The present study assessed the effect of projected climate change on the sowing time, onset, and duration of flowering, the duration of the growing season, and the grain yield of spring barley in Northern Serbia. An AquaCrop simulation covered two climate model integration periods (2001–2030 and 2071–2100) using a dual-step approach (with and without irrigation). After considering the effect of climate change on barley production, the economic benefit of future supplemental irrigation was assessed. The model was calibrated and validated using observed field data (2006–2014), and the simulation’s outcomes for future scenarios were compared to those of the baseline period (1971–2000) that was used for the expected climate analysis. The results showed that the projected features of barley production for the 2001–2030 period did not differ much from current practice in this region. On the contrary, for the 2071–2100 period, barley was expected to be sown earlier, to prolong its vegetation, and to shorten flowering’s duration. Nevertheless, its yield was expected to remain stable. An economic feasibility assessment of irrigation in the future indicated a negative income, which is why spring barley will most likely remain rain-fed under future conditions.

Credit risk assessment of agricultural enterprises in the Republic of Serbia was analyzed in this research by applying discriminant analysis and logistic regressions. The aim of the research is to determine the financial indicators which financial analysts consider when analyzing a loan application that have the most influence on the decision to approve or reject a loan application. The internal determinants of credit risk of agricultural enterprises are analyzed, i.e., indicators of financial leverage, profitability, liquidity, solvency, financial stability and effectiveness. The analyzed models gave different results in significance of the observed indicators. The indicators that stood out as significant in both models are only indicators of profitability and solvency. The model of discriminant analysis has successfully classified rate 81.0%, while the logistic regression model has successfully classifies rate 89.8%. In modeling the credit risk of agricultural enterprises in the Republic of Serbia, the logistic regression model gives better results.

Organic agriculture represents an alternative system of agricultural production that is included in the so-called sustainable agricultural practices. Development strategies in almost all countries today highlight the problem of environmental degradation, which is partly caused by the application of agrotechnical measures used in conventional agriculture. Consequently, organic production is gaining more and more importance, affecting the trend of its development. Considering the status of the Republic of Serbia as a candidate country for the European Union, it is of particular importance to understand the Common Agricultural Policy (CAP) of the EU and the position that organic producers and production have. The aim of this research was to analyze the attitudes of organic producers towards the CAP and the agrarian policy of the Republic of Serbia and their expectations following the Republic of Serbia’s entry into the EU. Statistical data processing involved descriptive statistical analysis followed by binary logistic regression. The results of the research showed that organic producers are not sufficiently familiar with the CAP, they believe that the agricultural policy of the Republic of Serbia is not favorable for organic producers and that their situation will not change significantly with entry into the EU, but that the position of organic production in the EU is better in comparison to that of the Republic of Serbia. In conclusion, the authors state that such attitudes and thoughts of organic producers are a limiting factor in the further development of organic agriculture and that it is necessary to work on them through continuous measures developed by competent ministries, local self-governments and advisory services.

This paper evaluates the eco-efficiency of crop production in the European Union (EU) and the Republic of Serbia for the period 2015–2023, using a stochastic frontier analysis (SFA) model based on panel data. Eco-efficiency was assessed as the ratio of agricultural output to key environmental pressures, with expenditures on fertilizers, plant protection products, and energy serving as proxies for ecological burden. The analysis shows that the average eco-efficiency score (Total EE) across the sample is 59.26%, implying that nearly 41% of inputs could be reduced without decreasing output. Decomposition reveals high residual eco-efficiency (93.62%) and lower persistent eco-efficiency (63.30%), suggesting that systematic inefficiencies dominate and are primarily linked to internal farm-level factors such as management practices, organizational structures, and technology adoption. Serbia’s total eco-efficiency score of 63.0% places it close to the EU average, confirming structural similarities with Southern and Eastern European countries. Eco-efficiency scores exhibit notable cross-country variation, ranging from approximately 35% to 96%. About 59% of countries fall within the 50–75% interval, while roughly 11% exceed 75%, indicating considerable scope for further improvement. Cluster analysis further indicates that while Serbia belongs to the lower-intensity group, it has significant potential to converge toward EU frontrunners through farm-level improvements. The findings highlight the importance of targeting internal determinants of efficiency, while recognizing that policy measures can provide enabling conditions and long-term incentives for the green transition. A coherent policy for the green transition should prioritize farm-level structural upgrades, such as technology adoption, advisory and knowledge transfer, and sustainable nutrient and soil management, supported by enabling CAP instruments (eco-schemes and GAEC) and IPARD measures to accelerate improvements in resource efficiency and environmental performance.

Summary: Owing to the fact that the EU is committed to reducing greenhouse gas emissions by 20% below 1990 levels by 2020, and having in mind their high dependence on import of oil and oil derivatives, which, in turn, causes instability of power supply, increasing attention is being paid to renewable energy sources. Given the ongoing pre-accession process of the Republic of Serbia in relation to the EU, in order to determine the capacity of the country to increase the share of energy use from renewable sources, in this paper clustering of selected regions in the EU-28 has been carried out, after which a comparative analysis of regions was performed in terms of potential of agricultural biomass, for the purpose of generating energy. The aim of this study is to determine the level of the region of Vojvodina in relation to ten selected EU regions, based on parameters that affect the potential for using renewable energy sources, primarily residues from agriculture. By applying the K-means method, Borda count method and comparative analysis, and based on empirical data, results show that the region of Vojvodina takes a significant fifth place. Its share of agricultural land ranks it as the first, whereas production of cereals and the total number of farms larger than 100 ha rank it as the second. It could be concluded that Vojvodina is an agricultural region with large quantities of plant remains, primarily those left over from harvest, which represents a significant potential for energy generation from agricultural biomass.

The paper analyzes the determinants of profitability of microagricultural enterprises that operated in the Republic of Serbia, the analysis was carried out for the period from 2010 to 2019. Using panel regression analysis, the influence of various microeconomic and macroeconomic determinants on profitability, measured by the rate of return on assets, was examined. The following indicators were observed as microeconomic determinants of profitability: liquidity, financial leverage, indebtedness, asset structure indicator, total business asset turnover ratio, fixed asset turnover ratio, current asset turnover ratio, inventory turnover ratio, trade receivables turnover ratio and sales rate. Indicators of the growth rate of the gross domestic product and inflation were observed as macroeconomic determinants of profitability. Based on the results of the panel regression analysis, it was determined that the turnover ratio of total business assets, the turnover ratio of current assets and the growth rate of the gross domestic product have a positive and statistically significant influence on the profitability of the observed companies. Indebtedness, an indicator of asset structure and the turnover ratio of fixed assets have a negative and statistically significant impact on the profitability of the observed companies. It is expected that the obtained results will be useful to all interested parties in agribusiness, primarily in the context of the analysis of factors that have been determined to have a negative impact on the profitability of the observed companies.