Applications in Plant Sciences · 2018 · 59 citations · 6 references
AgriculturePlant BiologyPlant SciencesPlant EcophysiologyPlant PhysiologyRemote SensingCrop Stress DetectionPlant Stress DetectionStress PhenotypingVegetation Cover AssessmentVegetation IndicesVegetation MonitoringCrop Stress AssessmentImage-based Stress DetectionPlant Stress ResponsesReflectanceVegetation Condition MonitoringVegetation Health AssessmentVegetation Health IndicesVegetation Stress Detection
Premise of the Study An imaging system was refined to monitor the health of vegetation grown in controlled conditions using spectral reflectance patterns. To measure plant health, the single‐image normalized difference vegetation index ( SI ‐ NDVI ) compares leaf reflectance in visible and near‐infrared light spectrums. Methods and Results The SI ‐ NDVI imaging system was characterized to assess plant responses to stress before visual detection during controlled stress assays. Images were analyzed using Fiji image processing software and Microsoft Excel to create qualitative false color images and quantitative graphs to detect plant stress. Conclusions Stress was detected in Arabidopsis thaliana seedlings within 15 min of salinity application using SI ‐ NDVI analysis, before stress was visible. Stress was also observed during ammonium nitrate treatment of Eruca sativa plants before visual detection. Early detection of plant stress is possible using SI ‐ NDVI imaging, which is both simpler to use and more cost efficient than traditional dual‐image NDVI or hyper‐spectral imaging.
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Fiji: an open-source platform for biological-image analysis
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Nicole S. Beisel, Jordan Callaham, Natasha Sng et al. · Applications in Plant Sciences · 2018 · 59 citations · Full text