Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants-Reference-Cited by-同舟云学术

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Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants

Published:2021-01 Issue:1 Volume:4 Page:
ISSN:2578-2703
Container-title:The Plant Phenome Journal
language:en
Short-container-title:The Plant Phenome Journal

Author:

Feldmann Mitchell J.¹^ORCID,Gage Joseph L.²^ORCID,Turner‐Hissong Sarah D.³^ORCID,Ubbens Jordan R.⁴^ORCID

Affiliation:

1. Dep. of Plant Sciences Univ. of California ‐ Davis Davis CA 95616 USA

2. Institute for Genomic Diversity Cornell Univ. Ithaca NY 14853 USA

3. Bayer Crop Science Chesterfield MO 63017 USA

4. Global Institute for Food Security Univ. of Saskatchewan Saskatoon SK S7N 0W9 Canada

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ppj2.20023

Reference173 articles.

1. Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci

2. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines

3. leafprocessor: a new leaf phenotyping tool using contour bending energy and shape cluster analysis

4. MorphoGraphX: A platform for quantifying morphogenesis in 4D

5. We aren’t good at picking candidate genes, and it’s slowing us down

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning in Image-Based Plant Phenotyping;Annual Review of Plant Biology;2024-07-22

2. High-throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models;2024-05-17

3. Spatio-temporal modeling of high-throughput multispectral aerial images improves agronomic trait genomic prediction in hybrid maize;GENETICS;2024-03-12

4. Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms;Frontiers in Plant Science;2024-02-20

5. High-Throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models;Plant Phenomics;2024-01

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