Different seed priming treatments are widely used in order to improve the nutritional status of wheat, as well as to improve its grain yield and yield- related traits. The present study aimed to evaluate the impact of seed priming with zinc oxide nanoparticles (ZnO NPs) on the yield related traits, such as, field emergence, plant height, spike length and grain yield per plant of four winter wheat genotypes (Triticum aestivum L.) during two vegetation seasons of 2018/2019 and 2019/2020. The seeds of each wheat genotypes were primed with different concentrations of ZnO NPs (0 mg L⁻¹, 10 mg L⁻¹, 100 mg L⁻¹ and 1000 mg L⁻¹) for 48 h in a dark box by continuous aeration and were sown in soil pots with 60–70% moisture content until full maturity. The additive main effects and multiplicative interaction (AMMI) models were used to study the genotype environment effects. The results indicated that the plants response to ZnO nanoparticles significantly increased all of the observed traits of the wheat, while its maximum rates reduced the traits of the wheat. The AMMI analysis revealed the very complex nature of the variation observed in the trial and showed the significant effect of the G×E interaction, in which the first main component was significant for all components.

The less productive soils present one of the major problems in wheat production. Because of unfavorable conditions, halomorphic soils could be intensively utilized using ameliorative measures and by selecting suitable stress tolerant wheat genotypes. This study examined the responses of ten winter wheat cultivars on stressful conditions of halomorphic soil, solonetz type in Banat, Serbia. The wheat genotypes were grown in field trails of control and treatments with two soil amelioration levels using phosphor gypsum, in amounts of 25 and 50 tha−1. Across two vegetation seasons, phenotypic variability and genotype by environment interaction (GEI) for yield traits of wheat were studied. The additive main effects and multiplicative interaction (AMMI) models were used to study the GEI. AMMI analyses revealed significant genotype and environmental effects, as well as GEI effect. Analysis of GEI using the IPCA (Interaction Principal Components) analysis showed a statistical significance of the first two main components, IPCA1 and IPCA2 for yield, which jointly explained 70% of GEI variation. First source of variation IPCA1 explained 41.15% of the GEI for the grain weight per plant and 78.54% for the harvest index. The results revealed that wheat genotypes responded differently to stressful conditions and ameliorative measures.

Maize ranks first among worldwide production and an important source of human and animal feed. Its production can be affected by management practices and climatic conditions. The objective of this study was to estimate stability of yield and hundred grains weight of six maize genotypes during two growing seasons at two locations, subjected to four different treatments: T₁ treatment—without herbicide, Control; T₂ treatment—active substance Nicosulfuron and Motivell commercial preparation; T₃ treatment—active substance Rimsulfuron and Tarot; and, T₄ treatment—active substance Forasulfuron and Equip. Additive main effects and multiplicative interaction—AMMI model and genotype × environment interaction—GGE biplot were used to estimate GEI—genotype by environment interaction. The results showed that the influence of genotype (G), year (Y), locality (L), treatment (T) and all interaction on hundred grains weight were significant. The share of genotypes in the total phenotypic variance was 64.70%, while the share in total interaction was 26.88%. The share of IPCA1 in terms of G × T interaction was 50.6%, while share of IPCA2 was 44.74%, which comprised together 94.80% of interaction. The first IPCA1 axis showed high share in the total interaction, which indicates out significance of genotype in total variation and interaction, while high level of IPCA2 indicates a significant treatment effect. Genotype L-6 had the same mass of 100 grains (37.96 g) during both years of testing, while genotype L-1, with 4.46 g, had the largest difference between years. This clearly indicates the influence of genotype but also stress under the influence of sulfonylureas and environmental factors. The maize genotype with the highest values of hundred grains weight, L-5 and L-6, expressed the highest values of grain yield (4665 kg ha⁻¹ and 4445 kg ha⁻¹).

It has been argued for a long time in academic papers which corporate governance factors have a significant impact on gains of a great number of businessmen. However, such studies rarely examine the impact taxation issues on agriculture. This paper differs from other published papers because its focus is tax on agricultural land in an economy in transition. The primary aim of the authors was to find rules in taxpayers' conduct after being served tax decisions issued by local tax authorities with the assessed tax. The following aim was to find out how tax authorities respond to receiving complaints on the assessed tax lodged by the affected tax payers. The conclusions are as follows: first, there is a difference in tax amounts assessed by local tax authorities relating to property rights of taxpayers resulting from their ownership of agricultural land: second, there is a significant difference in tax amounts assessed following the complaints lodged by taxpayers in all four categories of tax rates set by tax authorities for the four respective zones.

The organization of agricultural production in countries such as the Republic of Serbia should be as close as possible to optimality. This can be achieved in different ways. One of the ways to improve the success and efficiency of business should be seen in the search for the most favorable form of obtaining loans from commercial banks. The paper highlights the importance of analyzing three types of loans, namely: a loan for refinancing intended for agriculture, an investment loan intended for agriculture and a loan for working capital intended for agriculture from the perspective of the efficiency of agricultural operations. A Pearson correlation analysis was performed for the observation period 2021-2022. The main conclusion is that there is a connection between the efficiency of agricultural operations with all three forms of taking loans by agricultural farms on a sample of N =149, that is, the obtained results confirmed this (p<.05). In addition, the study points to the existence of another conclusion, i.e. that the costs related to the taken loans in the observed period have an increase, but they do not have such an impact as the analyzed three forms of loans taken by agricultural holdings, because their impact is in the interval of 0.067 for 2021 to 0.070 in 2022.

The evaluation of the owners of agricultural holdings regarding innovative approaches in business is one of the ways by which the overall quality of business can be raised. One of the modern ways of such observation is the application of software in the business of agricultural farms, and the main goal would be to improve the entire management process in them. The results obtained by the authors through the application of a paired sample using the T-test show the existence of differences in the given ratings of farm owners regarding the introduction of innovative software (p=.00), that is, regarding the application of the software and its practical application in the business of the farm.