for perfect multivariate statistical methods in the describing of the assessments made by respondents in variable groups, as well as the categories was carried out.Purpose: The aim of the study was to recognize the natural areas of transferring subjective satisfaction with the level of social factors in the three groups describing: household, country of residence, and the EU. The determined natural relations between the factors were then compared with the established sets of those factors. The characteristics of behaviour were compared in three generations of the EU.Research methodology: The Standard Eurobarometer, autumn 2018, provided data describing adults from the generations Y, X, and BB. In the analysis a factor analysis and correspondence analysis were used.Results: The effect of the used methods is a multidirectional image of the evaluations made by the EU Generations Y, X and BB in the areas of an individual’s functioning: direct (the household), close (the country of residence), and further (Europe and the EU).Novelty: The conducted analysis indicates the need to use diverse methods in order that the assumed research objectives are thoroughly realized. The article indicates the possibility of modifying the approach in using the Burt matrix in connection with concatenated contingency tables.

scholarly journals A Multidimensional Approach to Competitiveness, Innovation and Well-Being in the EU Using Canonical Correlation Analysis

2020 ◽  
Vol 12 (4) ◽  
pp. 5-21
Author(s):  
Ane-Mari Androniceanu ◽  
Jani Kinnunen ◽  
Irina Georgescu ◽  
Armenia Androniceanu
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Well Being ◽  
Eu Member States ◽  
Canonical Variates ◽  
Main Factors ◽  
The Uk ◽  
National Governments ◽  
The Eu

Achieving a competitive economy and a competitive market generally proceeds from the desire to meet economic and social objectives and it ensures a growing level of social welfare. The objectives of our research are to determine and highlight the bidirectional linear correlations among competitiveness, well-being and innovation and to analyze the main factors that influence these relations. Our research includes the EU member states and the UK using these countries’ specific indicators from the databases of EUROSTAT, the World Economic Forum and the United Nations from 2016-2018. We used Canonical Correlation Analysis to determine a set of canonical variates which represent linear combinations of the variables from each set. The contributions of our research show a direct and strong link among the three pillars of competitiveness, innovation and well-being. This analysis allowed us to identify and analyze the influence of innovation on the economic development and competitiveness of each EU country and on the well-being of its population. Governments and organizations that invest more in research in terms of innovation to increase the competitiveness of their products and services have shown a growing GDP and a higher level of population well-being. This research is representative at the European level and may influence the decisions of national governments and other institutions to encourage innovation through drivers such as R&D expenditures and human resources as the main factors generating economic growth and competitiveness, thus with a direct effect on GDP and on well-being.

scholarly journals Development of integration processes in the globalization conditions: Ukraine and EU-countries

2020 ◽  
Keyword(s):  
Growth Curves ◽  
Global Integration ◽  
Multivariate Statistical ◽  
International Integration ◽  
Member States ◽  
Factors Affecting ◽  
Eu Countries ◽  
Eu Member States ◽  
Is Integration ◽  
The Eu

The change in Ukraine’s position, taking into account various approaches to assessing the development of integration processes, indicates the importance of choosing the forecast for the development of integration with EU member states. The subject of the study is integration with the EU member states. The aim of the article is to analyze the development of integration processes in Ukraine and the EU member states, build a forecast of the strategy of international integration on the example of Ukraine and the EU countries in the context of globalization. Research methods: the method of multivariate statistical analysis, namely factor analysis to determine the factors affecting the development of integration processes; modeling of growth curves for predicting the values of indicators of integration processes. The calculations were performed using the Statgraphics Centurion application package. Based on the results of the research, a basis of indicators characterizing the socio-economic situation of the member countries of the integration processes is formed. It included: GDP and GDP per capita, attracting foreign direct investment and consumer price indices; as well as the share of ICT goods. The analysis of problems and prospects for the development of integration processes on the basis of a theoretical and logical analysis taking into account the strategic directions of development of the Ukrainian economy and the world economy is carried out. The forecast indicators for the member countries of the EU group and Ukraine are calculated. This allowed us to develop forecast scenarios for the development of integration processes of the member countries of integration processes in the long term. Based on the forecast obtained, strategic positions of Ukraine and the EU member states in the global integration space for three forecasting periods are formed. Conclusions: priority scenarios for the development of the integration processes of these EU member states are identified, namely Czech Republic, Estonia, Latvia, Lithuania, Poland and Ukraine indicate a positive prospect of EU cooperation with Ukraine in the aspect of international integration.

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