Yield and soil coverage of catch crops and their impact on the yield of spring barley

The aim of experiment was to evaluate the impact of catch crops on the yield of spring barley. An assessment of the suitability of catch crops in relation to their yield and soil coverage was made. The field experiment was set up in a corn-growing area (south Moravia, Czech Republic). The results show a statistically significant difference in yield of dry matter and soil coverage among catch crops as well as among years. The most appropriate was the cultivation of Phacelia tanacetifolia Bentham and Sinapis alba L., which regularly provided the highest yields and soil coverage. In some years, similar results were also achieved for Fagopyrum esculentum Moench and Carthamus tinctorius L. Less suitable catch crops are Secale cereale var. multicaule L., which ensured lower yield and good soil coverage, but reduced the yield of spring barley, and Panicum miliaceum L. Yield of spring barley was affected by year and species of catch crops. The lowest yield of barely was in the year with unfavourable rainfall. The yield decreased with increasing quantities of catch crop matter. In the case of favourable rainfall year, there was no risk of lower yield of spring barley after monitored catch crops in one of the driest and warmest places in the Czech Republic.O

Effect of Drought on the Development of Deschampsia caespitosa (L.) and Selected Soil Parameters during a Three-Year Lysimetric Experiment

This work presents results from a field experiment which was focused on the impact of the drought period on microbial activities in rhizosphere and non-rhizosphere soil. To demonstrate the effect of drought, the pot experiment lasted from 2012 to 2015. Fifteen lysimeters (plastic containers) were prepared in our area of interest. These lysimeters were filled with the subsoil and topsoil from this area and divided into two groups. The first group consisted of two variants: V1 (control) and V2 (84 kg N/ha), which were not stressed by drought. The second group consisted of three variants, V3 (control), V4 (84 kg N/ha), and V5 (84 kg N/ha + 1.25 L lignohumate/ha), which were stressed by drought every year of the experiment for 30 days. Changes in the soil moisture content caused by drought significantly affect the growth of Deschampsia caespitosa L., the microbial activity, and the soil's capacity to retain nutrients. The measured basal respiration and dehydrogenase activity values confirm the significant effect of drought on microbial activity. These values were demonstrably higher in the period before drought simulation by more than 60%. On the other hand, significant differences between microbial activities in the rhizosphere and non-rhizosphere soil were not found. We did not find a clear effect of drought on the formation of soil water repellency.O

Comparison of Proximal and Remote Sensing for the Diagnosis of Crop Status in Site-Specific Crop Management

The presented paper deals with the issue of selecting a suitable system for monitoring the winter wheat crop in order to determine its condition as a basis for variable applications of nitrogen fertilizers. In a four-year (2017-2020) field experiment, 1400 ha of winter wheat crop were monitored using the ISARIA on-the-go system and remote sensing using Sentinel-2 multispectral satellite images. The results of spectral measurements of ISARIA vegetation indices (IRMI, IBI) were statistically compared with the values of selected vegetation indices obtained from Sentinel-2 (EVI, GNDVI, NDMI, NDRE, NDVI and NRERI) in order to determine potential hips. Positive correlations were found between the vegetation indices determined by the ISARIA system and indices obtained by multispectral images from Sentinel-2 satellites. The correlations were medium to strong (r = 0.51-0.89). Therefore, it can be stated that both technologies were able to capture a similar trend in the development of vegetation. Furthermore, the influence of climatic conditions on the vegetation indices was analyzed in individual years of the experiment. The values of vegetation indices show significant differences between the individual years. The results of vegetation indices obtained by the analysis of spectral images from Sentinel-2 satellites varied the most. The values of winter wheat yield varied between the individual years. Yield was the highest in 2017 (7.83 t/ha), while the lowest was recorded in 2020 (6.96 t/ha). There was no statistically significant difference between 2018 (7.27 t/ha) and 2019 (7.44 t/ha).O

Estimation of Soil Properties Based on Soil Colour Index

Knowledge on soil properties is an important aspect in the implementation of precision agriculture. For this study was used an image taken by Sentinel 2 depicting fields of one farm with 8,261 ha in the South Moravian region of the Czech Republic. For the determination of soil properties, soil samples were taken at a density of 1 sample per 3 hectares and analyzed by Mehlich III methodology. The content of available nutrients phosphorus, potassium, magnesium and calcium have been determined together with soil pH, soil texture and sand. The specified sampling revealed high variability for phosphorus, potassium and calcium. Lower variability has been observed with magnesium and pH. An identification of bare soil area without vegetation cover was tested by different threshold values of Normalized vegetation difference index (NDVI) (0.15 – 0.3). The correlations between the multispectral bands and the soil properties were weak. In the analysis of soil samples was detected positive correlation (r = 0.505) between soil texture and Colour Index (CI). In area was found a negative correlation between CI and Ca (r = -0.618), then between CI and pH (r = -0.504). Weak correlation were found between CI, phosphorus and magnesium. At the level of lower NDVI values (0.16 - 0.15) we found correlation between CI and the sand content. The observed level of correlation found in the data of remote sensing can predict some soil properties in fields that have not been subjected to soil sampling and facilitate learning about soil properties for decisions in precision agriculture

Current Arable Farming Systems in the Czech Republic – Agronomic Measures Adapted to Soil Protection and Climate Change

The paper is focused on evaluation various soil tillage systems for maize in terms of productivity and reduction of soil erosion in the Czech Republic. The high slope of land, combined with expanding wide-row crops (when maize had the largest area) increase the risk of water erosion. Assessed yield data are from Southern Moravia in 2011-2016. Investigation of the effects of different soil tillage and silage maize stand establishment on soil and water runoff was carried out in the experimental station Lukavec near Pacov (Bohemian region). Average of six-years results showed that there are no any differences between conventional tillage (10.08 t ha-1) and minimum tillage (10.19 t ha-1), but year is significant. In trial, where different tillage systems were compared with/without phacelia as cover crop, according to three-year average, the highest grain yield was in chisel loosening (8.89 t ha-1) similar to ploughing (8.85 t ha-1). Lower yields were in no-tillage (8.61 t ha-1) and strip-tillage (8.55 t ha-1). Various conservation tillage systems have to be improved and modified for different soil and climate conditions. The benefit is in reduction of soil loss, which depends on crop residues coverage on soil surface. The soil sediment loss was the lowest in no-till variant (30 resp. 38 %) and less in minimum tillage (57 resp. 88 %) in comparison with ploughing (= 100 %). Decrease of soil sediment loss due to sown cover crops (Canary grass or rye) was almost less than 10 % in comparison with variant without cover crop. The results confirm the importance of soil conservation technologies (including strip-tillage) of soil tillage to reduce the risk of land degradation by water erosion

Using UAV to Identify the Optimal Vegetation Index for Yield Prediction of Oil Seed Rape (Brassica napus L.) at the Flowering Stage

Suitability of the vegetation indices of normalized difference vegetation index (NDVI), blue normalized difference vegetation index (BNDVI), and normalized difference yellowness index (NDYI) obtained by means of UAV at the flowering stage of oil seed rape for the prediction of seed yield and usability of these vegetation indices in the identification of anomalies in the condition of the flowering growth were verified based on the regression analysis. Correlation analysis was performed to find the degree of yield dependence on the values of NDVI, BNDVI, and NDYI indices, which revealed a strong, significant linear positive dependence of seed yield on BNDVI (R = 0.98) and NDYI (R = 0.95). The level of correlation between the NDVI index and the seed yield was weaker (R = 0.70) than the others. Regression analysis was performed for a closer determination of the functional dependence of NDVI, BNDVI, and NDYI indices and the yield of seeds. Coefficients of determination in the linear regression model of NDVI, BNDVI, and NDYI indices reached the following values: R2 = 0.48 (NDVI), R2 = 0.95 (BNDVI), and R2 = 0.90 (NDYI). Thus, it was shown that increased density of yellow flowers decreased the relationship between NDVI and crop yield. The NDVI index is not appropriate for assessing growth conditions and prediction of yields at the flowering stage of oil seed rape. High accuracy of yield prediction was achieved with the use of BNDVI and NDYI. The performed analysis of NDVI, BNDVI, and NDYI demonstrated that particularly the BNDVI and NDYI indices can be used to identify problems in the development of oil seed rape growth at the stage of flowering, for their precise localization, and hence to targeted and effective remedial measures in line with the principles of precision agriculture.O

Current Arable Farming Systems in the Czech Republic – Agronomic Measures Adapted to Soil Protection and Climate Change

The paper is focused on evaluation various soil tillage systems for maize in terms of productivity and reduction of soil erosion in the Czech Republic. The high slope of land, combined with expanding wide-row crops (when maize had the largest area) increase the risk of water erosion. Assessed yield data are from Southern Moravia in 2011-2016. Investigation of the effects of different soil tillage and silage maize stand establishment on soil and water runoff was carried out in the experimental station Lukavec near Pacov (Bohemian region). Average of six-years results showed that there are no any differences between conventional tillage (10.08 t ha-1) and minimum tillage (10.19 t ha-1), but year is significant. In trial, where different tillage systems were compared with/without phacelia as cover crop, according to three-year average, the highest grain yield was in chisel loosening (8.89 t ha-1) similar to ploughing (8.85 t ha-1). Lower yields were in no-tillage (8.61 t ha-1) and strip-tillage (8.55 t ha-1). Various conservation tillage systems have to be improved and modified for different soil and climate conditions. The benefit is in reduction of soil loss, which depends on crop residues coverage on soil surface. The soil sediment loss was the lowest in no-till variant (30 resp. 38 %) and less in minimum tillage (57 resp. 88 %) in comparison with ploughing (= 100 %). Decrease of soil sediment loss due to sown cover crops (Canary grass or rye) was almost less than 10 % in comparison with variant without cover crop. The results confirm the importance of soil conservation technologies (including strip-tillage) of soil tillage to reduce the risk of land degradation by water erosion

Towards the development and verification of a 3D-based advanced optimized farm machinery trajectory algorithm

Efforts related to minimizing the environmental burden caused by agricultural activities and increasing economic efficiency are key contemporary drivers in the precision agriculture domain. Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using the on-line optimization of trajectory planning for soil-sensitive field operations. The research presented in this paper aims at a proof-of-concept solution with respect to optimizing farm machinery trajectories in order to minimize the environmental burden and increase economic efficiency. As such, it further advances existing CTF solutions by including (1) efficient plot divisions in 3D, (2) the optimization of entry and exit points of both plot and plot segments, (3) the employment of more machines in parallel and (4) obstacles in a farm machinery trajectory. The developed algorithm is expressed in terms of unified modeling language (UML) activity diagrams as well as pseudo-code. Results were visualized in 2D and 3D to demonstrate terrain impact. Verifications were conducted at a fully operational commercial farm (Rostenice, the Czech Republic) against second-by-second sensor measurements of real farm machinery trajectories

1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.Comment: MaCVi 2023 was part of WACV 2023. This report (38 pages) discusses the competition as part of MaCV