Changes in the Structure of Crop Production in Slovakia after 2004 Using an Example of Selected Crops

Abstract

Spatial changes in the structure of crop production have the potential to impact economics and food security in Slovakia. The objective of this study was to analyze the modification of harvested areas, the production and yields of selected crops—cereals, oilseeds, and perennial forages—and their food and non-food use from 2004 to 2020. The results indicated that an increase in the cultivation of large-scale crops (cereals and oilseeds) has occurred at the expense of crops produced for food. Changes in the structure of plant production indicate negative risk factor that reduce the competitiveness of the agricultural sector and threaten Slovakia’s food security. Moran’s global and Moran’s local autocorrelation index were used in the synthesis of the findings. A spatial autocorrelation analysis of the harvest areas of selected crops was used as a practical approach to locate statistically significant areas with high or low crop harvest. This manifested itself as positive spatial autocorrelation.

Hotspot Identification and Causal Analysis of Chinese Rural Tourism at Different Spatial and Temporal Scales Based on Tourism Big Data

“…In order to further explore the spatial distribution characteristics of rural tourism popularity, this paper utilizes spatial autocorrelation techniques to analyze the hot and cold patterns of rural tourism popularity and reveal the spatial distribution patterns and interrelationships of rural tourism popularity so as to gain insights into the development process of rural tourism popularity and explore the spatial dependence between geographic phenomena. Commonly used indicators are global and local spatial autocorrelation, Moran's I [37]. The former measures the overall degree of clustering of observables within a certain space, while the latter measures the degree of clustering of observables among units within a spatial context:…”

Impact of COVID-19 on University Activities: Comparison of Experiences from Slovakia and Georgia

“…Other foreign countries with which CPU scientists cooperate include Saudi Arábia (King Saud University), University of Granada (Spain), I. N. Ulianov Chuvash State University and Peoples' Friendship University of Russia-RUDN University (Russia), and Polish Academy of Sciences (Poland). Cooperation with Italian scientists from various institutions is also noteworthy [38][39][40][41][42][43][44][45].…”

Impact assessment of direct payments of EU common agricultural policy on economic resilience of agriculture

“…Subsidies were also documented to negatively impact crop diversity (Lazíková et al, 2019), which is often emphasized as significantly increasing the resilience of the farming systems (Bowles et al, 2020;Sanford, 2021). Moreover, DPs tended to encourage producing extensive crops at the expense of intensive sectors (Valkanov, 2013;Ivanov, 2018;Balezentis et al, 2019;Morkunas & Labukas, 2020;Némethová & Vilinová, 2022). According to Ivanov (2018), the shift to crop farming may be encouraged by direct payments covering significantly different shares of expenses for different subsectors: e.g., around 20-30% of production expenses of crop farming and merely 3-5% of the production costs incurred in the intensive vegetable and fruit sectors.…”

“…This negative relationship between DPs and agricultural production may be caused by several factors. As discussed in Section 1.3.2, DPs may impact farms' productivity via several channels: farms' investment decisions (Zhu & Oude Lansink, 2010;Musliu, 2020), decisions on input volumes and quality (Ferjani, 2009;Patton, Olagunjuand & Feng, 2017), decisions on production structure (Ivanov, 2018;Morkunas & Labukas, 2020;Némethová & Vilinová, 2022), etc. Thus, if the motivation to produce due to DPs decreases in a wider range (or other negative effects increase faster), then the positive effects on investment or farm expansion, increasing productivity, are spread, and the overall effect on production is expected to be negative.…”

“…The negative DPs' impact on production is transferred, assumably, mainly via systematically changing farmer behavior in non-preferrable ways (as discussed above and in Section 1.3.2). One of the most notable differences between the DPs' impact on production in the OMS and the NMS may be due to a strong DPs impact on changing production structure (from animal husbandry to crop farming) in the NMS (Ivanov, 2018;Balezentis et al, 2019;Morkunas & Labukas, 2020;Némethová & Vilinová, 2022), while it is not emphasized in the literature in the case of the OMS. The other sorts of systematic non-preferrable behavior were observed both in the OMS and the NMS Minviel & Latruffe, 2017;Marzec & Pisulewski, 2017).…”