Timely and reliable prediction of grain yield and quality of spring barley represents a key prerequisite for effective crop management. Within this study we evaluated the relationships between yield components, grain quality, biomass production and the number of tillers in different growth stages. For this purpose, in three years (2011)(2012)(2013) multifactorial field trials focused on the combined effects of cultivar, sowing density and nitrogen nutrition were conducted. Based on ANOVA it was found that the formation of grain yield was affected by individual factors in the following order of importance: year, nitrogen, cultivar and sowing rate. The final grain yield significantly correlated both with the number of tillers and dry weight of above-ground biomass per unit area. The best estimation of yield provided both parameters at early growth stage (R = 0.83** and 0.81** for number of tillers and the above-ground biomass at BBCH 25). The grain protein content was inversely related to early growth parameters (R = -0.64** and -0.41** for number of tillers and above-ground biomass at BBCH 25). Based on the comparison of relationships between the years, it can be concluded that the early growth of barley and tiller differentiation is a key parameter for the formation of yield and grain quality.
ABSTRACT:Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as aboveground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of aboveground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 -0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower relationship to vegetation indices. Total amount of aboveground biomass was identified as the most important factor influencing the values of vegetation indices. Based on the results can be assumed that UAV and satellite monitoring provide reliable information about crop parameters for site specific crop management. The main difference of their utilization is coming from their specification and technical limits. Satellite survey can be used for periodic monitoring of crops as the indicator of their spatial heterogeneity within fields, but with low resolution (30 m per pixel for OLI). On the other hand UAV represents a special campaign aimed on the mapping of high-detailed spatial inputs for site specific crop management and variable rate application of fertilizers.
This paper examines the relationship among chlorophyll meter Yara N-Tester readings, nutrition status and growth parameters (leaf area index (LAI), plant height) of the winter wheat plants. Data used in this study were collected in 2010 from two fields located in the Czech Republic (area 52 and 38 ha) from different farms, both with uniform and conventional crop management. The monitoring of crop stands was done at growth stage BBCH 30 in a regular sampling grid with 150 m distance between points (27 and 18 points). At each sampling point, the plant height, LAI (Delta-T SunScan) and the chlorophyll concentration (Yara N-Tester) were recorded. Plant samples were taken to analyse the content of main nutrients (N, P, K, Mg, Ca and S). The results of plant analysis showed that both fields were in different nutrition status: one in a correct status and another had a complex nutritional deficit (K, Ca and N). Linear regressions and ANOVA proved that under a multiple nutritional deficit, N-Tester readings responded to the growth of the crop, while in the adequate nutritional conditions the sensitivity of N-Tester to the variation in the nitrogen concentration is lower. The relationships between crop parameters and chlorophyll meter readings are not generalisable and thus the interpretation of N-Tester results has to be done separately for each field.
ABSTRACT:Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as aboveground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of aboveground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 -0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower relationship to vegetation indices. Total amount of aboveground biomass was identified as the most important factor influencing the values of vegetation indices. Based on the results can be assumed that UAV and satellite monitoring provide reliable information about crop parameters for site specific crop management. The main difference of their utilization is coming from their specification and technical limits. Satellite survey can be used for periodic monitoring of crops as the indicator of their spatial heterogeneity within fields, but with low resolution (30 m per pixel for OLI). On the other hand UAV represents a special campaign aimed on the mapping of high-detailed spatial inputs for site specific crop management and variable rate application of fertilizers.
This study assessed the impact of using soil tillage in maize crops on weed infestation intensity and weed species composition. A field experiment was established as a model example of livestock production management in drier climate conditions where maize was grown in seven-step crop rotation sequence: alfalfa – the first year, alfalfa – the second year, winter wheat, forage maize, winter wheat, sugar beet, and spring barley. Three soil tillage treatments were applied: conventional tillage (CT), minimum tillage (MT), and no-tillage (NT). An arithmetic method and multivariate analyses of ecological data were used. The highest weed infestation, mainly due to late spring species, was recorded in MT. Perennial and overwintering species were frequently observed in NT. Early spring weed species were abundant in CT. Different tillage treatments cause a significant change in the weed species spectrum in maize. A study of the relationship between tillage and the level of weed infestation requires long-term monitoring which will allow us to predict the intensity of weed infestation in particular locations.
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.
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