Model-based scenario analysis for effective site-specific weed control on grassland sites

The site-specific management of weeds in grassland is often challenging because different weed control strategies have different trade-offs regarding the required resources and treatment efficiency. So, the question arises whether a wide tractor-based system with section control or a small agricultural robot has a higher weed control performance for a given infestation scenario. For example, a small autonomous robot moving from one weed to the next might have much shorter travel distances (and thus lower energy and time costs) than a tractor-mounted system if the locations of the weeds are relatively isolated across the field. However, if the plants are highly concentrated in small areas so-called clusters, the increased width of the tractor-mounted implement could be beneficial because of shorter travel distances and greater working width. An additional challenge is the fact that there is no complete knowledge of the weed locations. Weeds may not have been detected, for example, due to their growth stage, occlusion by other objects, or misclassification. Weed control strategies must therefore also be evaluated with regard to this issue. Thus, in addition to the driving distance, other metrics are also of interest, such as the number of plants that were actually controlled or the size of the total treatment area. We performed this investigation for the treatment of the toxic Colchicum autumnale, which had been detected in drone images of extensive grassland sites. In addition to real data, we generated and analyzed simulated weed locations using mathematical models of stochastic geometry. These offer the possibility to simulate very different spatial distributions of toxic plant locations. Different treatment strategies were then virtually tested on this data using Monte Carlo simulations and their performance was statistically evaluated.Comment: 20 pages, 9 figure

Detection of Colchicum autumnale in drone images, using a machine-learning approach

Colchicum autumnale are toxic autumn-blooming flowering plants, which often grow on extensive meadows and pastures. Thus, they pose a threat to farm animals especially in hay and silage. Intensive grassland management or the use of herbicides could reduce these weeds but environment protection requirements often prohibit these measures. For this reason, a non-chemical site- or plant-specific weed control is sought, which aims only at a small area around the C. autumnale and with low impact on the surrounding flora and fauna. For this purpose, however, the exact locations of the plants must be known. In the present paper, a procedure to locate blooming C. autumnale in high-resolution drone images in the visible light range is presented. This approach relies on convolutional neural networks to detect the flower positions. The training data, which is based on hand-labeled images, is further enhanced through image augmentation. The quality of the detection was evaluated in particular for grassland sites which were not included in the training to get an estimate for how well the detector works on previously unseen sites. In this case, 88.6% of the flowers in the test dataset were detected, which makes it suitable, e.g., for applications where the training is performed by the manufacturer of an automatic treatment tool and where the practitioners apply it to their previously unseen grassland sites

Benchmarking models of root architecture and function

3D models of root growth, architecture and function are evolving as they become important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common for water and solute transport models in soil, 3D root-soil interaction models have never been systematically analysed. Several interacting processes might induce disagreement between models: root growth, sink term definitions of root water and solute uptake and representation of the rhizosphere. The extent of discrepancies is currently unknown. Thus, a framework for quantitatively comparing such models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of the complex models: root architecture, water flow in soil and roots, solute transport in soil and roots. While the latter will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore defining common inputs that recreate reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled root-rhizosphere-soil models can be defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. We expect that this benchmarking will result in improved models, with which we can simulate various scenarios with greater confidence, avoiding that future work is based on accidental results caused by bugs, numerical errors or conceptual misunderstandings and will set a standard for future model development

Call for participation: Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute towards improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development

Call for participation: Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute towards improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development

RSD1019 suppresses ischaemia-induced monophasic action potential shortening and arrhythmias in anaesthetized rabbits

1. The electrophysiological actions of lidocaine, tedisamil and RSD1019 were assessed on normal and ischaemic cardiac tissue using monophasic action potentials (MAPs) recorded from the epicardium of anaesthetized rabbits. Drug effects on ischaemia-induced arrhythmias were assessed simultaneously in the same rabbits. 2. Lidocaine, infused at 2.5, 5 and 10 μmol kg(−1) min(−1) i.v., accelerated and worsened the electrophysiological derangement caused by ischaemia, had profibrillatory actions and reduced the time to the occurrence of ventricular fibrillation (VF) relative to controls. 3. Tedisamil, infused at 0.063, 0.125 and 0.25 μmol kg(−1) min(−1) i.v., prolonged MAP duration at 90% repolarization (MAPD(90%)) before induction of ischaemia in a dose-related manner; however, this effect was not maintained 5 min after induction of ischaemia. Tedisamil had no significant antiarrhythmic actions over the dose-range tested. 4. RSD1019, infused at 2, 4 and 8 μmol kg(−1) min(−1) i.v., produced a small increase in MAPD(90%) before induction of ischaemia and only at the highest dose tested. In contrast to tedisamil, RSD1019 suppressed ischaemia-induced MAP shortening assessed 5 min after induction of ischaemia. This effect was dose-related. RSD1019 completely prevented ischaemia-induced tachyarrhythmias at the mid and highest infusion levels tested. 5. The results of this study illustrate a pathologically targeted approach for preventing ischaemia-induced arrhythmias. Suppression of ischaemia-induced MAP shortening, demonstrated herein for RSD1019, represents a novel antifibrillatory approach

Impact of the coronavirus disease 2019 (COVID-19) pandemic on the care of patients with acute and chronic aortic conditions

OBJECTIVES To evaluate the impact of the coronavirus disease 2019 (COVID-19) pandemic on acute and elective thoracic and abdominal aortic procedures. METHODS Forty departments shared their data on acute and elective thoracic and abdominal aortic procedures between January and May 2020 and January and May 2019 in Europe, Asia and the USA. Admission rates as well as delay from onset of symptoms to referral were compared. RESULTS No differences in the number of acute thoracic and abdominal aortic procedures were observed between 2020 and the reference period in 2019 [incidence rates ratio (IRR): 0.96, confidence interval (CI) 0.89-1.04; P = 0.39]. Also, no difference in the time interval from acute onset of symptoms to referral was recorded ( 12 h 68% in 2020, 12 h 66% in 2019 P = 0.29). Conversely, a decline of 35% in elective procedures was seen (IRR: 0.81, CI 0.76-0.87; P < 0.001) with substantial differences between countries and the most pronounced decline in Italy (-40%, P < 0.001). Interestingly, in Switzerland, an increase in the number of elective cases was observed (+35%, P = 0.02). CONCLUSIONS There was no change in the number of acute thoracic and abdominal aortic cases and procedures during the initial wave of the COVID-19 pandemic, whereas the case load of elective operations and procedures decreased significantly. Patients with acute aortic syndromes presented despite COVID-19 and were managed according to current guidelines. Further analysis is required to prove that deferral of elective cases had no impact on premature mortality