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:

Image-based phenotyping of seed architectural traits and prediction of seed weight using machine learning models in soybean
Nguyen Trung Duc, Ayyagari Ramlal, Ambika Rajendran, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 14

Showing 14 citing articles:

Gene editing and GWAS for digital imaging analysis of wheat grain weight, size and shape are inevitable to enhance the yield
Muhammad Jamil, W.A.M Wan Ahmad, Muhammad Sanwal, et al.
Cereal Research Communications (2025)
Closed Access

Predicting Wheat Grain Yield Through Morphometric Analysis of Seed Dimensions Using Computational Imaging Techniques
Mahnoor, Muhammad Jamil, Aamir Ali, et al.
Plant Molecular Biology Reporter (2025)
Closed Access

Harnessing the power of machine learning for crop improvement and sustainable production
Seyed Mahdi Hosseiniyan Khatibi, Jauhar Ali
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2

YOLOv8-licorice: a lightweight salt-resistance detection method for licorice based on seed germination state
Mo Sha, Xiuqing Fu, Ruxiao Bai, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2

Editorial: A wonder legume, soybean: prospects for improvement
Ayyagari Ramlal, Aparna Nautiyal, S. K. Lal, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 5

Using machine learning algorithms to cluster and classify stone pine (Pinus pinea L.) populations based on seed and seedling characteristics
Servet Çalışkan, Elif Kartal, Safa Balekoğlu, et al.
European Journal of Forest Research (2024) Vol. 143, Iss. 5, pp. 1575-1591
Open Access | Times Cited: 1

Topological data analysis expands the genotype to phenotype map for 3D maize root system architecture
Mao Li, Zhengbin Liu, Ni Jiang, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes
Muh Farid, Muhammad Fuad Anshori, Riccardo Rossi, et al.
Agronomy (2024) Vol. 14, Iss. 2, pp. 338-338
Open Access

Metabolic mechanism exploring tea nutrients based on stable isotope fractionation and element accumulation
Zhuoli Yu, Lalai Zikela, Jindan Han, et al.
Journal of Food Measurement & Characterization (2024) Vol. 18, Iss. 9, pp. 7507-7518
Closed Access

GRABSEEDS: extraction of plant organ traits through image analysis
Haibao Tang, Wenqian Kong, Pheonah Nabukalu, et al.
Plant Methods (2024) Vol. 20, Iss. 1
Open Access

Comparison of supervised machine learning and variable selection methods for body weight prediction of growth pigs using image processing data
Eula Regina Carrara, Polliany da Costa Santos Oliveira, Layla Cristien de Cássia Miranda Dias, et al.
Revista Brasileira de Zootecnia (2024) Vol. 53
Open Access

Prediction of Total Anthocyanin Content in Single Kernel Maize Using Spectral and Color Space Data Coupled with Automl
Fatih Kahrıman, Umut Songur, Ezgi Alaca Yıldırım, et al.
(2024)
Closed Access

Analysis of Seed Morphological and Color Traits in Recombinant Inbred Line(RIL) Population of Maize(zea mays) using RGB based Images
Yeong-Tae Kim, Min‐Ji Kim, Young-Uk Kim, et al.
Journal of the Korean Society of International Agriculture (2023) Vol. 35, Iss. 4, pp. 311-319
Closed Access

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