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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:

Machine Learning-Assisted Approaches in Modernized Plant Breeding Programs
Mohsen Yoosefzadeh-Najafabadi, Mohsen Hesami, Milad Eskandari
Genes (2023) Vol. 14, Iss. 4, pp. 777-777
Open Access | Times Cited: 50

Showing 26-50 of 50 citing articles:

Estimating Agricultural Vulnerability to Climate Change Using a Hybrid Machine Learning Model
Usharani Bhimavarapu
Advances in environmental engineering and green technologies book series (2025), pp. 143-156
Closed Access
Synthetic seed production in Crataegus monogyna L. and prediction of regeneration of synthetic seeds with machine learning algorithms
Metin Koçak, Mustafa Can Yılmaz, Cansu Kuzğun, et al.
Plant Cell Tissue and Organ Culture (PCTOC) (2025) Vol. 161, Iss. 1
Open Access
Future Horizons: Emerging “Omics” Technologies and Challenges in Tomato
Zakir Ullah, Javed Iqbal, Bilal Haider Abbasi, et al.
(2025), pp. 347-394
Closed Access
Forest Tree Breeding Under the Global Environmental Change: Challenges and Opportunities
Chenglin Li, B.B. Li, Wenxuan Zhao, et al.
Trees Forests and People (2025) Vol. 20, pp. 100867-100867
Open Access
Physiological and AI-based study of endophytes on medicinal plants: A mini review
Saloni Kunwar, Aditya Joshi, Prateek Gururani, et al.
Plant Science Today (2023)
Open Access | Times Cited: 10
Development of Machine Learning Methods for Accurate Prediction of Plant Disease Resistance
Qi Liu, Shimin Zuo, Shasha Peng, et al.
Engineering (2024) Vol. 40, pp. 100-110
Open Access | Times Cited: 3
Unveiling the Mysteries of Non-Mendelian Heredity in Plant Breeding
Mohsen Yoosefzadeh-Najafabadi, Mohsen Hesami, Istvan Rajcan
Plants (2023) Vol. 12, Iss. 10, pp. 1956-1956
Open Access | Times Cited: 8
An Approach Toward Classifying Plant-Leaf Diseases and Comparisons With the Conventional Classification
Anita Shrotriya, Akhilesh Sharma, Srikanth Prabhu, et al.
IEEE Access (2024) Vol. 12, pp. 117379-117398
Open Access | Times Cited: 2
Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review
Fawad Ali, Yiren Zhao, Arif Ali, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 21, pp. 11360-11360
Open Access | Times Cited: 2
Application of SVR-Mediated GWAS for Identification of Durable Genetic Regions Associated with Soybean Seed Quality Traits
Mohsen Yoosefzadeh-Najafabadi, Sepideh Torabi, Dan Tulpan, et al.
Plants (2023) Vol. 12, Iss. 14, pp. 2659-2659
Open Access | Times Cited: 6
Artificial Intelligence in Agriculture
Peace Busola Falola, Abidemi Emmanuel Adeniyi, Olugbenga Ayomide Madamidola, et al.
Advances in environmental engineering and green technologies book series (2023), pp. 307-329
Closed Access | Times Cited: 5
Exploring Machine Learning Algorithms for Gene Function Prediction in Crops
Ruchi Jakhmola‐Mani, Sonali Sonali, Aniket Pandey, et al.
(2024), pp. 159-183
Closed Access | Times Cited: 1
AutoXAI4Omics: an automated explainable AI tool for omics and tabular data
James Strudwick, Laura‐Jayne Gardiner, Kate E Denning-James, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access | Times Cited: 1
Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups
Lígia de Oliveira Amaral, Glauco Vieira Miranda, Jardel da Silva Souza, et al.
Agronomy (2023) Vol. 13, Iss. 10, pp. 2476-2476
Open Access | Times Cited: 3
Artificial Intelligence Applications in Agricultural Sustainability
Imed Othmeni, R. Ben Abdallah, Hiba Ben Aribi, et al.
Advances in environmental engineering and green technologies book series (2023), pp. 187-209
Closed Access | Times Cited: 2
Technological Tools Based on Artificial Intelligence in the Sugar Industry: A Bibliometric Analysis and Future Perspectives for Energy Efficiency
Hugo Hernández Palma, Jonny Rafael Plaza Alvarado, Jesús Enrique García Guiliany, et al.
Latin American Developments in Energy Engineering (2023) Vol. 4, Iss. 2, pp. 49-64
Open Access | Times Cited: 2
Synergizing Smart Agriculture with Hybrid Deep Learning: Predicting Crop Yields Using IoT
Abhijeet Madhukar Haval, F. Rahman
BIO Web of Conferences (2024) Vol. 82, pp. 05009-05009
Open Access
Synergizing Smart Farming and Human Bioinformatics Through IoT and Sensor Devices
Sandeep Kumar Jain, Pritesh Jain
Microorganisms for sustainability (2024), pp. 139-149
Closed Access
Stress phenotyping in plants using artificial intelligence and machine learning
Krishna Kumar, Krishna Rai
(2024) Vol. 1, Iss. 1
Open Access
Unveiling insights into drought-tolerant responses in soybean: a data-driven pipeline for feature engineering in biomarker discovery
Pei-Hsiu Kao, Supaporn Baiya, C Lee, et al.
Research Square (Research Square) (2024)
Open Access
Intelligent technologies and their transformative role in modern agriculture: A comparative approach
Karishma Behera, Anita Babbar, R. G. Vyshnavi, et al.
Environment Conservation Journal (2024) Vol. 25, Iss. 3, pp. 870-880
Open Access
Spinach leaf disease identification based on deep learning techniques
Laixiang Xu, Jianguang Su, Bei Li, et al.
Plant Biotechnology Reports (2024)
Closed Access
Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes
Hamid Hatami Maleki, Reza Darvishzadeh, Ahmad Alijanpour, et al.
Heliyon (2024) Vol. 11, Iss. 1, pp. e41548-e41548
Open Access
Challenges for crop improvement
Rodomiro Ortíz
Emerging Topics in Life Sciences (2023) Vol. 7, Iss. 2, pp. 197-205
Closed Access | Times Cited: 1
Stress phenotyping in plants using artificial intelligence and machine learning
K. Mohan Kumar
(2023) Vol. 1, Iss. 1, pp. 1-2
Open Access
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