Arbuscular mycorrhizal (AM) fungi are key soil symbiotic microorganisms, intensively studied for their roles in improving plant fitness and their ubiquity in terrestrial ecosystems. Research on AM fungi is difficult because their obligate biotrophic nature makes it impossible to culture them in the absence of a host. Over the last three decades, Ri T-DNA transformed roots have been the gold standard to study AM fungi under in vitro conditions. However, only two host plant species (Daucus carota and Cichorium intybus) have been routinely used to in vitro propagate less than 5% of the known AM fungal species. There is much evidence that host identity can significantly affect AM symbioses, therefore, we investigated any potential host-specific effects of two novel Ri T-DNA transformed root species, Medicago truncatula and Nicotiana benthamiana, by associating them with seven AM fungal species selected based on their contrasting behaviors when grown with Ri T-DNA transformed D. carota roots. To evaluate the performance of new Ri T-DNA transformed roots to host and propagate AM fungal species, a factorial set-up was used to generate nine unique pairs of hosts (M. truncatula, N. benthamiana, D. carota) and AM fungi (Rhizophagus irregularis, R. clarus, Glomus sp.). Using statistical modeling, all pairs of hosts and AM fungi were compared by their symbiosis development (SD) and sporulation patterns in the hyphal compartments (HCs) of two-compartment Petri dishes. Our results show that 1) most of the variation between host and AM fungus pairs relating to SD or HC sporulation was explained by an interaction between host and AM fungal identity, i.e., host identity alone was not sufficient to explain AM fungal behaviour, 2) AM symbioses involving different combinations of symbiont identities trigger heterogenous fungal behaviours. This work provides a robust framework to develop and evaluate new Ri T-DNA roots for the in vitro propagation of AM fungi, an important asset for germplasm collections and biodiversity preservation.

The dissertation deals with the accounting aspects of assessing the financial health of a company with a focus on agriculture. The main objective of this study is to assess individual methods designed to evaluate the financial health of a company, to determine their sensitivity to risk data in accounting. The study is focused on the field of agriculture mainly as a result of knowledge about the difficult process of compiling and using agricultural accounting. Agriculture fall within the primary sector of the economy, is very important for landscaping and a lot of subsidies flow from the budget of state and the European Union. Due to the specifics and stated problematic areas, which cannot be fully captured by legislation, incomplete or distorted information is transmitted, being also transferred to the methods of the financial health assessment of the company. Attention is also paid to the influence of legislative changes on the values in accounting as well as creative accounting. Following the findings from the theoretical basis, the application part analyses the impact of different accounting solutions on the financial statements. A paired t-test, used for the analysis, was preceded by data normality testing using the histogram and Shapiro-Wilk test. According to these tests, statistically significant differences were found com-paring the current method of accounting used for investment subsidies and leases with the IFRS accounting, between the accounting of changes in inventories and capitalization before and after 1 January 2016, and in land valuation using historical cost and market price. All these areas influence the values of all the analysed methods of financial health assessment. Only the CH-index showed no statistically significant difference in land valuation and accounting solution of inventory activation and changes. Furthermore, the reliability and controllability of the selected methods used for the evaluation of financial health in the field of agriculture is assessed. According to the results, none of the evaluated models can be used in its original variant, but it is possible to use them to compare the company with similar enterprises or over time thanks to the proven dependence of partial indicators and even the whole models on the productivity. Another type of analysis is designed to determine the indicators that have a statistically significant impact on the actual financial situation of businesses. The method of generalized linear models - multinomial linear regression - is used for this test. To determine whether an enterprise is at risk or not, it would be possible to use the stock / income and short-term liabilities / income indicators, and the cash flow / assets indicator to determine the type of threat.