Machine learning methods for efficient and automated in situ monitoring of peach flowering phenology

Yihang Zhu,Miaojin Chen,Qing Gu,Yiying Zhao,Xiaobin Zhang,Qinan Sun,Xianbin Gu,Kefeng Zheng

Computers and Electronics in Agriculture（2022）

引用 1|浏览3

暂无评分

摘要

•Image colors vary dramatically at different BBCH flowering phenological stages.•A random forest model classifies BBCH stages by image color ranges accurately.•Growing degree days and biological growth time improve the model accuracy.•In situ flowering phenology monitoring is applicable for peach breeding management.

查看译文

关键词

Peach flowering,Phenology,BBCH scale,In situ monitoring,Machine learning

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要