The application discloses a corn
nitrogen reduction and
biochar effect
time sequence dynamic characteristic evaluation method, first, different combinations are set,
chlorophyll fluorescence parameters, crown layer spectral reflectance and yield data of corn at key growth stages such as jointing stage and big
bell mouth stage are collected; second, the
spectral data is preprocessed, single time phase red edge characteristics are calculated, and
time sequence dynamic characteristics are constructed,
biochar sensitive wave bands are screened through reflectance difference percentage during growth, red edge index is designed, and
fluorescence weight
spectral index is constructed in combination with
wide band vegetation index; then, the data is integrated to construct a multi-time phase spectral characteristic
data set, a
time sequence dynamic
chlorophyll inversion model containing dynamic inversion, yield prediction and attribution branches is built, the former outputs
chlorophyll and photosynthetic code vector at the
grain filling stage, and the latter predicts yield and related parameter contribution; finally, the model is trained, the
optimal matching is obtained based on the trained model, and support is provided for corn planting and fertilization decision-making.