Abstract: In three national first-class agricultural meteorological observation test stations in Zhengzhou, Hebi and Huangfan district of Henan Province, 5 sets of observation equipment of Aerospace New Meteorological Technology Co., Ltd. and Henan Zhongyuan Optoelectronics Measurement and Control Technology Co., Ltd. were used to conduce continuous automatic observation experiments on the growth period, canopy height, density, leaf area index and dry matter of winter wheat and summer corn from 2016 to 2020, and at the same time, manual comparative observation was carried out. The results showed that the identification error of winter wheat in the growth period was usually within 4 days. The error in turning green and jointing period was more than 5 days, which should be supplemented by artificial observation. The average error of canopy height identification was less than 10 cm. The density fluctuated greatly during the growth period, and the effect of automatic identification was poor. The identification error of summer corn in the growth period was generally less than 4 days, and artificial observation was temporarily needed to assist in jointing, milk-ripening and ripening stages. The identification effect of the density and height was good. The identification effects on growth period, growth evaluation, canopy height and corn density of winter wheat and summer corn were good, which could be popularized and applied after optimization. However,the identification effect of the leaf area index and dry matter quality was poor, so there were no conditions for business promotion, and the algorithm or recognition technology should be improved.

Key words: winter wheat, summer corn, agricultural meteorological, automated observation, assessment