摘要
The root is an important organ for plants to obtain nutrients and water,and its phenotypic characteristics are closely related to its functions.Deep-learning-based high-throughput in situ root senescence feature extraction has not yet been published.In light of this,this paper suggests a technique based on the transformer neural network for retrieving cotton's in situ root senescence properties.High-resolution in situ root pictures with various levels of senescence are the main subject of the investigation.
基金
supported by grants from the National Natural Science Foundation of China(nos.32272220 and 32172120)
the Top-notch Talent Plan Program of the Education Department of Hebei Province(BJ2021058)
Central Guiding Local Science and Technology Development Fund Project(236Z7402G)
S&T Program of Hebei(23567601H)
State Key Laboratory of North China Crop Improvement and Regulation(NCCIR2024ZZ-18).
作者简介
Address correspondence to:Liantao Liu,liultday@126.com;Address correspondence to:Nan Wang,cmwn@163.com;Hui Tang,contributed equally to this work;Xue Cheng,contributed equally to this work
