中国农学通报2025，Vol.41Issue(1)：1-7,7.
冬小麦发育期识别方法研究进展
Research Progress on Winter Wheat Growth Period Recognition Methods
摘要
Abstract
China is a major agricultural country. With the rapid development of agricultural science and technology,agriculture has entered a new stage of development with high yield,high quality,and high efficiency. Achieving automation and intelligent observation of crop growth period recognition is a crucial part of agricultural modernization. This paper introduced the current research status of crop growth period recognition and presented two methods for automatic observation and identification of winter wheat growth period,one based on the Normalized Difference Vegetation Index (NDVI) and the other based on deep learning. Using winter wheat in Henan as an example,the results of automatic observation and identification from both methods were compared with manual observations. The results validated the feasibility and effectiveness of both identification methods,showing high accuracy and efficiency,thereby improving measurement efficiency and reliability. In terms of identification accuracy,the two methods had their own strengths at different growth periods and could complement each other. The deep learning-based identification method demonstrated better generalizability compared to the NDVI-based method. However,both methods required optimization and upgrading in the future to further enhance identification accuracy.关键词
冬小麦/发育期/图像识别/归一化植被指数/深度学习Key words
winter wheat/growth period/image recognition/normalized differential vegetation index (NDVI)/deep learning分类
农业科技引用本文复制引用
王苗苗,王贝贝,李明放,张志红,严雪..冬小麦发育期识别方法研究进展[J].中国农学通报,2025,41(1):1-7,7.基金项目
中国气象局农业气象保障与应用技术重点开放实验室开放研究基金项目"物候气象智能化观测仪研发及其应用"(AMF202203). （AMF202203）
