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The results of 81 different crop management practices in spring barley grown in small-plot field trials on fertile soils in central Moravia were assessed during 2014-2016 with the aim to achieve the highest gross margin (GM - calculated as the difference between revenues and direct costs). GM was most affected by protein content in the grain below 12% corresponding to malting quality. Analyses identified greater determination level of non-linear relationships between stand structure elements and the content of nitrogen substances in the grain. This indicates that the probability of obtaining high quality malting barley is increased when a high level of sinks (number of grains/m2) corresponding to availability of sources, mainly water, is formed by optimal plant density (300-400/m2) and balanced combination of both structural elements of crop stand, i.e. - number of spikes per plant (2-4) and number of grains per spike (18-26). In case that the high level of sinks will be formed predominantly by one element, the risk of higher protein content in grain increases. This constitutes the requirement of early sowing and uniform, synchronized tillering and efficient use of nitrogen fertilizers.

The objective of this study was to evaluate the effect of a year of cultivation and three agronomic measures (pre-crop, soil tillage, application of fungicides) on the yield of winter wheat grown in the crop rotation without the livestock production. The results from the years 2011-2017, except for the year 2012, from the Žabčice Field Experimental Station (49°01'20''N, 16°37'55''E) were evaluated. The soil texture is clay loam soil and the soil type is fluvisol. In the field trial, winter wheat was grown after two pre-crops (winter wheat, pea). Two soil tillage technologies, namely the conventional tillage - CT (ploughing - at a depth of 24 cm) and the minimum tillage - MT (shallow loosening - at a depth of 15 cm) were used. Two fungicide treatments against leaf and spikelet diseases were used, and they were compared to the non-treated variants. The obtained results showed that the grain yield of winter wheat was statistically influenced not only by a year of cultivation, but also by the pre-crop, the application of fungicides, and mostly by the interaction of these factors with the soil tillage. The importance of pea as a suitable pre-crop for winter wheat was confirmed as the grain yield was higher compared to winter wheat as a pre-crop by an average of 0.49 t/ha. It was also found that the MT is a more appropriate technology than the CT, on average by 0.12 t/ha over the six years. The importance of fungicide treatment was also confirmed, where the grain yield of winter wheat was higher by 0.26 t/ha compared to the non-treated variant. The presented results brought a new knowledge for winter wheat management practice in dry conditions.

Malting barley requires sensitive methods for N status estimation during the vegetation period, as inadequate N nutrition can significantly limit yield formation, while overfertilization often leads to an increase in grain protein content above the limit for malting barley and also to excessive lodging. We hypothesized that the use of N nutrition index and N uptake combined with red-edge or green reflectance would provide extended linearity and higher accuracy in estimating N status across different years, genotypes, and densities, and the accuracy of N status estimation will be further improved by using artificial neural network based on multiple spectral reflectance wavelengths. Multifactorial field experiments on interactive effects of N nutrition, sowing density, and genotype were conducted in 2011–2013 to develop methods for estimation of N status and to reduce dependency on changing environmental conditions, genotype, or barley management. N nutrition index (NNI) and total N uptake were used to correct the effect of biomass accumulation and N dilution during plant development. We employed an artificial neural network to integrate data from multiple reflectance wavelengths and thereby eliminate the effects of such interfering factors as genotype, sowing density, and year. NNI and N uptake significantly reduced the interannual variation in relationships to vegetation indices documented for N content. The vegetation indices showing the best performance across years were mainly based on red-edge and carotenoid absorption bands. The use of an artificial neural network also significantly improved the estimation of all N status indicators, including N content. The critical reflectance wavelengths for neural network training were in spectral bands 400–490, 530–570, and 710–720 nm. In summary, combining NNI or N uptake and neural network increased the accuracy of N status estimation to up 94%, compared to less than 60% for N concentration.

The aim of this study was to analyse the sets of atmospherically corrected Remote Sensing (RS) data in order to assess the variability of bare arable land between different soil blocks in the selected area and evaluate the suitability of this approach for locally targeted management. The study was carried out on the territory of parts of South Moravian, Vysocina and Zlín regions. The RS data was analyzed by two models developed in the Arc GIS 10.22 environment using the Normalized Differential Vegetation Index (NDVI) and the Principal component analysis (PCA) analyzing bare soil (BS) with more than 50 % and more than 95 % of the block representation. A layer of agricultural land from the LPIS system was used to delimit arable land areas. For correct determinig of BS value for NDVI were carried out the terrestrial measurements in the monitored area by using the GreenSeeker handheld crop sensor and The FieldSpec® HandHeld 2 spectrometer. Based on these measurements and image dates, 0.2 NDVI was selected as the limit value. As a more suitable source for identifying BS, RapidEye appears to be able to identify an average of 26 % of the observed area as bare ground compared to Sentinel 2 data (22.5 % of the observed area) in models with more than 50 % By representing the BS in a block (NDVI 50, PCA 50). In these versions of the model was more variable soil (VS) indicated by RapidEye. With more than 95 % of the BS in the block (NDVI 95, PCA 95) was found more variable soils by Sentinel 2. This method of indirectly identifying soil variability can assist in the application of fertilizer or soil treatment in the area of site‑specific management.

The results of small-plot field trials of international comparisons of a series of crop management practices for winter wheat grown during 2014-2016 on fertile soils of Central Moravia were assessed. The objective of the experiments was to obtain the highest gross margin (GM), which is the difference between revenues and direct costs. The analyses showed that an optimal level of inputs and costs for obtaining the highest GM could exist. In the assessed series of crop management practices, the optimum input costs corresponded to 11 000-12 000 CZK/ha and 6-9 input measures. At high levels of grains (above 10 t/ha), higher values of GM were obtained by increased efficiency of inputs, but not by increasing their amount to maximize the yields. This indicates the multifunctional and synergic effects of production factors, which can be used at the so-called ecological intensification. Optimizations of inputs can be obtained rather by crop protection than by crop nutrition, which means rather in protection of high yields than in their maximization. Under field conditions, soil and plant processes affected by weather cannot be controlled. Therefore, optimisation of production factors is based both on scientific findings and practical agronomic experience. That is why a universal crop management practice with increased economic and ecological effects cannot be practically proposed.

Historical evolution of approaches used for the assessment of the cereal stand structure development is presented. Weaknesses and strengths of these approaches are discussed that are based on: - dividing of cereal yield into yield components and growth analysis, - modular concept of plant growth, - use of laws of plant population biology in order to explain autoregulation and compensation in stands.The presented methods are assessed with respect to labour intensity and possibilities of utilization of obtained information. Other possibilities of diagnostics of the cereal stand state and structure using a current level of knowledge and new technologies enabling to determine spectral characteristics of the stand by areal sensing are outlined. Based on the character of processes influencing the stand structure, the growing season of cereals was divided into the three parts:1. vegetative, including the period from emergence till the end of tillering (BBCH 10-29),2. generative, including the period of stem elongation and heading (BBCH 30-59),3. reproductive, including anthesis, grain formation and maturation (BBCH 60-99).To optimize the stand structure, data necessary for decision making in cereal crop management practices were proposed for the above listed development stages.

Our study offers:A review of basic indicators important for sustainability assessment of arable farming (balance of nutrients, organic matter and energy, pesticide use, biodiversity and soil protection); A review and way of expression of the most frequent indicators for assessment of the above characters and impact of farming on the environment including the methods for a complex assessment of agricultural enterprises in which individual indicators have been used;A knowledge and practical experience of using of the indicators for assessment in agricultural enterprises.

The contribution is aimed at the assessment of recommended crop management practices of chosen cereals for organic farming. To increase competitiveness, these practices are modified depending on soil and climatic conditions, and on a way of production use. Furthermore, impacts of the recommended crop management practices on economics of growing chosen cereals are evaluated and compared with economic results obtained under conventional farming. It is assumed that achieved results will contribute to the increase in proportion of arable crops in the Czech Republic where organic production offer does not meet current demands.When evaluating results of growing individual cereal species in a selective set of organic farms, triticale, spelt and spring barley (in this ranking) can be considered as profitable crops. Moreover, triticale and spelt have even higher gross margin under organic farming than under conventional farming (by 62 % in triticale). Oat brings losses, however, it is important for livestock production. Winter wheat seems to be also unprofitable since less grain is produced at lower imputs per hectare and only part of it is produced in quality “bio”, i.e. marketed for higher prices. Rye also brings losses under organic farming, particularly due to lower yields, similarly to the other mentioned cereals. Special cereal species that are still neglected in organic farming systems are of potential use. Durum wheat has vitreous kernels with a high content of quality gluten which is used for pasta production. It can be grown in the maize production area on fertile soils only.

Long term stationary field experiments with continuous spring barley were conducted in the maize-growing region on heavy gleic fluvisol from 1974 to 2002. Two variants of straw management (straw harvested and incorporated into soil), two variants of soil tillage (conventional plough tillage to 0.22 m, shallow disc tillage to 0.12–0.15 m) and three variants of fertilization (30, 60 and 90 kg. N ha–1) were studied. The results of organic matter balance in the examinated period according to particular methods were related to trends of real humus content which is presented in Cox in particular experiment variants. The examinated method by LEITHOLD et al. (1997), used in model Repro, answers most accurate in given conditions according to hypothesys defined in scientific literature. On the base of this result we can confirm significancy of the result. Other verification of method is appropriate for its using in real conditions in context of agricultural sustainability assesment.

Abstract Objective Turn sections represent the second largest part of total race time in 1500 m freestyle races and may substantially affect race results. Therefore, the aim of the study was to investigate individual race strategies and compare the effect of start, swim, and turn performances between short-course and long-course races. Video footages were collected from all 16 male finalists at the 2018 short and 2019 long-course World swimming championships (age 23.06 ± 2.3 years, FINA points 941 ± 42) for subsequently analysis of start, turn, and swim performance. Results The larger number of turns in short-course races resulted in significantly faster race times (p = 0.004), but slower mean turn times compared to long-course races (p

Particle Image Velocimetry measurements of the liquid velocity fields in the flow over the backward-facing step were performed in the same flow configuration as in the existing Direct Numerical Simulation (DNS). The experiment and the simulation were performed in an identical cross-section geometry with step expansion rate 2.25 and the square shape of the outlet duct at the Reynolds number in an inlet part of the section 7100. The experiment was performed in transparent test section, 1.2 m long, with 20 × 45 mm2 cross-section upstream and 45 × 45 mm2 downstream, while a domain that was three times shorter was used in the DNS. A 2D-2C PIV system with a single high-speed camera and a pulse laser was used for a series of two-dimensional measurements of the velocity field at several cross-sections from two different perspectives. Variables analyzed in the experiment are time-averaged fluid velocities, velocity RMS fluctuations and two components of the Reynolds stress tensor. The key novelty is the comparison of two very accurate approaches, PIV and DNS, in the same cross-section geometry. Comparison of the similarities, and especially the differences between the two approaches, elucidates uncertainties of both studies and answers the question on what kind of agreement is expected when two very accurate approaches are compared.