Utilization of single‐image normalized difference vegetation index (SI‐NDVI) for early plant stress detection

Abstract

Premise of the StudyAn 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 ResultsThe 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.ConclusionsStress 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.

Performance of multiple turfgrass species during prolonged heat stress and recovery in a controlled environment

“…The normalized difference vegetation index (NDVI) is a known indicator of plant health and was therefore used to assess turfgrass performance during the heat stress and recovery periods (Beisel et al., 2018). A FieldScout TCM 500 NDVI TurfColor meter (Spectrum Technologies) meter was placed on top of the pot, and the NDVI value was recorded.…”

The Plant Health Monitoring System of the EDEN ISS Space Greenhouse in Antarctica During the 2018 Experiment Phase

“…The extensive control capabilities of the Illumination System enables the use of approaches such as Normalized Difference Vegetation Index (NDVI) in the evaluation and monitoring of plant health. In particular, the modified GoPro cameras of the Dual Wavelength Spectral Imaging System allow NDVI and NDVI-like approaches to be taken using single RGB images and established post-processing algorithms (Beisel et al, 2018). Using these simple RGB images and commercial cameras allowed the flexible deployment of NDVI imaging within the physical and cost constraints of the project, and minimized the data management loads compared to the use of a true hyperspectral imaging system.…”

“…For the initial deployment of spectral imaging within the FEG, GoPro Hero4 cameras were modified to become Dual Wavelength Spectral Imagers (Beisel et al, 2018). The infrared (IR) filters were removed to allow Near IR (NIR) into the sensor ( Figures 2 and 8 ) and a dual wavelength filter was added so as to collect and segregate the NIR (690–790 nm) and Blue (380–550 nm) wavebands.…”

“…The basic steps involved in the assembly and deployment of the Dual Wavelength Spectral Imaging GoPro system (A) , and a test sample of images captured in healthy and salt-stressed plants, including false color NDVI renditions that use color to highlight NDVI pixel values that change with salt stress as an example (B) . (Beisel et al, 2018). The imaging filter is NDVI-7 () and the camera adaptations were from Ribcage ().…”

“…Essentially, the plants themselves will be queried to assess their health, and the environment adjusted accordingly or the on-site operator requested to implement other corrective actions. Various imaging techniques exist for such plant health monitoring systems (Chaerle and Van Der Straeten, 2001; Li et al, 2014; Saglam et al, 2019) and considering that controlled environment agriculture (CEA) systems can largely regulate each photon of input light, there are numerous new techniques in the exploratory phase (Ferl et al, 2017; Beisel et al, 2018).…”