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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:

Nondestructive 3D Image Analysis Pipeline to Extract Rice Grain Traits Using X-Ray Computed Tomography
Weijuan Hu, Can Zhang, Yuqiang Jiang, et al.
Plant Phenomics (2020) Vol. 2020
Open Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Plant trait estimation and classification studies in plant phenotyping using machine vision – A review
Shrikrishna Kolhar, Jayant Jagtap
Information Processing in Agriculture (2021) Vol. 10, Iss. 1, pp. 114-135
Open Access | Times Cited: 70
3D modeling and reconstruction of plants and trees: A cross-cutting review across computer graphics, vision, and plant phenotyping
Fumio Okura
Breeding Science (2022) Vol. 72, Iss. 1, pp. 31-47
Open Access | Times Cited: 32
Next-Generation Tools for Nutrition-Inclusive Breeding for Cereals
Sunita Choudhary, Krithika Anbazhagan, Jana Kholová, et al.
IntechOpen eBooks (2025)
Closed Access
Utilizing X-ray radiography for non-destructive assessment of paddy rice grain quality traits
Murugesan Tharanya, Debarati Chakraborty, Anand Pandravada, et al.
Research Square (Research Square) (2025)
Closed Access
Evaluation of 3D seed structure and cellular traits in-situ using X-ray microscopy
Marcus Griffiths, Barsanti Gautam, Clara Lebow, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Nondestructive detection and rapid segmentation of the development process of Sitophilus zeamais in single wheat kernels based on CT and MV-UNet
Ju Gao, Ying Zhou, Yanbo Hui, et al.
Journal of Economic Entomology (2025)
Closed Access
A deep learning-based micro-CT image analysis pipeline for nondestructive quantification of the maize kernel internal structure
Juan Wang, Si Yang, Chuanyu Wang, et al.
Plant Phenomics (2025), pp. 100022-100022
Open Access
The influence of grain shape and size on the relationship between porosity and permeability in sandstone: a digital approach
Ryan L. Payton, Domenico Chiarella, Andrew Kingdon
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 26
Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning
Yuwei Lu, Rui Wang, Tianyu Hu, et al.
Frontiers in Plant Science (2023) Vol. 13
Open Access | Times Cited: 14
High-Throughput Phenotyping of Morphological Seed and Fruit Characteristics Using X-Ray Computed Tomography
Weizhen Liu, Chang Liu, Jingyi Jin, et al.
Frontiers in Plant Science (2020) Vol. 11
Open Access | Times Cited: 34
An integrated rice panicle phenotyping method based on X-ray and RGB scanning and deep learning
Lejun Yu, Jiawei Shi, Chenglong Huang, et al.
The Crop Journal (2020) Vol. 9, Iss. 1, pp. 42-56
Open Access | Times Cited: 33
Plant microphenotype: from innovative imaging to computational analysis
Ying Zhang, Shenghao Gu, Jianjun Du, et al.
Plant Biotechnology Journal (2024) Vol. 22, Iss. 4, pp. 802-818
Open Access | Times Cited: 3
Crop HTP Technologies: Applications and Prospects
Shuyuan He, Xiuni Li, Menggen Chen, et al.
Agriculture (2024) Vol. 14, Iss. 5, pp. 723-723
Open Access | Times Cited: 3
The seed morphospace, a new contribution towards the multidimensional study of angiosperm sexual reproductive biology
Angelino Carta, Filip Vandelook, Santiago Ramírez‐Barahona, et al.
Annals of Botany (2024) Vol. 134, Iss. 5, pp. 701-710
Open Access | Times Cited: 3
Panicle-3D: A low-cost 3D-modeling method for rice panicles based on deep learning, shape from silhouette, and supervoxel clustering
Dan Wu, Lejun Yu, Junli Ye, et al.
The Crop Journal (2022) Vol. 10, Iss. 5, pp. 1386-1398
Open Access | Times Cited: 17
High-throughput and separating-free phenotyping method for on-panicle rice grains based on deep learning
Yuwei Lu, Jinhu Wang, Ling Fu, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 9
3D Visualization and Volume-Based Quantification of Rice Chalkiness In Vivo by Using High Resolution Micro-CT
Yi Su, Langtao Xiao
Rice (2020) Vol. 13, Iss. 1
Open Access | Times Cited: 24
Challenges and opportunities in applying AI to evolutionary morphology
Yichen He, James M. Mulqueeney, Emily Watt, et al.
(2024)
Open Access | Times Cited: 2
Toward robust and high-throughput detection of seed defects in X-ray images via deep learning
Sherif Hamdy, Aurélie Charrier, Laurence Le Corre, et al.
Plant Methods (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 2
A High-Throughput Method for Accurate Extraction of Intact Rice Panicle Traits
Jian Sun, Zhengwei Ren, Jiale Cui, et al.
Plant Phenomics (2024) Vol. 6
Open Access | Times Cited: 2
Plant stress phenotyping: Current status and future prospects
Vishal Dinkar, Sayantan Sarkar, Saurabh Pandey, et al.
Advances in agronomy (2024), pp. 247-294
Closed Access | Times Cited: 2
High-Throughput Legume Seed Phenotyping Using a Handheld 3D Laser Scanner
Xia Huang, Shunyi Zheng, Ningning Zhu
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 431-431
Open Access | Times Cited: 12
Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form
Mitchell J. Feldmann, Amy Tabb
The Plant Phenome Journal (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 12
MCC-Net: A class attention-enhanced multi-scale model for internal structure segmentation of rice seedling stem
Minhui Chen, Juan Liao, Dequan Zhu, et al.
Computers and Electronics in Agriculture (2023) Vol. 207, pp. 107717-107717
Closed Access | Times Cited: 6
Mask R‐CNN‐based feature extraction and three‐dimensional recognition of rice panicle CT images
Huihua Kong, Ping Chen
Plant Direct (2021) Vol. 5, Iss. 5
Open Access | Times Cited: 15
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