scholarly journals Development of agricultural farms in terms of Common Agricultural Policy support in the opinion of farmers

2019 ◽  
Author(s):  
Slawomir Zawisza ◽  
◽  
Piotr Prus ◽  
Szymon Beben ◽  
Keyword(s):  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Policy Support

scholarly journals On diversity effects of alternative agricultural policy reforms in Finland: an agricultural sector modelling approach

2008 ◽  
Vol 13 (3) ◽  
pp. 229 ◽  
Author(s):  
A. MIETTINEN ◽  
H. LEHTONEN ◽  
R. HIETALA-KOIVU
Keyword(s):  
Land Use ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Agricultural Land ◽  
Policy Support ◽  
Agricultural Land Use ◽  
Policy Reforms ◽  
Sector Model ◽  
Positive Effects ◽  
Diversity Effects

The European Union has decided to reform its agricultural policy and decouple Common Agricultural Policy support partially from production. The aim of this study is to predict the diversity effects of agricultural policy reforms in which direct aid payments are disconnected from production, and compare the outcomes with the effects of a policy in which Common Agricultural Policy support is coupled to production. The study employs a dynamic regional sector model of Finnish agriculture. The sector model predicts regional agricultural land use, numbers of livestock, stocking densities, pesticide application areas, and nutrient balances. Diversity of agricultural land use is measured by Shannon’s diversity index. The results indicate that if agricultural support is independent from production, the amount of fallow land will increase considerably in the future. This will decrease the diversity of agricultural land use at landscape level, but may not be harmful at species level since green fallow has some positive effects, especially on the densities and abundance of farmland birds. Instead, the decrease in bovine animals is likely to run down biological diversity, since it simplifies crop rotation and diminishes grazing.;

Cherneha O. B., Chepurnova A. V. COMPARATIVE ANALYSIS OF UKRAINE AND POLAND FOOD SECURITY LEVELS

2019 ◽  
pp. 9-17
Keyword(s):  
Food Security ◽  
Comparative Analysis ◽  
Rural Development ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Public Spending ◽  
Development Program ◽  
Rural Development Program ◽  
Security Levels ◽  
The Eu

Objective. The purpose of the article is to compare the levels and mechanisms of food security management in Ukraine and Poland, to identify the main factors influencing the processes of its formation and to determine the directions of increasing the level of Ukraine food security. Methods. The scientific results of the study were obtained using the following methods: theoretical generalization and comparison (for the study of meaningful aspects of the definition of «food security»), analysis and synthesis (for comparative analysis of Ukraine and Poland food security levels), abstract-logical method (for establishing the links between the level of economic development of countries and the levels of their food security and determining the directions of increasing the Ukraine level of food security). Results. On the basis of a comparative analysis of Ukraine and Poland food security levels, a significant gap in Ukraine’s provision of food security has been identified. Thus, with respect to all food security components identified by FAO, except for the «use» of sanitary and safe drinking water, Poland has reached far ahead of Ukraine. It has been found that for the period 2012–2018, the value of the Global Food Security Index for Ukraine decreased by 2.1 due to a decrease in the level of affordability and availability of food, while the Polish side increased its position on GFSI by 2.8 due to the increase in affordability and availability of food in the country. It has been found that the decisive influence on the level of food security in Poland, as well as high ranking in the ranking is carried out by the EU Common Agricultural Policy (CAP), the implementation of the Polish Rural Development Program and significant public spending on agriculture. It has been determined that the main directions for improving the level of food security of Ukraine should be: lifting the moratorium on the sale of agricultural land; financing the agri-food sector not only through public spending but also through EU programs; creation and implementation of the National Rural Development Program; full and unconditional implementation of Government programs on EU integration; adaptation to the EU Common Agricultural Policy standards.

scholarly journals A Possible Role of Copernicus Sentinel-2 Data to Support Common Agricultural Policy Controls in Agriculture

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Filippo Sarvia ◽  
Elena Xausa ◽  
Samuele De Petris ◽  
Gianluca Cantamessa ◽  
Enrico Borgogno-Mondino
Keyword(s):  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Observation Data ◽  
Key Factor ◽  
Ndvi Time Series ◽  
Earth Observation Data ◽  
Four Levels ◽  
Nw Italy ◽  
Sentinel 2

Farmers that intend to access Common Agricultural Policy (CAP) contributions must submit an application to the territorially competent Paying Agencies (PA). Agencies are called to verify consistency of CAP contributions requirements through ground campaigns. Recently, EU regulation (N. 746/2018) proposed an alternative methodology to control CAP applications based on Earth Observation data. Accordingly, this work was aimed at designing and implementing a prototype of service based on Copernicus Sentinel-2 (S2) data for the classification of soybean, corn, wheat, rice, and meadow crops. The approach relies on the classification of S2 NDVI time-series (TS) by “user-friendly” supervised classification algorithms: Minimum Distance (MD) and Random Forest (RF). The study area was located in the Vercelli province (NW Italy), which represents a strategic agricultural area in the Piemonte region. Crop classes separability proved to be a key factor during the classification process. Confusion matrices were generated with respect to ground checks (GCs); they showed a high Overall Accuracy (>80%) for both MD and RF approaches. With respect to MD and RF, a new raster layer was generated (hereinafter called Controls Map layer), mapping four levels of classification occurrences, useful for administrative procedures required by PA. The Control Map layer highlighted that only the eight percent of CAP 2019 applications appeared to be critical in terms of consistency between farmers’ declarations and classification results. Only for these ones, a GC was warmly suggested, while the 12% must be desirable and the 80% was not required. This information alone suggested that the proposed methodology is able to optimize GCs, making possible to focus ground checks on a limited number of fields, thus determining an economic saving for PA and/or a more effective strategy of controls.

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