Jitka Kumhálová

The impact of topography on soil properties and yield and the effects of weather conditions

Quantitative knowledge of the factors and interactions affecting yield is essential for site-specific crop management. One of the factors that frequently affects yield is topography. The aims of this study were to compare elevation data obtained from a combine harvester yield monitor and a hand RTK-GPS, and to evaluate the relationships between the spatial variation of cereal yield, selected crop nutrient concentration and topographic attributes derived from the two sources of elevation data. Simple models of elevation, slope and flow accumulation were created from the data of an experimental field in the Czech Republic, and the relations between yield and soil nitrogen and organic carbon contents and topography were determined over a four-year period. The models of elevation, slope and flow accumulation were compared with the yield, and soil nitrogen and organic carbon contents during the growing seasons of 2004, 2005, 2006 and 2007 in relation to total precipitation and temperature. The relationship between yield and topographic attributes was evaluated with the help of geostatistical methods. The results of correlation analysis among the variables were evaluated statistically by forward stepwise linear regression. No significant differences between elevation data from the combine harvester yield monitor and RTK-GPS were found. There was a significant relation between yield and crop nutrient concentration with topography. The correlation coefficients between flow accumulation and yield were weak for the wetter years and strong for the drier years.

Winter oilseed rape and winter wheat growth prediction using remote sensing methods.

Remote sensing is often used for yield prediction as well as for crop monitoring. This paper describes how Landsat satellite data can be used to derive a growth model calculated from normalised difference vegetation index that can predict winter wheat (Triticum aestivum) and winter oilseed rape (Brassica napus) phenological state using the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie scale. Time series of Landsat images were chosen from the years 2004, 2008 and 2012, when winter oilseed rape was grown, and 2005, 2009, 2011 and 2013, when winter wheat was grown in the same experimental field. The images were selected from the whole growing season of both crops. An advantage of this method is the easy availability of the remote sensing and its easy application for deriving a prediction model from vegetation indices. Our results showed that Landsat images, after correct pre-processing, can be used for winter wheat and winter oilseed rape growth model prediction.

Yield variability prediction by remote sensing sensors with different spatial resolution

Abstract Currently, remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView-2 satellite data) spatial resolution, together with GreenSeeker hand held crop sensor, can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud-free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView-2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless, better results, in comparison with crop yield, were obtained for images acquired in later phenological phases, e.g. in 2007 - BBCH 59 - average correlation coefficient 0.856, and in 2011 - BBCH 59-0.784. GreenSeeker handheld crop sensor was not suitable for yield estimation due to different measuring method.

Spatial Variability and Pattern of Selected Properties of Agricultural Soils in the Czech Republic Measured by Indirect Proximal and Remote Sensing

Spatial and temporal variabilities of soil properties were monitored within a 12-ha field over several consecutive years. Particle-size distribution, total carbon content (Ct), and pH were monitored. Soil samples were taken from points on a regular square grid. Additionally, the variability of soil properties was evaluated by proximal measurement methods including draft force measurements, soil electrical conductivity (ECa), and crop yield mapping. Remotely sensed bare-soil satellite images were obtained and digital elevation models were made. All the observed variables showed spatial variability, but the spatial patterns of Ct, pH, EC, and crop yield were temporally stable. Results were processed using statistical and geostatistical methods. Variograms and their parameters were used to describe spatial dependencies between observed variables. Significant dependencies were observed between monitored soil properties and indirect methods, indicating utility in the proximal approach.

SOIL TILLAGE FOCUSING ON THE REDUCTION OF WATER EROSION OF SOIL IN THE CULTIVATION OF SELECTED FIELD CROPS

Water erosion is a problem of global significance. Water erosion destroys or damages a vast expanse of usable agricultural land every year. Conditions in the Czech Republic are characterized by high average slope of the land. It is reported that approximately half of land in the Czech Republic is threatened by water erosion. Water erosion is a natural process that cannot be fully prevented. In case of agricultural land an important option is suitable tillage, which may reduce symptoms of water erosion. The problem of water erosion of agricultural land is growing in the Czech Republic, which is mainly caused by the growth of wide areas of crops (maize). This is due to expansion of biogas power plants using parts of maize silage. The aim of paper is to evaluate and assess the crop stand establishment in conditions of resistance to water erosion. For this purpose, a field experiment was set up. This experiment affects the most widely used methods of maize cultivation in Central Bohemia region. It consists of six variants of crops and technologies stand establishment and control treatment without vegetation. To determine the surface runoff and erosive wash was used measurement by runoff microplots. From processed measurement the positive impact of reduced tillage on soil resistance to water erosion results can be confirmed. The consequence is a reduction of surface runoff and especially erosive washes of soil. Impact of ground cover with organic matter is favorable, even in case of conventional tillage. The results of the experiment are directly applicable to agricultural practices. Results of the experiment were used for the legislative recommendations of appropriate technology (wide-row crops on slopes). Keywords: erosive wash, surface tillage methods, water runoff. Article DOI: http://doi.org/10.15544/RD.2015.015