Plant Disease Detection by Imaging Sensors - Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping.

By Anne-Katrin Mahlein. Plant Disease, 2016

1,011 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/551fefb7f2ebc6836cd2d5797704bbc6c422069e

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In Analytical Chemistry

In Ecology

In Plant Science

Citations in the corpus

Discrimination between abiotic and biotic drought stress in tomatoes using hyperspectral imaging (2018, result): “The latter is in accordance with conclusion of Mahlein [52], who noted that chlorophyll fluorescence is sensitive to early stress reaction of a plant, but lacks the potential to identify a specific disease.”
Forestry applications of UAVs in Europe: a review (2017, methodology): “Hyperspectral imaging offers high potential as a noninvasive diagnostic tool for disease detection (Mahlein 2016).”
Control of crop diseases through Integrated Crop Management to deliver climate-smart farming systems for low- and high-input crop production (2021, background): “…types of non- invasive sensors can be used to detect a change in crop health, identify the disease, and quantify the severity of the symptoms (phytopathometry) to inform the farmer where it is necessary to apply a treatment within a crop (Mahlein, 2016; Oerke, 2020; West et al., 2003; Yang, 2020).”
Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress (2017, background): “One conclusion is that RGB and hyperspectral imaging are preferable for identifying specific diseases [7].”
Quantitative and qualitative phenotyping of disease resistance of crops by hyperspectral sensors: seamless interlocking of phytopathology, sensors, and machine learning is needed! (2019, background): “During the last decade, several non-invasive sensors were established to enable a deeper view into the interaction types [18,19 ].”
Spatio-Temporal Data Mining (2017, background): “One of the purposes of collecting and studying this data is to detect plant diseases [Mahlein 2016] and understand the impact of several factors such as misapplication of fertilizer, compaction during planting and weeds on crop yield, as well as their inter-relationships.”
Precision Agriculture Techniques and Practices: From Considerations to Applications (2019, background): “Much research has been done in the agriculture sector for early disease detection and pest control systems using more advanced and sophisticated technologies [48,49].”
High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture (2019, background): “Plant phenotyping is still the bottleneck as the development of techniques for the precise and accurate recording of important agronomical traits and crop monitoring are lagging behind [13,14].”
Applications of Remote Sensing in Precision Agriculture: A Review (2020, methodology): “Multiple techniques using RGB, multi-spectral, hyperspectral, thermal, and fluorescence imaging have been used to identify diseases in a variety of crops [178].”