Estimation of Maize Yield and Protein Content under Different Density and N Rate Conditions Based on UAV Multi-Spectral Images

In the field of precision agriculture research, it is very important to monitor crop growth in time so as effectively conduct diagnosis and management accurately predict yield quality. this experiment, relationship between vegetation index Zhengdan 958 Suyu 41 their quality when reducing N application (25 50% reduction compared local conventional rate) under low, medium high planting densities (60,000, 75,000 90,000 plants·ha−1) during 2018–2020 was investigated using multispectral images obtained from UAV monitoring. The results showed that different density treatments, normalized (NDVI) ratio (RVI) decreased with decrease nitrogen application, while plant senescence reflectance (PSRI) increased. Through principal component analysis (PCA) subordinate function analysis, comprehensive score each treatment can reflect maize total protein content treatment. Based on index, predictive models were established. best prediction period for grain physiological maturity 35 days after silking (R4), respectively. R2 are greater than 0.734 0.769, Multi-period multi-vegetation indexes better help agricultural management.