Fusarium head blight (FHB) is a fungal disease in wheat, primarily caused by Fusarium graminearum (Fg), which reduces yield and results in mycotoxin accumulation in the grain. Resistance to FHB is evaluated by phenotyping inoculated plants. Two recombinant inbred wheat line populations were assessed in inoculated Fusarium nurseries, and a significant relationship was found between mycotoxin content in the grain and Fusarium-damaged kernels (R2=0.16). A detached wheat head bioassay using winter wheat cultivars point inoculated with Fg isolates demonstrated specific interactions between wheat cultivars and isolates. To improve selection efficiency for FHB resistance in wheat, a new innovative method combining deep learning with spectral indices derived from cell phone images of infected wheat heads was developed to estimate disease severity. The method demonstrated high accuracy (88%) in estimating infected tissue and showed a strong correlation with visual symptom assessment (R² = 0.83).