a,b,c Spectral differences of healthy and inoculated with B. graminis f.sp. hordei (Bgh), susceptible WT, resistant mlo3 and Mla1, 0.5, 12, 24, 48 and 72 hai. Positive values in the difference plot demonstrate higher reflectance intensity of healthy leaves, negative values higher reflectance intensity of inoculated leaves. In addition, schemes of the interaction types development are illustrated. On pseudo RGB image from HSI, no symptoms are visible. Based on the reflectance spectrum, computed disease maps indicate Bgh infested pixels in white 72 hai. HR maps indicated pixels, which undergoes a hypersensitive response also in white 72 hai. (n = 8 biological replicates).</p
The utilization of high-throughput in-field phenotyping systems presents new opportunities for evalu...
BackgroundWith steadily growing interest in the use of remote-sensing technologies to detect and dia...
International audienceThe disease detection by means of hyperspectral reflectance is influenced by t...
Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. H...
Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. H...
Hyperspectral imaging sensors are valuable tools for plant disease detection and plant phenotyping. ...
Spectral vegetation indices (SVIs) have been widely used to detect different plant diseases. Wheat l...
Fungal leaf diseases cause economically important damage to crop plants. Protective treatments help ...
Bacterial leaf blight (BLB) is an important vascular disease of irrigated rice and serious infestati...
Spectral data have been widely used to estimate the disease severity (DS) levels of different plants...
Spectral Vegetation Indices (SVIs) have been widely used to indirectly detect plant diseases. The ai...
Detecting disease in crops increases yields and reduces economic loss. Traditional methods detect pl...
This methodology summarises findings from a comparison of three perspective methods of fungal diseas...
Hyperspectral remote sensing is one of the advanced and effective techniques in disease monitoring a...
Powdery mildew (Blumeria graminis) is one of the most destructive diseases, which has a significant ...
The utilization of high-throughput in-field phenotyping systems presents new opportunities for evalu...
BackgroundWith steadily growing interest in the use of remote-sensing technologies to detect and dia...
International audienceThe disease detection by means of hyperspectral reflectance is influenced by t...
Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. H...
Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. H...
Hyperspectral imaging sensors are valuable tools for plant disease detection and plant phenotyping. ...
Spectral vegetation indices (SVIs) have been widely used to detect different plant diseases. Wheat l...
Fungal leaf diseases cause economically important damage to crop plants. Protective treatments help ...
Bacterial leaf blight (BLB) is an important vascular disease of irrigated rice and serious infestati...
Spectral data have been widely used to estimate the disease severity (DS) levels of different plants...
Spectral Vegetation Indices (SVIs) have been widely used to indirectly detect plant diseases. The ai...
Detecting disease in crops increases yields and reduces economic loss. Traditional methods detect pl...
This methodology summarises findings from a comparison of three perspective methods of fungal diseas...
Hyperspectral remote sensing is one of the advanced and effective techniques in disease monitoring a...
Powdery mildew (Blumeria graminis) is one of the most destructive diseases, which has a significant ...
The utilization of high-throughput in-field phenotyping systems presents new opportunities for evalu...
BackgroundWith steadily growing interest in the use of remote-sensing technologies to detect and dia...
International audienceThe disease detection by means of hyperspectral reflectance is influenced by t...