OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives
Haiyu Tao, Shan Xu, Yongchao Tian, et al.
Plant Communications (2022) Vol. 3, Iss. 6, pp. 100344-100344
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture
Danuta Cembrowska-Lech, Adrianna Krzemińska, Tymoteusz Miller, et al.
Biology (2023) Vol. 12, Iss. 10, pp. 1298-1298
Open Access | Times Cited: 25

Detection and Evaluation of Environmental Stress in Winter Wheat Using Remote and Proximal Sensing Methods and Vegetation Indices—A Review
Sandra Skendžić, Monika Zovko, Vinko Lešić, et al.
Diversity (2023) Vol. 15, Iss. 4, pp. 481-481
Open Access | Times Cited: 23

Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season
Siphiwokuhle Buthelezi, Onisimo Mutanga, Mbulisi Sibanda, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1597-1597
Open Access | Times Cited: 21

Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques
Muhammad Salman Akhtar, Zuhair Zafar, Raheel Nawaz, et al.
Computers and Electronics in Agriculture (2024) Vol. 222, pp. 109033-109033
Closed Access | Times Cited: 10

PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification
Ruinan Zhang, Shichao Jin, Yuanhao Zhang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 208, pp. 136-157
Closed Access | Times Cited: 9

High-throughput proximal ground crop phenotyping systems – A comprehensive review
Z. Y. Rui, Zhe Zhang, Michael Zhang, et al.
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109108-109108
Closed Access | Times Cited: 8

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs
Ocident Bongomin, Jimmy Lamo, Joshua Mugeziaubwa Guina, et al.
The Plant Phenome Journal (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 7

Deep learning models based on hyperspectral data and time-series phenotypes for predicting quality attributes in lettuces under water stress
S.K. Yu, Jiangchuan Fan, Xianju Lu, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108034-108034
Closed Access | Times Cited: 16

What plant breeding may (and may not) look like in 2050?
Filippo M. Bassi, Miguel Sanchez‐Garcia, Rodomiro Ortíz
The Plant Genome (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 16

Radar vegetation indices for monitoring surface vegetation: Developments, challenges, and trends
Xueqian Hu, Li Li, Jianxi Huang, et al.
The Science of The Total Environment (2024) Vol. 945, pp. 173974-173974
Closed Access | Times Cited: 6

Advances in the tea plants phenotyping using hyperspectral imaging technology
Baidong Luo, Hong-Wei Sun, Leilei Zhang, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 5

High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices
Melissa Cristina de Carvalho Miranda, Alexandre Hild Aono, Talieisse Gomes Fagundes, et al.
Agronomy Journal (2025) Vol. 117, Iss. 1
Open Access

Breeding Climate-Resilient Sunflowers in the Climate Change Era: Current Breeding Strategies and Prospects
R. Manivannan, R. Sasikala, R. P. Ramteke, et al.
(2025), pp. 349-405
Closed Access

Morphological characteristic extraction of unopened cotton bolls using image analysis and geometric modeling methods
Rongqiao He, Pei Yang, Chao Tang, et al.
Computers and Electronics in Agriculture (2025) Vol. 232, pp. 110094-110094
Closed Access

Crop adaptation to climate change: An evolutionary perspective
Lexuan Gao, Michael B. Kantar, Dylan R. Moxley, et al.
Molecular Plant (2023) Vol. 16, Iss. 10, pp. 1518-1546
Open Access | Times Cited: 14

Field-measured canopy height may not be as accurate and heritable as believed: evidence from advanced 3D sensing
Jingrong Zang, Shichao Jin, Songyin Zhang, et al.
Plant Methods (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 13

Energy-Efficient IoT-Based Light Control System in Smart Indoor Agriculture
Oussama Hadj Abdelkader, Hadjer Bouzebiba, Danilo Pena, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7670-7670
Open Access | Times Cited: 11

Molecular Advances to Combat Different Biotic and Abiotic Stresses in Linseed (Linum usitatissimum L.): A Comprehensive Review
Shruti Paliwal, M. K. Tripathi, Sushma Tiwari, et al.
Genes (2023) Vol. 14, Iss. 7, pp. 1461-1461
Open Access | Times Cited: 9

UAS Quality Control and Crop Three-Dimensional Characterization Framework Using Multi-Temporal LiDAR Data
Nadeem Fareed, Anup Das, Paulo Flores, et al.
Remote Sensing (2024) Vol. 16, Iss. 4, pp. 699-699
Open Access | Times Cited: 2

Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms
N. Ace Pugh, Andrew W. Young, M. D. Ojha, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2

Trait Improvement of Solanaceae Fruit Crops for Vertical Farming by Genome Editing
Choon‐Tak Kwon
Journal of Plant Biology (2022) Vol. 66, Iss. 1, pp. 1-14
Closed Access | Times Cited: 9

Omics technologies for crop improvement
Arvind Kumar Yadav, Bharti Shree, Deepika Lakhwani, et al.
Elsevier eBooks (2024), pp. 293-313
Closed Access | Times Cited: 1

Evaluation of Soybean Drought Tolerance Using Multimodal Data from an Unmanned Aerial Vehicle and Machine Learning
Heng Liang, Yonggang Zhou, Yuwei Lu, et al.
Remote Sensing (2024) Vol. 16, Iss. 11, pp. 2043-2043
Open Access | Times Cited: 1

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