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Anne-Katrin Mahlein

Anne-Katrin Mahlein
Institute of Sugar Beet Research (IfZ) at the University Göttingen

Prof. Dr.

About

139
Publications
95,559
Reads
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9,175
Citations
Additional affiliations
January 2011 - present
University of Bonn
Position
  • Junior research group leader

Publications

Publications (139)
Article
Full-text available
Molecular marker analysis allow for a rapid and advanced pre-selection and resistance screenings in plant breeding processes. During the phenotyping process, optical sensors have proved their potential to determine and assess the function of the genotype of the breeding material. Thereby, biomarkers for specific disease resistance traits provide va...
Article
Full-text available
The OPCW Member states cover 98% of the global population and landmass. Regrettably, unanticipated chemical warfare agent assaults are reported during the last decades. In addition to the frequent threat situation, the sampling of bio-medical samples from these areas is critical and mainly depends on investigation opportunities of victims. Non-cont...
Article
Full-text available
Early and accurate detection and diagnosis of plant diseases are key factors in plant production and the reduction of both qualitative and quantitative losses in crop yield. Optical techniques, such as RGB imaging, multi- and hyperspectral sensors, thermography, or chlorophyll fluorescence, have proven their potential in automated, objective and re...
Article
Full-text available
Differences in early plant-pathogen interactions are mainly characterized by using destructive methods. Optical sensors are advanced techniques for phenotyping host-pathogen interactions on different scales and for detecting subtle plant resistance responses against pathogens. A microscope with a hyperspectral camera was used to study interactions...
Article
Full-text available
Modern phenotyping and plant disease detection methods, based on optical sensors and information technology, provide promising approaches to plant research and precision farming. In particular, hyperspectral imaging have been found to reveal physiological and structural characteristics in plants and to allow for tracking physiological dynamics due...
Article
Full-text available
Background This research proposes an easy to apply quality assurance pipeline for hyperspectral imaging (HSI) systems used for plant phenotyping. Furthermore, a concept for the analysis of quality assured hyperspectral images to investigate plant disease progress is proposed. The quality assurance was applied to a handheld line scanning HSI-system...
Article
Full-text available
Background Root growth is most commonly determined with the destructive soil core method, which is very labor-intensive and destroys the plants at the sampling spots. The alternative minirhizotron technique allows for root growth observation throughout the growing season at the same spot but necessitates a high-throughput image analysis for being l...
Article
This study investigates the potential of high‐resolution (<0.5 cm/pixel) aerial imagery and convolutional neural networks (CNNs) for disease incidence scoring in sugar beet, focusing on two important aphid‐transmitted viruses, beet mild yellowing virus (BMYV) and beet chlorosis virus (BChV). The development of tolerant sugar beet cultivars is imper...
Preprint
Full-text available
Background This research proposes an easy to apply quality assurance pipeline for hyperspectral imaging (HSI) systems used for plant phenotyping. Furthermore, a concept for the analysis of quality assured hyperspectral images to investigate plant disease progress is proposed. The quality assurance was applied to a handheld line scanning HSI-system...
Article
Background This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing plant breeding and improving crop production. Traditionally, reference data in plant phenotyping rely on invasive methods. Recent advancements in 3D sensing technologies offer the possibility to collect param...
Article
Effectively feeding a burgeoning world population is one of the main goals of sustainable agricultural practices. Digital technology, such as edge artificial intelligence (AI), has the potential to introduce substantial benefits to agriculture by enhancing farming practices that can improve agricultural production efficiency, yield, quality and saf...
Article
In the past decade, there has been a recognized need for innovative methods to monitor and manage plant diseases aiming to meet the precision demands of modern agriculture. Over the last 15 years, significant advances in detection, monitoring, and management of plant diseases have been made, largely propelled by cutting-edge technologies. Recent ad...
Article
Agriculture faces several challenges including climate change and biodiversity loss while, at the same time, the demand for food, feed, biofuels, and fiber is increasing. Sustainable intensification aims to increase productivity and input-use efficiency while enhancing the resilience of agricultural systems to adverse environmental conditions throu...
Article
Full-text available
In crop protection, disease quantification parameters such as disease incidence (DI) and disease severity (DS) are the principal indicators for decision making, aimed at ensuring the safety and productivity of crop yield. The quantification is standardized with leaf organs, defined as individual scoring units. This study focuses on identifying and...
Preprint
Full-text available
Remote sensing and artificial intelligence are pivotal technologies of precision agriculture nowadays. The efficient retrieval of large-scale field imagery combined with machine learning techniques shows success in various tasks like phenotyping, weeding, cropping, and disease control. This work will introduce a machine learning framework for autom...
Conference Paper
Remote sensing technologies provide the potential to support the breeding process of crop cultivars. The presented work suggests a new phenotyping routine for sugar beet genotypes, resistant or tolerant to beet mosaic virus (BtMV). The use of non-invasive sensors could potentially eliminate the need for time-consuming and expensive laboratory analy...
Conference Paper
In the field of vegetation remote sensing, the concept and conversion across scales has been addressed—but not concluded—in recent years. A large array of different sensors is deployed using various platforms such as uncrewed aerial vehicles (UAVs) and satellites. In this context, while multiple concepts of scale exist, the influence of spatial sca...
Article
Rhizoctonia crown and root rot (RCRR), caused by Rhizoctonia solani, can cause severe yield and quality losses in sugar beet. The most common strategy to control the disease is the development of resistant varieties. In the breeding process, field experiments with artificial inoculation are carried out to evaluate the performance of genotypes and v...
Article
Plant-parasitic nematodes are one of the most insidious pests limiting agricultural production, parasitizing mostly belowground and occasionally aboveground plant parts. They are an important and underestimated component of the estimated 30% yield loss inflicted on crops globally by biotic constraints. Nematode damage is intensified by interactions...
Article
Full-text available
Background Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet (Beta vulgaris). Sugar beet storage roots a...
Article
Full-text available
Fusarium head blight (FHB) is a major threat for wheat production worldwide. Most reviews focus on Fusarium graminearum as a main causal agent of FHB. However, different Fusarium species are involved in this disease complex. These species differ in their geographic adaptation and mycotoxin profile. The incidence of FHB epidemics is highly correlate...
Conference Paper
This study shows how spectral sensing of plants extends technical challenges of spectral measuring. A greenhouse experiment shows that plant diseases can be recognized even before a human expert is able to detect visible symptoms.
Preprint
Full-text available
In crop production plant diseases cause significant yield losses. Therefore, the detection and scoring of disease occurrence is of high importance. The quantification of plant diseases requires the identification of leaves as individual scoring units. Diseased leaves are very dynamic and complex biological object which constantly change in form and...
Article
Turnip yellows virus (TuYV), belonging to the genus Polerovirus of the family Solemoviridae, is an aphid transmissible, pathogenic virus causing considerable yield losses in oilseed rape (Brassica napus subsp. napus) cultivation. Virus detection in infected plants is difficult due to the phloem limitation and the irregular distribution of the virio...
Preprint
Full-text available
Background Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet (Beta vulgaris). Sugar beet storage roots a...
Article
Fungal infections trigger defense or signaling responses in plants, leading to various changes in plant metabolites. The changes in metabolites, for example chlorophyll or flavonoids, have long been detectable using time-consuming destructive analytical methods including high-performance liquid chromatography or photometric determination. Recent pl...
Chapter
Plant diseases pose a significant threat to agriculture. Precise and appropriately timed detection and identification of plant diseases is crucial for disease management, and for the selection of resistant and tolerant varieties. The detection of plant diseases by the human eye is dependent on the experience of the expert and on external influences...
Article
Full-text available
Background Unmanned aerial vehicle (UAV)–based image retrieval in modern agriculture enables gathering large amounts of spatially referenced crop image data. In large-scale experiments, however, UAV images suffer from containing a multitudinous amount of crops in a complex canopy architecture. Especially for the observation of temporal effects, thi...
Article
Full-text available
Disease incidence (DI) and metrics of disease severity are relevant parameters for decision making in plant protection and plant breeding. To develop automated and sensor-based routines, a sugar beet variety trial was inoculated with Cercospora beticola and monitored with a multispectral camera system mounted to an unmanned aerial vehicle (UAV) ove...
Article
The most damaging foliar disease in sugar beet is Cercospora leaf spot (CLS), caused by Cercospora beticola Sacc. The pathogen is expanding its territory due to climate conditions, generating the need for early and accurate detection to avoid yield losses. In Germany, monitoring and control strategies are based on visual field assessments, with the...
Article
Previous studies investigating the performance of transmission and reflection datasets for disease detection showed inconsistent results. Within the studies, the performance of transmission imaging varied significantly for the detection of biotroph and necrotrophy plant pathogens, while reflection imaging showed excellent results in both studies. T...
Preprint
Full-text available
UAV-based image retrieval in modern agriculture enables gathering large amounts of spatially referenced crop image data. In large-scale experiments, however, UAV images suffer from containing a multitudinous amount of crops in a complex canopy architecture. Especially for the observation of temporal effects, this complicates the recognition of indi...
Chapter
This book outlines the economic importance of specific plant parasitic nematode problems on the major food and industrial crops and presents the state-of-the-art management strategies that have been developed to reduce specific nematode impacts and outlines their limitations. Case studies to illustrate nematode impact in the field are presented and...
Preprint
Full-text available
In this work we combine representation learning capabilities of neural network with agricultural knowledge from experts to model environmental heat and drought stresses. We first design deterministic expert models which serve as a benchmark and inform the design of flexible neural-network architectures. Finally, a sensitivity analysis of the latter...
Article
Counting crop seedlings is a time-demanding activity involved in diverse agricultural practices like plant cultivating, experimental trials, plant breeding procedures, and weed control. Unmanned Aerial Vehicles (UAVs) carrying RGB cameras are novel tools for automatic field mapping, and the analysis of UAV images by deep learning methods can provid...
Article
Full-text available
Phytopathometry can be defined as the branch of plant pathology (phytopathology) that is concerned with estimation or measurement of the amount of plant disease expressed by symptoms of disease or signs of a pathogen on a single or group of specimens. Phytopathometry is critical for many reasons, including analyzing yield loss due to disease, breed...
Article
Full-text available
The ban imposed by the European Union on the use of neonicotinoids as sugar beet seed treatments was based on the exposure of bees to residues of neonicotinoids in pollen and nectar of succeeding crops. To address this concern, residues of thiamethoxam (TMX) and clothianidin (CTD) were analyzed in soil collected from fields planted in at least the...
Article
Full-text available
BACKGROUND The assessment of the environmental risks for pesticides is a current topic of the European Union (EU) strategy ‘Farm to Fork’. Therefore, an analysis of the status quo of pesticide use from 2010 to 2015 and the associated environmental risks was performed for sugar beet cultivation in Germany. Based on this assessment, crop protection s...
Article
Full-text available
Ditylenchus dipsaci is an economically important plant-parasitic nematode affecting European sugar beets. To date, no sugar beet cultivars carrying resistance against D. dipsaci are available to farmers. To find potentially resistant sugar beet lines restricting reproduction and penetration of D. dipsaci , three consecutive in vivo bioassays were c...
Article
In recent studies, the potential of hyperspectral sensors for the analysis of plant‐pathogen interactions was expanded to the ultraviolet range (UV; 200‐380 nm) to monitor stress processes in plants. A hyperspectral imaging set‐up was established to highlight the influence of early plant‐pathogen interactions on secondary plant metabolites. In this...
Article
Full-text available
Plant diseases can impact crop yield. Thus, the detection of plant diseases using sensors that can be mounted on aerial vehicles is in the interest of farmers to support decision-making in integrated pest management and to breeders for selecting tolerant or resistant genotypes. This paper investigated the detection of Cercospora leaf spot (CLS), ca...
Article
Full-text available
The stem nematode, Ditylenchus dipsaci, is a severe pest in European sugar beet production. In France, Germany, and Switzerland, D. dipsaci damage in sugar beet varies among specific geographic areas. In this study, the reproduction potential of four geographically distinct D. dipsaci populations was determined using sterile carrot disc cultures. I...
Article
This work established a hyperspectral library of important foliar diseases of wheat in time series to detect spectral changes from infection to symptom appearance induced by different pathogens. The data was generated under controlled conditions at the leaf-scale. The transition from healthy to diseased leaf tissue was assessed, spectral shifts wer...
Article
The stem nematode, Ditylenchus dipsaci , causes severe damage in sugar beet. To date, nematode inoculation through the leaf axil has been used as the standard method to investigate D. dipsaci interaction with sugar beet under in vivo conditions. To get as close as possible to field conditions, we established a new screening mechanism to perform soi...
Conference Paper
Hyperspectral sensors offer the potential to monitor plants non-invasively. Analysis of spectral signatures enable the detection of specific plant stress. This is a prerequisite for site- specific management strategies and may reduce the input of agrochemicals.
Article
Full-text available
Most studies of Fusarium head blight (FHB) focused on wheat infection at anthesis. Less is known about infections at later stages. In this study, the effect of infection timing on the development of FHB and the distribution of fungal biomass and deoxynivalenol (DON) along wheat spikes was investigated. Under greenhouse conditions, two wheat varieti...
Article
Full-text available
BACKGROUND Cercospora leaf spot caused by Cercospora beticola is the most relevant foliar disease in sugar beet cultivation. In the last decade a decreasing sensitivity of C. beticola towards demethylation inhibitors (DMIs) occurred. Different mechanisms mediating a reduced sensitivity towards DMIs have been identified in different plant pathogens...
Article
Full-text available
The severity of plant diseases, traditionally the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases and is prone to error. Good quality disease severity data should be accurate (close to the true value). Earliest quantification of disease severity was by visual estimates. Sensor-based image...
Article
Full-text available
Plants produce sugar and oxygen in a process called photosynthesis, by using sunlight, water, and carbon dioxide. This is an important process on Earth, since it removes carbon dioxide from the air and provides food for us. Photosynthesis happens in small compartments within the plant cells, called chloroplasts. In a two-step process, plants obtain...
Article
Full-text available
Deep neural networks have demonstrated excellent performances in many real-world applications. Unfortunately, they may show Clever Hans-like behaviour (making use of confounding factors within datasets) to achieve high performance. In this work we introduce the novel learning setting of explanatory interactive learning and illustrate its benefits o...
Article
Full-text available
Background The use of hyperspectral cameras is well established in the field of plant phenotyping, especially as a part of high-throughput routines in greenhouses. Nevertheless, the workflows used differ depending on the applied camera, the plants being imaged, the experience of the users, and the measurement set-up. Results This review describes...
Article
Full-text available
Background: The efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress. Laserscanning is a highly accurate and high resolution technique to acquire the 3D shape of plant surfaces. The c...
Article
Full-text available
Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing root rot, has already affected more than 25% of the area under kiwifruit cultivation in Italy. Diseased plants are characterised by severe decay of the fine roots and sudden wilting of the canopy, which is only visible after the season’s first period...
Article
The fungal pathogen Rhizoctonia solani is one of the most important soil-borne diseases in sugar beet production worldwide. Root and crown rot caused by this fungus are traditionally recognized later in the cropping season by rating the above-ground symptoms like wilting and chlorosis on foliage, and dark brown lesions at the base of petioles. The...
Preprint
Full-text available
Deep neural networks have shown excellent performances in many real-world applications such as plant phenotyping. Unfortunately, they may show "Clever Hans"-like behaviour--- making use of confounding factors within datasets---to achieve high prediction rates. Rather than discarding the trained models or the dataset, we show that interactions betwe...
Preprint
Full-text available
Background: The efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress. Laser scanning is a highly accurate and high resolution technique to acquire the 3D shape of plant surfaces. The c...
Article
Monitoring von Pflanzen mit nicht-destruktiver Sensorik ist ein etabliertes Werkzeug bei der Begutachtung und Beschreibung pflanzlicher Entwicklung und Leistungsfähigkeit. Diese Methoden werden im Labor- und Gewächshaus auf Organ-, Pflanzen-, und Kleinbestandebene eingesetzt. Hochdurchsatzverfahren sind ebenfalls etabliert. Die Übertragung dieser T...
Article
Full-text available
The application of hyperspectral imaging technology for plant disease detection in the field is still challenging. Existing equipment and analysis algorithms are adapted to highly controlled environmental conditions in the laboratory. However, only real time information from the field scale is able to guide plant protection measures and to optimize...
Article
Full-text available
Fusarium head blight (FHB) epidemics in wheat and contamination with Fusarium mycotoxins has become an increasing problem over the last decades. This prompted the need for non-invasive and non-destructive techniques to screen cereal grains for Fusarium infection, which is usually accompanied by mycotoxin contamination. This study tested the potenti...
Article
Background Variations in the temperature of body and skin are symptoms of many pathological changes. Although joint replacement surgery of hip and knee has been very successful in recent decades, periprosthetic infection is a growing problem and the number one reason for revision. While many studies have investigated changes in blood levels, invest...
Article
Regelmäßig wird an das Institut für Zuckerrübenforschung (IfZ) herangetragen, Daten aus der Betriebsbefragung zur Produktionstechnik im Zuckerrübenanbau zur Kommunikation in verschiedene Zielgruppen zur Verfügung zu stellen. Dabei begeben sich WissenschaftlerInnen auf eine Gratwanderung zwischen zielgruppengerechter Darstellung von Ergebnissen bei...
Article
Determination and characterization of resistance reactions of crops against fungal pathogens are essential to select resistant genotypes. In plant breeding, phenotyping of genotypes is realized by time consuming and expensive visual plant ratings. During resistance reactions and during pathogenesis plants initiate different structural and biochemic...