Identification and location of maize canopy at seedling stage is an important basis for plant operation and fertilization. Aiming at the problem that fertilizer utilization rate is not high, strip and broadcast fertilizer are the main fertilization methods in China, a new method for identification and location of maize canopy in seedling stage was proposed, which could identify and locate the canopy centroid of maize in seedling stage under farmland environment. In order to locate the maize plant position quickly, the maize canopy was identified by the method of deep learning, and then the centroid location of the identified area was calculated. Firstly, Faster R-CNN was used to identify the seedling maize canopy in the field environment. Then the centroid detection algorithm based on the linear property of differential inner product improved the centroid location method of maize canopy. After the corn canopy and the weeds were segmented, the centroid of maize canopy was located and the pixel coordinates of maize seedling centroid were obtained. Through the verification in the actual farmland environment, the accuracy of identification and positioning of the canopy centroid reached 92.9%. The average detection time of a frame image was 0.17s. The positioning error of the canopy centroid was less than 1 pixel. Through the analysis of the test results, the research results can provide information support for the positioning fertilization and research basis for the followup variable fertilization operations, so as to achieve the production goal of saving fertilizer and increasing efficiency.