The quantitative effects of temperature and light intensity on accumulation of phenolics were examined on greenhouse-grown plants of Hypericum perforatum L. Plants were grown in a greenhouse separated into two parts: shaded by 50% transparent polyethylene cover and un-shaded. Temperature values and light intensities were measured daily during the experiment, while plants were harvested weekly for HPLC analyses. Multi regression analyses were performed to describe the quantitative effects of temperature and light intensity on phenolics accumulation. According to the results, increases in temperatures from 24°C to 32°C and light intensities from 803.4 µMm-2 s-1 to 1618.6 µMm-2 s-1 resulted in a continuous increase in amentoflavone, apigenin-7-glucoside, cholorogenic acid, hyperoside, kaempferol, rutin, quercetin and quercitrin contents. The relationships between temperature, light intensity and phenolics accumulation were formulized as P= [a + (b 1 x t) + (b 2 x l) + [b 3 x(t x l)]] equition, where P is the content of the corresponding phenolic, t temperature (°C), l light intensity (µMm-2 s-1) and a, b 1 , b 2 and b 3 the coefficients of the produced equation. The regression coefficient (R 2) value for amentoflavone was 0.84, for apigenin-7glucoside 0.87, for cholorogenic acid 0.83, for hyperoside 0.95, for kaempferol 0.76, for rutin 0.70, for quercetin-0.93, and for quercitrin-0.86. All R 2 values and standard errors of the equations were found to be significant at the p<0.001 level. The mathematical models produced in the present study could be applied by Hypericum researchers as useful tools for the prediction of phenolics content instead of routine chemical analyses.

This tutorial is based on modification of the professor nomination lecture presented two years ago in front of the Scientific Council of the Czech Technical University in Prague [16].It is devoted to the techniques for the models developing suitable for processes forecasting in complex systems. Because of the high sensitivity of the processes to the initial conditions and, consequently, due to our limited possibilities to forecast the processes for the long-term horizon, the attention is focused on the techniques leading to practical applications of the short term prediction models. The aim of this tutorial paper is to bring attention to possible difficulties which designers of the predicting models and their users meet and which have to be solved during the prediction model developing, validation, testing, and applications. The presented overview is not complete, it only reflects the author's experience with developing of the prediction models for practical tasks solving in banking, meteorology, air pollution and energy sector. The paper is completed by an example of the global solar radiation prediction which forms an important input for the electrical energy production forecast from renewable sources. The global solar radiation forecasting is based on numerical weather prediction models. The time-lagged ensemble technique for uncertainty quantification is demonstrated on a simple example.

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Hypericum pruinatum is a medicinal herb containing several bioactive compounds with important pharmacological activity. In this study, we investigated the effects of the salt (0.03 -control, 1, 2.5, 4 and 8 dS m -1 of MgSO4, CaCl2 and NaCl salts) and drought stress (80, 100 and 120% of required water) on the content of phenolic compounds, namely chlorogenic acid, rutin, hyperoside, isoquercetine, quercitrine and quercetine in greenhouse grown plantlets. In general, the salt stress especially in elevating doses increased the levels of all of the compounds analysed, whereas drought stress did not cause a significant chance in chemical content of the plantlets. The present results indicated that abiotic stress factors, particularly salinity, have a marked influence on the content of phenolic constituents in H. pruinatum and it is a salt tolerant species. The results also indicated that phenolic compounds play a significant physiological role in salinity tolerance.

This study was conducted to assess the influence of different salinity and irrigation water treatments on the growth and development of sweet basil (Ocimum basilicum L.). Five salinity levels (0.4, 1.00, 2.50, 4.00 and 8.00 dSm-1) and three different irrigation water regimes (80, 100, 120% of full irrigation) were applied in a factorial design with three replications. Dry root weight, aerial part dry weight and aerial part/root ratio were determined and evaluated as experimental parameters at the end of growing period. Results revealed significant decreases in yields with increasing salinity levels. However, basil managed to survive high salt stress. With increasing salinity levels, decreases in growth were higher in roots than in leaves. Changes in the amount of irrigation water also significantly affected the evaluated parameters.

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