A water stress detection method for tomatoes in a seedling stage based on micro-CT and polarization-hyperspectral imaging multi-feature fusion, comprising: using micro-CT to scan microscopic morphological features such as water stress stomata, spongy body, palisade tissue, cilia, vascular bundle, root volume, main root, and root hair density of tomatoes； using a polarization-hyperspectral imaging system to obtain macroscopic morphological features such as crown width, plant height, and leaf inclination of water stress plants, as well as leaf vein distribution, average gray, and leaf margin shaded area under a water-sensitive wavelength of 1450 nm, and macroscopic morphological features such as polarization states, stock vectors, and Mueller matrix variables of 1450 nm feature images at 0°, 45°, 90°, 135°, and 180° feature polarization angles. By fusion of internal and external structures, above-ground, underground, and macroscopic and microscopic morphological features of water stress tomatoes, and mutual fusion of water stress feature wavelength images and polarization state features, advantages are complementary, comprehensive and precise extraction and precise quantitative analysis of water stress features of the tomatoes are implemented, and a basis for scientific management of water and fertilizer integration of facilities is provided.
