Developing a Deep Learning network “MSCP-Net” to generate stalk anatomical traits related with crop lodging and yield in maize-Reference-Cited by-同舟云学术

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Developing a Deep Learning network “MSCP-Net” to generate stalk anatomical traits related with crop lodging and yield in maize

Published:2024-10 Issue: Volume:160 Page:127325
ISSN:1161-0301
Container-title:European Journal of Agronomy
language:en
Short-container-title:European Journal of Agronomy

Author:

Zhou Haiyu,Li Xiang,Jiang Yufeng,Zhu Xiaoying,Fu Taiming,Yang Mingchong,Cheng Weidong,Xie Xiaodong,Chen Yan,Wang Lingqiang

Funder

Guangxi Academy of Agricultural Science

Guangxi Science and Technology Department

Guangxi Natural Science Foundation

Publisher

Elsevier BV

Reference34 articles.

1. Darkfield and fluorescence macrovision of a series of large images to assess anatomical and chemical tissue variability in whole cross-sections of maize stems;Berger;Front. Plant Sci.,2021

2. Soft-NMS--improving object detection with one line of code;Bodla;Proc. IEEE Int. Conf. Comput. Vis. (ICCV),2017

3. X-ray microtomography (micro-ct): a reference technology for high-resolution quantification of xylem embolism in trees;Cochard;Plant, Cell Environ.,2015

4. Micron-scale phenotyping quantification and three-dimensional microstructure reconstruction of vascular bundles within maize stalks based on micro-ct scanning;Du;Funct. Plant Biol.,2016

5. A deep learning-integrated phenotyping pipeline for vascular bundle phenotypes and its application in evaluating sap flflow in the maize stem;Du;Crop J.,2022

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