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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:

High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling
Kakeru Watanabe, Wei Guo, Keigo Arai, et al.
Frontiers in Plant Science (2017) Vol. 8
Open Access | Times Cited: 244

Showing 1-25 of 244 citing articles:

Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture
Wouter H. Maes, Kathy Steppe
Trends in Plant Science (2018) Vol. 24, Iss. 2, pp. 152-164
Closed Access | Times Cited: 724
Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives
Wanneng Yang, Hui Feng, Xuehai Zhang, et al.
Molecular Plant (2020) Vol. 13, Iss. 2, pp. 187-214
Open Access | Times Cited: 647
Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives
Guijun Yang, Jiangang Liu, Chunjiang Zhao, et al.
Frontiers in Plant Science (2017) Vol. 8
Open Access | Times Cited: 638
Computer vision technology in agricultural automation —A review
Hongkun Tian, Tianhai Wang, Yadong Liu, et al.
Information Processing in Agriculture (2019) Vol. 7, Iss. 1, pp. 1-19
Open Access | Times Cited: 517
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Liang Han, Guijun Yang, Huayang Dai, et al.
Plant Methods (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 363
The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems
Jinha Jung, Murilo Maeda, Anjin Chang, et al.
Current Opinion in Biotechnology (2020) Vol. 70, pp. 15-22
Open Access | Times Cited: 340
A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform
Muhammad Adeel Hassan, Mengjiao Yang, Awais Rasheed, et al.
Plant Science (2018) Vol. 282, pp. 95-103
Closed Access | Times Cited: 331
An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery
Ana Isabel de Castro, Jorge Torres‐Sánchez, José M. Peña, et al.
Remote Sensing (2018) Vol. 10, Iss. 2, pp. 285-285
Open Access | Times Cited: 252
Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
Antoine Harfouche, Daniel Jacobson, David Kainer, et al.
Trends in biotechnology (2019) Vol. 37, Iss. 11, pp. 1217-1235
Open Access | Times Cited: 203
Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system
Ning Lu, Jie Zhou, Zixu Han, et al.
Plant Methods (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 184
In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR
Shangpeng Sun, Changying Li, Andrew H. Paterson, et al.
Frontiers in Plant Science (2018) Vol. 9
Open Access | Times Cited: 179
Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective
Keiichi Mochida, Satoru Koda, Komaki Inoue, et al.
GigaScience (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 165
How does nitrogen shape plant architecture?
Le Luo, Yali Zhang, Guohua Xu
Journal of Experimental Botany (2020) Vol. 71, Iss. 15, pp. 4415-4427
Open Access | Times Cited: 159
Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
Yunbi Xu, Xingping Zhang, Huihui Li, et al.
Molecular Plant (2022) Vol. 15, Iss. 11, pp. 1664-1695
Open Access | Times Cited: 159
A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenotyping
Lei Feng, Shuangshuang Chen, Chu Zhang, et al.
Computers and Electronics in Agriculture (2021) Vol. 182, pp. 106033-106033
Closed Access | Times Cited: 156
High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field
Daoliang Li, Chaoqun Quan, Zhaoyang Song, et al.
Frontiers in Bioengineering and Biotechnology (2021) Vol. 8
Open Access | Times Cited: 125
Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms
Shuaibing Liu, Xiuliang Jin, Chenwei Nie, et al.
PLANT PHYSIOLOGY (2021) Vol. 187, Iss. 3, pp. 1551-1576
Open Access | Times Cited: 112
Plant height measurement using UAV-based aerial RGB and LiDAR images in soybean
Lalit Pun Magar, Jeremy Sandifer, Deepak Khatri, et al.
Frontiers in Plant Science (2025) Vol. 16
Open Access | Times Cited: 2
Dynamic monitoring of biomass of rice under different nitrogen treatments using a lightweight UAV with dual image-frame snapshot cameras
Haiyan Cen, Liang Wan, Jiangpeng Zhu, et al.
Plant Methods (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 140
Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding
Pengcheng Hu, Scott Chapman, Xue Min Wang, et al.
European Journal of Agronomy (2018) Vol. 95, pp. 24-32
Open Access | Times Cited: 139
What is cost-efficient phenotyping? Optimizing costs for different scenarios
Daniel Reynolds, Frédéric Baret, Claude Welcker, et al.
Plant Science (2018) Vol. 282, pp. 14-22
Open Access | Times Cited: 133
Dynamic plant height QTL revealed in maize through remote sensing phenotyping using a high-throughput unmanned aerial vehicle (UAV)
Xiaqing Wang, Ruyang Zhang, Wei Song, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 126
Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments
Richard Boyles, Zachary Brenton, Stephen Kresovich
The Plant Journal (2018) Vol. 97, Iss. 1, pp. 19-39
Open Access | Times Cited: 120
Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat
Muhammad Adeel Hassan, Mengjiao Yang, Luping Fu, et al.
Plant Methods (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 113
Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture
Kyosuke Yamamoto, Takashi Togami, Norio Yamaguchi
Sensors (2017) Vol. 17, Iss. 11, pp. 2557-2557
Open Access | Times Cited: 111
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