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Sorghum is a forage species important in animal nutrition with an increased potential in the upcoming difficulties in agricultural practices in regard to climate change. Therefore, this paper describes its yield and nutritional parameters depending on growing conditions simulated on two locations (humid and fertile Obora, less fertile and dry Písky), two sowing dates (29. 5. and 25. 6.), and variety (11 varieties). Fresh matter yield was determined by weighing the sample on the field immediately after harvest, Dry matter yield and nutritional content were determined in laboratory by Weende analysis from dried and homogenized samples. Nutritional parameters measured were crude fibre, fat, nitrogen and ash content. Additionally, digestibility of organic as well as dry matter was determined. No significant differences in average fresh matter yield or dry matter yield were found between the two locations and sowing dates in general. There were significant differences among varieties, the highest yields were measured in KWS Zerberus (51.57 ± 3.76 t/ha of fresh matter yield, 15.98 ± 1.34 t/ha of dry matter yield, with higher values observed on Písky). Our data suggest, that sowing date does significantly affect fat content (higher in June sowing). Other nutritional parameters were also higher in sorghum sown in June, with the exception of ash. Nutritional composition of samples did not significantly differ variety to variety, however, there were differences in digestibility of the biomass. Organic matter digestibility was 70.58–85.67%, dry matter digestibility was 73.21–86.70%, with highest digestibility in DMS 45-480. Varieties with the highest importance to farmers in the area are KWS Zerberus, KWS Tarzan and KWS Kallisto (based on dry matter yield), and Triumfo BMR, Sweet Susana and DSM 45-480 (based on digestibility). Sorghum was able to perform well even on dry sandy soil with lower fertilization, which shows the high variability and suitability of sorghum in agricultural practice. [ABSTRACT FROM AUTHOR]

Drought (similarly as flooding) is considerably the gravest agrometeorological extreme connected with climate change and bringing the highest losses in an agricultural production. The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in the Czech Republic, per decade, during the 55-year period (1961 - 2015). AI is a climatic index, which is important for recording of the drought phenomenon evolution. The climatic data used, include monthly precipitation totals and air temperature from 120 meteorological stations operated by the Czech Hydrometeorological Institute. The potential evapotranspiration was calculated based on the modified algorithm Penman-Monteith. The data processing was done by the statistical tools of Microsoft Excel and the Geographical Information Systems (Clidata GIS, ArcGIS 10). The results of the analysis showed, that during the decade 1961 - 1970, almost the whole area of the Czech Republic is classified as "wet" with AI values ranging above 0.60, but over the next years (1971 - 2015), areas of the south Moravia (e.g. Dyjsko-svratecký ravine, Valticko-lednický area, surroundings of Brno city), and also Prague city and Poohří river basin shifted gradually to "sub-humid" climate zone with AI < = 0.60. Especially, during the pre-last decade of the study period 1991 - 2000. [ABSTRACT FROM AUTHOR]