Sensor-based weed mapping in arable fields is a key element for site-specific herbicide management strategies. In this study, we investigated the generation of application maps based on Unmanned Aerial Vehicle imagery and present a site-specific herbicide application using those maps. Field trials for site-specific herbicide applications and multi-temporal image flights were carried out in maize (Zea mays L.) and sugar beet (Beta vulgaris L.) in southern Germany. Real-time kinematic Global Positioning System precision planting information provided the input for determining plant rows in the geocoded aerial images. Vegetation indices combined with generated plant height data were used to detect the patches containing creeping thistle (Cirsium arvense (L.) Scop.) and curled dock (Rumex crispus L.). The computed weed maps showed the presence or absence of the aforementioned weeds on the fields, clustered to 9 m × 9 m grid cells. The precision of the correct classification varied from 96% in maize to 80% in the last sugar beet treatment. The computational underestimation of manual mapped C. arvense and R. cripus patches varied from 1% to 10% respectively. Overall, the developed algorithm performed well, identifying tall perennial weeds for the computation of large-scale herbicide application maps.

BACKGROUND Some maize post‐emergence herbicides obtain their crop/weed selectivity only through the use of chemical crop safeners. Safeners improve the tolerance of maize to herbicidal active ingredients. In order to investigate the crop response to safener (cyprosulfamide) spray application and seed treatment, greenhouse and field trials were conducted on three maize development stages (2‐, 4‐, and 6‐leaf stage). Visual estimations on crop vitality were compared to ground‐based and airborne hyperspectral and multispectral sensors. RESULTS The reduction of cyprosulfamide by 88% when applied as seed treatment did not significantly reduce maize biomass yields at the field. The crop deterioration in both trials was stronger in the cyprosulfamide seed treatments compared to the spray applications but was found to be transient in the field trial. The hyperspectral sensor and multispectral camera data correlated with R2 = 0.84 (CropSpec Vegetation Index) and R2 = 0.64 (Green Normalized Difference Vegetation Index). CONCLUSION The sensor‐based collection of crop responses to treatments enables early, quantifiable and auditor‐independent assessments. In particular, the airborne multispectral imagery assessment of field experiments provides more detailed and comprehensive information than visually collected data. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

SummaryReliable in‐season and in‐field tools for rapidly quantifying herbicide efficacy in dicotyledonous weeds are missing. In this study, the maximum quantum efficiency of photosystem II (Fv/Fm) of susceptible and resistant Papaver rhoeas and Stellaria media populations in response to treatments with acetolactate synthase (ALS) inhibitors were examined. Seedlings (4–6 leafs) were transplanted into the field immediately after the application of the ALS inhibitors florasulam, metsulfuron‐methyl and tribenuron‐methyl. The Fv/Fm values were assessed 1–7, 9 and 14 days after treatment (DAT). Based on the Fv/Fm values of all fluorescing pixels in the images of herbicide‐treated plants, discriminant maximum‐likelihood classifiers were created. Based on this classifier, an independent set of images were classified into ‘susceptible’ or ‘resistant’ plants. The classifiers’ accuracy, false‐positive rate and false‐negative rate were calculated. The Fv/Fm values of sensitive P. rhoeas and S. media plants decreased within 3 DAT by 28–43%. The Fv/Fm values of the resistant plants of both species were 20% higher than those of the sensitive plants in all herbicide treatments. The classifier separated sensitive and resistant plants 3 DAT with accuracies of 62–100%. False‐positive and false‐negative classifications decreased with increasing DAT. We conclude that by the assessment of the Fv/Fm value in combination with the classification sensitive and resistant P. rhoeas and S. media populations could be separated 3 DAT. This technique can help to select effective control methods and speed up the monitoring process of susceptible and resistant weeds.

Throughout all kingdoms of life, highly conserved transport proteins mediate the passage of ammonium across membranes. These transporters share a high homology and a common pore structure. Whether NH3, NH4+ or NH3 + H+ is the molecularly transported substrate, still remains unclear for distinct proteins. High-resolution protein structures of several ammonium transporters suggested two conserved pore domains, an external NH4+ recruitment site and a pore-occluding twin phenylalanine gate, to take over a crucial role in substrate determination and selectivity. Here, we show that while the external recruitment site seems essential for AtAMT1;2 function, single mutants of the double phenylalanine gate were not reduced in their ammonium transport capacity. Despite an unchanged ammonium transport rate, a single mutant of the inner phenylalanine showed reduced N-isotope selection that was proposed to be associated with ammonium deprotonation during transport. Even though ammonium might pass the mutant AMT pore in the ionic form, the transporter still excluded potassium ions from being transported. Our results, highlight the importance of the twin phenylalanine gate in blocking uncontrolled ammonium ion flux.

Aim of study: An approach to integrate knowledge into the IT-infrastructure of precision agriculture (PA) is presented. The creation of operation relevant information is analyzed and explored to be processed by standardized web services and thereby to integrate external knowledge into PA. The target is to make knowledge integrable into any software solution. Area of study: The data sampling took place at the Heidfeld Hof Research Station in Stuttgart, Germany. Material and methods: This study follows the information science’s idea to separate the process from data sampling into the final actuation through four steps: data, information, knowledge, and wisdom. The process from the data acquisition, over a professional data treatment to the actual application is analyzed by methods modelled in the Unified Modelling Language (UML) for two use-cases. It was further applied for a low altitude sensor in a PA operation; a data sampling by UAV represents the starting point. Main results: For the implemented solution, the Web Processing Service (WPS) of the Open Geospatial Consortium (OGC) is proposed. This approach reflects the idea of a function as a service (FaaS), in order to develop a demand-driven and extensible solution for irregularly used functionalities. PA benefits, as on-farm processes are season oriented and a FaaS reflects the farm’s variable demands over time by origin and extends the concept to offer external know-how for the integration into specific processes. Research highlights: The standardized implementation of knowledge into PA software products helps to generate additional benefits for PA.