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  • Author: Jana Klimešová x
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Maize transpiration in response to meteorological conditions


Differences in transpiration of maize (Zea mays L.) plants in four soil moisture regimes were quantified in a pot experiment. The transpiration was measured by the “Stem Heat Balance” method. The dependence of transpiration on air temperature, air humidity, global solar radiation, soil moisture, wind speed and leaf surface temperature were quantified. Significant relationships among transpiration, global radiation and air temperature (in the first vegetation period in the drought non-stressed variant, r = 0.881**, r = 0.934**) were found. Conclusive dependence of transpiration on leaf temperature (r = 0.820**) and wind speed (r = 0.710**) was found. Transpiration was significantly influenced by soil moisture (r = 0.395**, r = 0.528**) under moderate and severe drought stress. The dependence of transpiration on meteorological factors decreased with increasing deficiency of water. Correlation between transpiration and plant dry matter weight (r = 0.997**), plant height (r = 0.973**) and weight of corn cob (r = 0.987**) was found. The results of instrumental measuring of field crops transpiration under diverse moisture conditions at a concurrent monitoring of the meteorological elements spectra are rather unique. These results will be utilized in the effort to make calculations of the evapotranspiration in computing models more accurate.

Open access
Ordinal regression model for pea seed mass


The development of seeds at various positions in the pod is asynchronous. Thus, the differences of seed dry mass production because of environmental conditions may depend on the cultivar type, type of inoculants and interrelations between seeds per pod, pods per plant or seeds per plant. Presently, a mathematical description of pea seed categorisation is missing. The aim of the study was the assessment of two groups of variables (quantitative and qualitative) for pea seed weight categorisation by ordinal regression model. Year, cultivar and inoculant constituted the first group (qualitative variables), whilst seeds per pod, the pods per plant and seeds per plant (quantitative variables) were entered as covariates in the ordinal regression model. According to the ordinal regression model variables, seeds per pod, pods per plant, seeds per plant, year and cultivar are meaningful predictors of the seed mass categories. However, the variable inoculant is marginally significant.

Open access