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The present paper aimed to analyze utilized agricultural area (UAA), number of agricultural holdings (NAH), average holding size (AHS), standard output per holding (SOH) in Romania and other EU countries with large UAA in the period 2005-2020 using the data from Eurostat and National Institute of Statistics in order to identify the trends and actual situation. Fixed basis indices, regression equations, R square, Herfindahl-Hirschman Index (HHI), Gini Struck Coefficient(GSC), structural indices, comparisons with the EU average and among the selected EU countries: Romania, Poland, Italy, Spain, France, Germany, United Kingdom were used as processing methods for reflecting the changes farmland and farm structures. In 2020, Romania had 12,763 thousand ha UAA, representing 7.6% of the EU's UAA and coming on the 6th position, after France, Spain, Germany, Poland and Italy. In 2020, Romania had 2.88 million AH and together with Poland, Italy, Spain, France and Germany, had 6.89 million AH (75.7% of the EU's 9.1 million NAH). The farms smaller than 5 ha represent: 90.3% in Romania, 64.1% in Italy, 52.3% in Poland, 51.6% in Spain, 19.6% in France and 8.2% in Germany, while the farms with 50 ha and over account for 7.5% at the EU level, 1% in Romania, 3.1% in Poland, 4.5% in Italy, 11.6% in Spain, 31.5% in Germany and 45.9% in France. To the EU's SO, all these six countries contribute by 71% to the EU's SO. In the EU, less than Euro 2,000 SO was produced by 35.7% farms, while Euro 50,000 and over was achieved by 12.9% farms. In Romania, 71.5% farms produce less than Euro2,000, while 0.9% achieve Euro 50,000 and over. Regarding the concentration of farms by SO size class, HHI and GSC reflected a high concentration in Romania, relatively moderate at the EU level, moderate in Poland and Italy, and a lack of concentration in Spain, France and Germany. The SO/AH in Romania was Euro 4,029, compared to Euro 38,703 at the EU level, Euro 19,680 in Poland, Euro 57,681 in Italy, Euro 44,124 in Spain, Euro 158,430 in France and Euro 167,631 in Germany. As a final conclusion, the gaps among these countries are caused by the unbalanced farm structure with the highest share belonging to the farms with less than 2 ha. Farms with 50 ha and over could assure a higher SO/farm. To diminish NAH and grow AHS has to continue for increasing the economic power in terms of standard output. Small and medium-sized farms have to be sustained to join their efforts for a higher concentration of land, production and economic efficiency. [ABSTRACT FROM AUTHOR]

The paper analyzed rural population, rural working age population, civil population occupied in agriculture and agricultural output value using the data from National Institute of Statistics for the period 2008-2020. Trend line, regression equations, coefficient of determination, Spearman's rank correlation coefficient represented the methodological means for processing the data. Romania had still a high labour resource accounting for 6.23 million persons in 2020, by 10% more than in 2008. In the period 2008-2020, the population able to work declined in almost all the regions, except North East and Bucharest Ilfov, but, the rural population having the age to work increased in various proportions in all the regions. However, civil population occupied in agriculture declined by - 30% from 2,407 thousand persons in 2008 to 1,681 thousand persons in 2020. Population aging and migration are the main causes of this decrease. The decline in the territory ranged between -31.3% in North East and -25% in Bucharest-Ilfov. Agricultural production value increased by +21.6% from Ron 66,993 Million in 2008 to Ron 81,400 Million in 2020. In 2020, the highest agricultural output value was achieved in South Muntenia, North East, North West, South West Oltenia, South East. Analyzing the linear dependency between the ranks of civil population occupied in agriculture and agricultural output value, we noticed that in 2008, it was not found such a connection, as Spearman's correlation coefficient was rS = 0.1004, tcrit 6;0.05 was 1,943 and RI = 0.4748 < 0.1943. However, in 2020, between the ranks of the two studied indicators was found a linear dependency reflected by rS = 0.739, RI = 2.26, tcrit 6;0.05 was 1,943, therefore RI > tcrit. As a final conclusion, while the population occupied in agriculture decreases, agricultural production value increases due to the decline in civil population occupied in this economic sector caused by aging and migration, increased performance in agricultural production, grace to technological progress and a better farm management, price volatility for agricultural products, financial support according to the CAP of the EU and Romania's Government. [ABSTRACT FROM AUTHOR]

The paper aimed to analyze the evolution of watermelon market and melon market in Romania in order to identify the main trends in the period 1990-2009 based on statistical data and using the specific indicators such as: cultivated area, yield and production, consumption, trade and price. Despite that the cultivated area remained relatively constant at about 33.5 thou ha, watermelon and melon yield increased by 73.36 % from 11.2 tons/ha in 1990 to 19.5 tones /ha in 2009. As a result, total production reached 652.8 thou tons in 2009, being by 71.06 % higher than in 1990. The main trends identified in watermelon and melon production and market in Romania are the following ones: a constant cultivated and producing area, mainly in the East, West and South parts Romania, a continuous increase of yield and production, a diversified offer consisting both of local and imported watermelons and melons, appearance of extra and early fruit of Romanian origin even from June contributing to a better cover of consumer demand along the summer season, an increased competition among suppliers and also a higher income and profit for Romanian producers. Romania's watermelon and melon market is continuously developing grace to an increased demand for a healthy diet including more vegetables and fruit. [ABSTRACT FROM AUTHOR]