Search

This article explores the complexities and opportunities of agricultural value chains from international, European, and Romanian perspectives. Highlighting the importance of efficient value chain management, the exploration examines first the situation at the global level in the countries with a high economic development: USA, China, Germany, Japan and India, as a reflection on how global and regional policies impact agricultural production and distribution. Market dynamics of raw materials and high tech products and services in terms of export, import and trade balance was analyzed in the EU in the interval 2012-2022, based on Eurostat data, emphasizing its role in shaping value chains. The European lens focuses on the Common Agricultural Policy (CAP) and its implications for member states. The Romanian context highlights local challenges and strategies for integrating into broader value chains. From a methodological point of view, there were used various methods and procedures among which the main ones have been: descriptive context of the literature, trend dynamics in raw materials and high tech-products and services in terms of regression equation and R square, fixed basis index for showing the growth rate on the studied period, comparison method, illustrations in tabulated results and suggestive graphics. By analyzing case studies and current trends, the current research provide insights for enhancing economic efficiency, sustainability, and competitiveness in the agricultural sectors. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyze the land use at the global level and in the European Union in the period, 2000-2021, in order to identify the changes and trend pointing out the status of agricultural land and by category of use. Fixed and structural indices and suggestive illustration were used to show the variations and trends for agricultural land, arable land, crop land and permanent meadows and pastures at the global level, for the top countries with the largest agricultural area and in the EU-27 by member states. The global agricultural land decreased, in 2021, being 4,787.5 Million ha, by 1.8% smaller. The world crop land increased to 1,579.8 Million ha in 2021, being by 5.7% larger. Of the global agricultural land, 33% is cropland and 67% permanent grasslands. The larger cropland is in Asia, Americas and Europe. The largest countries in cropland represent 39.3%, while the largest countries in grasslands 23.2%. About 40% of the EU's territory is represented by agricultural land and belongs to France, Spain, Sweden, Germany, Poland, Finland, Italy, and Romania. The EU agricultural land decreased to 162,905.8 thousand ha, being by 10.83% smaller. Cropland declined by 9.4%, and permanent grasslands declined by 13.71%. Cropland accounts for 68%, while permanent grasslands for 32% in the EU. The EU keeps 3.4% of the global agricultural land, 7.01% of crop land and 1.62% of grasslands. In the most EU countries agricultural land declined. In the EU, it is a high concentration of agricultural land, but no concentration in arable land, cropland and permanent grasslands. The world agricultural land per capita declined from 0.24 ha in 2000 to 0.20 ha in 2021. The highest cropland per capita is in Oceania 0.77 ha, Europe 0.39 ha, Americas 0.37 ha, Africa 0.21 ha and Asia with only 0.13 ha. In the EU-27, the average is 36.56 ha agricultural land per capita. The expand of the agricultural land has to be stopped, as it is enough food to nourish the global population. New agro-eco technologies are called to increase crop yield and productivity to protect environment and biodiversity. The reduction in meat production and consumption will protect forests and cropland, and stopping deforestation will orient the people to a healthier and green diet. [ABSTRACT FROM AUTHOR]

The paper aims to present models of agricultural production optimization as tools for managers to increase yield, crop structure, crop rotation, increased efficiency and profitability. The two optimization models are: Case 1: Optimization of yield depending on wheat price and subsidy for increasing net return and profitability in wheat culture; Case 2: Optimal model for optimizing crop rotation in cereal culture with maximum income, having two solutions: (a) Basic optimal primal solution and (b) Basic optimal dual solution. The methodology included the calculations regarding the specific indicators reflecting the economic efficiency in wheat cropping for Case 1 and determination of the optimal primal and dual solutions assisted by SOLVER application from MS Excel for Case 2. The two examples come from vegetal farming but, other models of optimization could be developed in animal production for improving livestock structure by species and category and also in animal feeding setting up optimized feed ratios to sustain production. [ABSTRACT FROM AUTHOR]

The paper aims to identify the main aspects of digitalization in the EU and Romania at present, in general, and emphasizing on agriculture, because in this sector has a deep impact on infrastructure and work resources. The EU average for DESI index quantifying digital economy performance was compared with the index in the member states to show the differences in the performance of the digital economy. The aspects related to the impact of digitalization in agriculture from many points of view, but mainly on human resources have also been highlighted. Index scores differ from one country to another and reflect the performance result of the efforts that each member state has made to implement digital economy. The higher the index value, the higher the digital economy performance in that country. During the period 2017-2022, Finland, Denmark, the Netherlands and Sweden have maintained their top position in the EU, while Romania and Bulgaria are situated on the last places. Romania should be focused on the improvement of digital infrastructure, promotion of digital competences, innovation and entrepreneurship in order to increase its performance in digital economy. Major efforts should be done to improve connectivity, educational programmes in digital competences and to develop a favourable business environment for contributing to its digital transformation and integration into the EU digital unique market. [ABSTRACT FROM AUTHOR]

The paper analyzed the dynamics of cultivated area, production and yield in vegetal sector of Romania's agriculture in the period 2007-2020 and also in the decade 2014-2020 versus 2007-2013 in order to quantify the effects of the implemented agricultural strategy aligned to the EU CAP. The data from National Institute of Statistics were processed using fixed basis indices, structural indices, growth rate, mean, regression models, R square and comparisons between the two decades. In 2020, Romania had 8,263,672 ha cultivated by +6.25% more than in 2007. Crop structure included: cereals 64.6%, oil plants 20.3%, vegetables 2.4%, leguminous plants 1.3% and 1% potatoes. The area cultivated with cereals raised by +4.07% reaching 5,338,067 ha in 2020, of which maize and wheat 87.9%. In the decade 2014-2020 versus 2007-2013, it was registered a larger total cultivated area and also with cereals (wheat and maize), leguminous crops, oil crops (sunflower), but a reduced area with vegetables and potatoes. Cereals production increased by +132.29% accounting for 18,153,714 tons in 2020, of which maize 55.61% and wheat 35.2%. In the period 2007-2020, important production gains were carried out in leguminous grains, oil seeds, fruits and vegetables, but potatoes production declined by -49.63%. In the period 2014-2020 versus 2007-2013, production gains were registered in cereals, wheat, maize, leguminous grains, in oil seeds, sunflower seeds and fruits, but losses by -4.14% in vegetables and -21.26% in potatoes. In 2020 versus 2007, yield level was accounted for 3,400 kg/ha cereals (+123.24%), 2,966 kg/ha wheat (+92.47%), 3,977 kg/ha maize (+160.61%), 1,858 kg/ha sunflower seeds (+184.09%), 15,843 kg/ha potatoes (+15.95%), 21,858 kg/ha tomatoes (+57.07%). In the period 2014-2020 versus 2007-2013, yield gain accounted for: +50.08% cereals grains, +44.7% wheat, +54.18% maize, +61.5% sunflower seeds, +13.13% potatoes and +12.83% tomatoes. In conclusion, the implementation of Romania's strategy of agriculture development in the vegetal sector aligned to CAP has resulted in higher productions and yields of the analyzed groups of crops, except potatoes production which declined by about 50% in 2020 compared to 2007, and also, in the 2nd decade 2024-2020 versus 2007-2013, it was registered a decrease by -4.14% in vegetables and by -21.26% in potatoes, which is justified by the decline in cultivated area. This performance is due to the efforts made by farmers to obtain better results in their business and to the financial support given by the EU and Romanian Government. [ABSTRACT FROM AUTHOR]

The paper aimed to analyze the concentration degree of standard output (SO) and number of agricultural holdings (AH) in the EU countries in the year 2020 by economic dimension in terms of standard output size class. The data collected from Eurostat were used to calculate Gini-Struck coefficient according to which the countries were classified. The EU has a moderate concentration both concerning SO (GSC = 0.3938) and AH (GSC = 0.3276) by SO class. Discrepancies were noticed referred to these two indicators in the member states. Regarding SO, GSC varied between 0.7941 in Denmark and 0.1597 in Romania. Six countries (22.3%) have a low concentration, 12 countries (44.4%) have a moderate concentration and 9 countries 9933.3%) have a high level. 13 countries: Bulgaria, Cyprus, France, Luxemburg, Sweden, Estonia, Hungary, Germany, Belgium, Slovakia, Netherlands, Czechia and Denmark exceeds the EU GSC= = 0.3938. Regarding AH, GSC values ranged from 0.1204 in Denmark and 0.7004 in Romania. A number of 17 countries (63%) registered a low concentration level of the number of farms by SO class, other 9 countries (33.3%) recorded a moderate concentration and one country, Romania (2.7%) had the top position with the highest concentration of the number of farms. Taking into consideration GSC values both for Standard output and number of farms by SO class, it was found that 8 countries (29.3%) have a high concentration of SO and a low concentration of AH; 7 countries (25.9%) have a moderate concentration of SO and a low concentration of AH; 5 countries (18.5%) have a moderate concentration of SO and a moderate concentration of AH, all these three categories summing 73.7%. As a final conclusion, the concentration of standard output by SO class is a moderate one in 44.4% of the EU countries and in 33% is a high. [ABSTRACT FROM AUTHOR]

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 purpose was to assess the impact of climate change on wheat, maize and sunflower yield in the period 2017-2021, using statistical data from National Institute of Statistics (NIS) and National Administration of Meteorology (NAM) and other sources. Comparison method was used to evaluate the deviations between the registered air temperatures and precipitations and the 1981-2010 climatological norm. Graphic method reflected the dynamics of monthly air temperatures and rainfalls in each year. Descriptive statistics for mean, standard deviation and coefficient of variation reflected an more comprehensive image upon air temperature, precipitations and yield. Correlations and regression equations were used to establish the intensity of the kinks between climate factors and yield. The highest average air temperature In Romania was 12.130C in 2019. In the period 2017-2020, the average annual temperatures exceeded the climatological norm 1981-2010 accounting for 9.10C. The lowest rainfalls, 614.2 mm, were recorded in 2019, being below of 633.1 mm the norm for the period 1981-2010. The high temperatures associated with drought and low precipitations have deeply affected yield of many agricultural crops, including maize, wheat and sunflower. The highest wheat yield 4,888 kg/ha was achieved in 2017, and the lowest one, 2,966 kg/ha in 2020. Maize registered the highest performance of 7,644 kg/ha in 2018, and the lowest one, 3,977 kg/ha in 2020. Sunflower carried out the high performance 3,041 kg/ha in 2018, and the lowest one, 1,858 kg/ha in 2020. The worst agricultural years for these three crops was 2020, but 2017 favored wheat, while 2018 favored maize and sunflower. The correlation coefficient had in general small values between average temperature and yield, but a higher link with precipitations level. The multiple correlation between yield, air temperatures and precipitations was: r= 0.817 for wheat, r = 0.116 for maize and r = 0.504 for sunflower. In the South Eastern Dobrogea, the driest area in Romania, the rainfalls declined by 65% in the period 2018-2020 having a deep negative impact on sunflower seeds yield, which decreased from 4,282 kg/ha in 2018, to 1,503 kg/ha in 2020. The correlation between precipitations and sunflower yield positive and very strong (r = 0.737). As a conclusion, the climate conditions should be analyzed in each farm and farmers have to take measure to adapt the technologies for sustaining production. [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 analyzed the use of pesticides in Romania in the period 2007-2020, based on the official statistical data by type of pesticide, at the national and territorial level, and using fixed and structural indices, concentration indices and time and spatial comparisons. In the year 2020, pesticides were applied on larger surfaces than in 2007 and they accounted for 3.88 million ha for herbicides, 2.39 million ha for fungicides, and 2.34 million ha for insecticides. But, the total consumption decreased by 26% for insecticides and by 23% for herbicides, but it increased by 8.2% in case of fungicides. The national mean consumption of pesticides per ha declined and in 2020 accounted for 0.27 kg a.s. insecticide, 0.75 kg herbicide and 0.76 kg fungicide. Romania comes on the last position in the EU for the smallest average consumption 0.8 kg a.s. pesticide per ha and also for the risk indicator 1 equal to 48. The largest areas where pesticides are applied in the territory are in South Muntenia, West, South East and South West Oltenia micro-regions. Total consumption differs from a region to another as follows: insecticides are much more consumed in South West Oltenia, South Muntenia, North East, South East and West, fungicides are especially applied in South East, North East, Center and West, and herbicides are predominantly utilized in North East, South East, North West, South West Oltenia, and West. The average consumption per ha, over the national mean, is higher in the following regions: insecticides in North West, South West Oltenia, Center and North West, fungicides in the Center, Bucharest-Ilfov, South East and North East and herbicides in North East, North West and Center regions. The values of the concentration indices Herfindahl-Hirschman, Gini-Struck and Concentration coefficient proved that in 2020, Romania was characterized by a relative moderate concentration of the use of pesticides. As a conclusion, pesticides have to be used taking into consideration the local conditions at the regional level and at farm level. Farmers have to evaluate the problems and make the best decision regarding what type of pesticide to use, on what surface, which is the suitable dose per ha, how many treatments are required etc. The EU regulations regarding pesticides imposes a strict control and use of the approved pesticides for compiling with the European the Green Deal. [ABSTRACT FROM AUTHOR]