J. Catalão , “ Computer simulation of wind power systems: power electronics and transient stabilityanalysis ,” in Int. Conf. Power Sys. Trans. , Kyoto , Japan . 2009 .  B. Sun , H. Zhengyou , Y. Jia , and K. Liao , “ Small
In a long-term experiment set up in Martonvásár (N 47°21′, E 18°49′), Hungary in 1960 on a humous loam soil of the chernozem type, the effect of five crop production factors in increasing maize yields was studied in seven treatments. The factors studied were soil cultivation, fertilisation, plant density, variety and weed control. All the factors had a favourable and an unfavourable level. Yield data recorded over 42 years were evaluated using analysis of variance and stability analysis. The highest yield (8.59 t ha
) was obtained when all the production factors were favourable and lowest (2.09 t ha
) when these factors were unfavourable. When only one factor was unfavourable and all the other factors were favourable the following yields were obtained (t ha
): soil tillage: 8.32, fertilisation: 5.21, genotype: 4.98, plant density: 6.31 weed control: 7.01. The crop production factors contributed to the increase in maize yield in the following ratios (%): fertilisation 30.6, variety 32.6, plant density 20.2, weed control 14.2, soil cultivation 2.4. The highest value of the coefficient of variation (CV%) was obtained when all the production factors were at the unfavourable level (45.7%) and when weed control or fertilisation were unfavourable (36.6% and 34.8%, respectively), while the lowest value was recorded when all the factors were favourable (19.5%). The significant treatment × year interaction could be attributed principally to treatments in which weed control, fertilisation, genotype or all the factors were unfavourable. The regression coefficient of linear regression analysis provided a satisfactory characterisation of the stability of the treatments in different environments, while the distance between the straight lines expressed the yield differences between the treatment pairs. The AMMI (Additive Main Effect and Multiplicative Interaction) model proved to be a valuable approach for understanding agronomic treatment × environment interactions and assessing the mean performance and yield stability of treatments.
Long-term experiments are indispensable for investigations on the long-term effects of various crop production methods and technologies. The long-term experiments set up in Martonvásár by Béla Győrffy are now 50 years old and can be considered as part of the national heritage. The most important of these experiments involve crop rotation vs. monoculture trials, the comparison of fertilisation systems, studies on the interactions and carry-over effects of organic and mineral fertilisers, fertiliser rate experiments and polyfactorial experiments. The long-term experiments in Martonvásár form an integral part of maize and wheat research and provide a place for testing the agronomic responses of maize hybrids and wheat varieties. Valuable scientific results are obtained from these experiments regarding the reasons for yield depression in monocultures, the yieldincreasing effect of crop rotations, the comparative benefits of organic and mineral fertilisation, the agronomic responses of genotypes, the sustainability and yield stability of crop production techniques, and the interaction between various crop production factors. These results promote the improvement of maize and wheat production and are regularly incorporated into recommendation systems. The present generation of scientists has a responsibility to maintain these experiments, so that they can continue to serve their purpose in the coming decades.
Authors:Monika Dąbrowska, Jan Krzek, and Ewa Miękina
The stability of cefaclor and its inclusion complex of β-cyclodextrin was investigated, including an effect of pH solution, temperature, and incubation time. Favorable retention parameters (RF, Rs, α) were obtained under developed conditions, which guarantee good separation of studied components. The degradation processes were described with kinetic and thermodynamic parameters (k, t0.1, t0.5, and Ea). The identification of degradation products was performed with the application of proton nuclear magnetic resonance spectrometry and thin-layer chromatography with densitometry.