Yara (Germany)

Coffee production around the world is under threat due to climate variability and change, and drought stress will increase in many coffee regions; nutrient management practices can enhance the adaptation capacity of coffee production. Considering that coffee is a crop sensitive to boron (B) deficiency, this research investigated how B nutrition improves resistance to drought stress in coffee under controlled conditions as well as how the interaction with calcium (Ca2+) influences productivity, seed composition, and soil fertility during a production cycle of 5 years. Under controlled conditions for seven months, coffee plants were submitted to water stress with and without B nutrition. In the field, the coffee plantation was exposed to two B rates (0.6 and 1.1 kg.ha−1-year−1) with a fixed calcium (Ca2+) rate and a control without Ca2+ and B. After 9 months of growth and seven months of water deficit, under controlled conditions, the application of B significantly (p < 0.05) reduced the negative effect of water stress on coffee growth. Under field conditions, after a production cycle of 5 years, the application of 0.6 kg B and 77 kg CaO. ha−1.year−1 yielded 14% more than the control without B and Ca2+. An increase in the B rate to 1.1 kg.ha−1.year−1 with the same Ca2+ rate increased the productivity significantly (p < 0.05) by 37% compared to the control. The B application also improved significantly (p < 0.05) the B content in the soil at 0–30 cm. The B treatments influenced the biochemical composition of the green coffee beans, with a significant (p < 0.05) inverse correlation between the B content of the green coffee beans and caffeine and unsaturated fatty acids (UFAs), mainly, oleic, linoleic, and linolenic acids, which are considered negative descriptors of the coffee quality.

Boron (B) is readily leached from the soil, depending on the soil texture, soil organic matter (OM) content, and the fertilizer source used. This can restrict B uptake by plants. Therefore, we investigated the most adequate B source for soybeans grown in soils with contrasting textures and OM contents. The plants were cultivated for 55 days in columns filled with clayey or sandy Oxisols with low or high OM contents. The clay contents (%) in the soils were as follows: clayey soil with low OM = 64; clayey soil with high OM = 67; sandy soil with low OM = 4; and sandy soil with high OM = 15. The B sources tested comprised the control (no B supply), ulexite, zinc borate, boric acid, and B-monoethanolamine (B-MEA), with the equivalent of 6 kg B ha–1 applied. Boron leaching from ulexite was lower than other B fertilizers in the sandy soil with high OM content. Boron leaching was higher in sandy than in clayey soils. Boron accumulation in shoots was lower when boric acid was applied to the sandy soil with low OM content than the other B fertilizers. In this same soil, the agronomic efficiency and recovery of B applied by plants supplied with ulexite and zinc borate were higher compared to boric acid and B-MEA. In conclusion, the use of ulexite and zinc borate is more appropriate for soybean fertilization in sandy soils with low OM content, while B-MEA is more suitable for sandy soils with high OM content.

Die Geschichte der Behandlung ventrikulärer Tachykardien durch chirurgische Verfahren ist kurz; sie dauerte nicht länger als 15 Jahre von etwa 1978 bis 1993. Grundsätzlich sind zwei chirurgische Verfahren zu unterscheiden. Die indirekten Verfahren mit Resektion einer Infarktnarbe ohne elektrophysiologische Untersuchung und die direkten Verfahren mit gezielter Endokardinzision („encircling endocardial ventriculotomy“). In Deutschland haben Ostermeyer, Breithardt und Seipel (Düsseldorf) 1979 erstmals über intraoperatives, elektrophysiologisches Mapping bei ventrikulären Tachykardien (VT) berichtet; 1981 hat dann die Gruppe in Hannover (Frank, Klein) über erste Ergebnisse bei der chirurgischen Therapie von Kammertachykardien berichtet. 1984 konnten Ostermeyer, Breithardt und Borggrefe zeigen, dass eine nur partielle Endokardinzision deutlich günstiger und weniger Ventrikel schädigend (8 % vs. 46 %) ist als eine komplette zirkuläre Inzision. 1987 berichtete die Düsseldorfer Gruppe über Behandlungsergebnisse von 93 Patienten. Nach 5 Jahren waren 77 % der Patienten ohne VT-Rezidiv, die Gesamtmortalität nach einem Jahr war 11 %, nach 5 Jahren 30 %. Die Hannover Gruppe berichtete 1992 über 147 Patienten, die mit endokardialem Resektionsverfahren behandelt wurden; die Gesamtmortalität nach 3 Jahren war 27 %, VT-Rezidive traten bei 18 % der Überlebenden auf.Die Geschichte der chirurgischen Verfahren bei supraventrikulären Tachykardien (SVT), insbesondere dem Wolff-Parkinson-White(WPW)-Syndrom ist noch kürzer als die der Chirurgie für VT. Bereits 1969 berichteten Sealy, Gallagher und Cox über die ersten Fälle einer chirurgischen Intervention beim WPW-Syndrom über einen endokardialen Zugang bei kardioplegischem Herzstillstand. 1984 berichteten Guiraudon und Klein über ein neues Verfahren mit epikardialem Zugang zum akzessorischen Bündel ohne Kardioplegie bei lateral lokalisierten Leitungsbahnen. Auch in Deutschland führten seit 1980 die Gruppen in Düsseldorf (Ostermeyer, Seipel, Breithardt, Borggrefe) und seit 1981 die Hannover Gruppe (Frank, Klein und Kallfelz) operative Verfahren bei WPW-Syndrom durch. Borggrefe berichtete 1987 über 18 operierte Patienten mit WPW-Syndrom und Vorhofflimmern. Nach 2 Jahren blieben 14 von 18 Patienten ohne Tachykardie Rezidive; 1989 berichteten Frank, Klein und Kallfelz (Hannover) über 10 operierte Kinder (2−14 Jahre) unter Anwendung der Kryoablationstechnik. Zwischen 1984 und 1992 wurden in Hannover insgesamt 120 Patienten mit SVT, meist WPW-Syndrom, operiert; nach 42 Monaten hatten 12 Patienten ein SVT-Rezidiv. Bei der Reoperation verstarben 2 Patienten.

This article presents the data obtained from a field experiment in which grass–clover leys were fertilized with increasing N rates applied in either mineral N fertilizer and/or cattle slurry forms. The leys were composed of a 2–species mixture of white clover (Trifolium repens L.) and ryegrass (Lolium perenne L.) and a 4–species mixture of white clover, red clover (Trifolium pratense L.), festulolium (Festulolium braunii) and ryegrass. In total, eighty fields were established at two farm sites in the western part of Denmark on sandy soils and monitored for two herbage seasons (2018–2019). Dry matter yield, botanical composition, N concentration and the proportion of N derived from the atmosphere using the 15 N dilution method were recorded in the harvestable biomass after each cut. Furthermore, the specific growth, N uptake and quantitative biological N fixation of the species were determined.The dataset can be used to establish the N balance, to calculate the optimal economic fertilization rate based on grass-clover composition and to predict N leaching and residual effect.The data presented were thoroughly used and discussed in the research article “Contrasting effects of slurry and mineral fertilizer on N2 fixation in grass-clover mixtures”.

Remote sensing systems based on unmanned aerial vehicles (UAVs) are well suited for airborne monitoring of small to medium-sized farmland in agricultural applications. An imaging system is often used in the form of a multispectral multi-camera system to derive well-established vegetation indices (VIs) efficiently. This study investigates the potential of such a multi-camera system with a novel approach to extend spectral sensitivity from visible-to-near-infrared (VNIR) to short-wave infrared (SWIR) (400–1700 nm) for estimating forage mass from an aerial carrier platform. The system test was performed in a grassland fertilizer trial in Germany near Cologne in late July 2019. Within 37 min, a spectral response in four different wavelength bands in the NIR and SWIR range was acquired during two consecutive flights. Spectral image data were calibrated to reflectance using two different methods. The resulting reflectance data sets were processed to orthomosaics for each wavelength band. From these orthomosaics for both calibration methods, the four-band NIR/SWIR GnyLi VI and the two-band NIR/SWIR Normalized Ratio Index (NRI), were calculated. During both UAV flights, spectral ground truth data were recorded with a spectroradiometer on 12 plots in total for validation of camera-based spectral data. The camera and spectroradiometer data sets were directly compared in resulting reflectance and further analyzed with simple linear regression (SLR) models to predict dry matter (DM) yield. In the camera-based SLRs, the NRI performed best with R^2 of 0.73 and 0.75 (RMSE: 0.18 and 0.17) before the GnyLi with R^{2} of 0.71 and 0.73 (RMSE: 0.19 and 0.18). These results clearly indicate the potential of the camera system for applications in forage mass monitoring.

Monitoring grassland biomass throughout the growing season is of key importance in sustainable, site-specific management decisions. Precision agriculture applications can support these decisions. However, precision agriculture relies on timely and accurate information on plant parameters with a high spatial and temporal resolution. The use of structural and spectral features derived from unmanned aerial vehicle (UAV)-based image data from low-cost sensors is a promising nondestructive approach to assess plant traits such as above-ground biomass or plant height. Therefore, the main objectives were (1) to evaluate the potential of low-cost UAV-based canopy surface models to monitor sward height as an indicator of grassland biomass, (2) to evaluate the potential of vegetation indices from low-cost UAV-based red-green-blue (RGB) digital image data, and (3) to compare the mentioned methods with established methods for biomass monitoring such as rising plate meters and spectroradiometer-based narrowband vegetation indices over the growing season in 2017, including three cuts. We compared the accuracy of each single UAV-based height feature and vegetation index using a combined multivariate approach to estimate fresh and dry biomass. The heterogeneous sward structure with high spatiotemporal variability led to varying performance in biomass estimation depending on the growths (time between two cuts) and choice of predictor variable. The results showed that biomass prediction by height features provided moderate-to-good results (cross-validation R 2 = 0.57 to 0.73 for dry biomass and 0.43 to 0.79 for fresh biomass), but reference measurements based on rising plate meters were more robust when estimating biomass. The spectral features (RGB-based vegetation indices and spectroradiometer-based vegetation indices) yielded varying accuracy and suitability for biomass prediction. Despite the variability, our findings indicate a promising approach for grassland biomass monitoring.

Abstract. Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Abstract The search for agricultural practices that mitigate N2O emissions, and the validation and development of models, would benefit if the uncertainty of emission estimates would be reduced relative to current levels. This uncertainty has different sources, such as the error of the flux measurements, the error caused by spatially scaling up measurements to the field or regional level, and the error caused by estimating emissions for the time intervals between measurements by interpolation. This paper focuses on the uncertainty of flux measurements and on flux spatial variability, which is a major cause of error when measured fluxes are scaled up spatially. The analysis focuses on 2415 flux measurements made with the closed chamber method over a monitoring campaign of approximately 3 years.Statistically significant nonlinearities in the changes of N2O concentrations during chamber closure were infrequent (8.3%). Further analysis of significant non‐linear concentration changes indicates that, for positive fluxes, nonlinearity might not always be an artifact caused by chamber placement, but that it can reflect natural temporal variability of the flux during chamber placement in a significant number of cases. The analysis of the coefficients of determination (R2) and of the normalized root mean squared errors (NRMSE) of the linear regressions shows that, below emission rates of 5 g N2O‐N ha−1 d−1, the uncertainty of flux estimates strongly increases. The flux detection limit was 3.5 g N2O‐N ha−1 d−1, which is consistent with the outcome of the analysis of the R2s and NRMSEs. Flux measurements based on less than five N2O concentrations per flux led to estimates with considerably larger confidence intervals. When the number of N2O concentrations per flux was reduced from five to four, the detection limit increased to 7.5 g N2O‐N ha−1 d−1. The individual fluxes of spatially replicated plots show strong dispersion around the mean: the average coefficient of variation for fluxes above 5 g N2O‐N ha−1 d−1 was 54.3% and the data suggest that the spatial variability of fluxes correlates positively with flux magnitude.Our results suggest that, for measurements performed with the closed static chamber method, (1) linear regression might generally lead to the best estimates of the average fluxes during closure time, and that the chamber sampling strategy might be designed accordingly, (2) there is considerable potential to reduce the uncertainty for fluxes lower than 5 g N2O‐N ha−1 d−1 by employing analytical instrumentation with higher precision, (3) flux uncertainty and detection limit are strongly affected by the number of concentrations measured for each flux, and (4) large numbers of replicated chambers could be particularly beneficial if high fluxes are expected.

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O.