The invention relates to the technical field of
grassland agricultural
vegetation, and provides a leguminous
forage grass yield
estimation method based on
Meta analysis and unmanned aerial vehicle multispectral
remote sensing, which comprises the following steps: step 1,
Meta analysis data integration and gradient design: retrieving and screening alfalfa field
test data through a literature
database, extracting
irrigation amount, fertilization amount and yield data, and carrying out
Meta analysis data integration and gradient design; a Meta
analysis method is adopted, a response ratio (RR) and a
confidence interval are calculated, an influence rule of different water and
fertilizer gradients on the yield is determined, an
irrigation gradient and a fertilization gradient are divided based on a Meta analysis result, and a water and
fertilizer cross treatment scheme is designed. 20-year literature data are integrated through Meta analysis,
irrigation and fertilization gradients are standardized, regional heterogeneity interference is solved, a water and
fertilizer threshold effect is defined and combined with a nonlinear optimization
algorithm, a water and fertilizer-yield
response model is established, the optimal irrigation amount and fertilization amount are accurately predicted based on an unmanned aerial vehicle multispectral
remote sensing technology, and production
capital investment is reduced by 10%-15%.