Plant growth and development depends on essential macronutrients such as nitrogen (N), phosphorus (P), and potassium (K), and deficiencies in these nutrients result in significant physiological and morphological changes. Leaf biochemical and biophysical properties influence light absorption and reflectance across various wavelengths, providing insights into canopy health. Advancements in high-throughput (HT) digital phenotyping technologies, including high-resolution scanning and multispectral imaging, have improved plant health assessment and monitoring. The TraitFinder, a digital phenotyping system developed by Phenospex, is equipped with two PlantEye-600 multispectral 3D laser scanners that generate three-dimensional plant models while capturing multispectral data. The system directs light in green (G), blue (B), red (R), and near-infrared (NIR) wavelengths onto the plant canopy and captures the reflected signals, which are then used to compute vegetation indices for plant health evaluation. This study utilized the TraitFinder system to determine reference values for vegetation indices associated with healthy plants and those deficient in N, P, and K. Four ornamental species—coleus (Solenostemon scutellarioides), marigold (Tagetes patula), petunia (Petunia × hybrida), and celosia (Celosia plumosa)—were evaluated over time. The experiment followed a randomized complete block design with eight replications and four nutrient treatments: a complete Hoagland’s solution and three modified versions, each lacking one macronutrient (N, P, or K). Morphological traits, such as biomass, showed reduced plant growth under nutrient-deficient conditions. Spectral data revealed common trends in nutrient-deficient plants, including decreased Green Leaf Index (GLI) and Normalized Difference Vegetation Index (NDVI) and increased Normalized Pigment Chlorophyll Ratio Index (NPCI) and Plant Senescence Reflectance Index (PSRI) compared to controls. In healthy plants, GLI ranged from 0.2 to 0.35, NDVI from 0.4 to 0.75, NPCI from 0.10 to 0.45, and PSRI from 0.07 to 0.25. However, species-specific responses to nutrient deficiencies were also observed. This study highlights the distinct morphological and physiological responses of ornamental species to macronutrient deficiencies and demonstrates the effectiveness of digital phenotyping using the TraitFinder system for tracking plant health over time. The findings emphasize the potential of HT digital phenotyping which could enhance ornamental crop management.
