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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:

Modeling and optimizing in vitro seed germination of industrial hemp (Cannabis sativa L.)
Mohsen Hesami, Marco Pepe, Adrian S. Monthony, et al.
Industrial Crops and Products (2021) Vol. 170, pp. 113753-113753
Closed Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Machine learning (ML) algorithms and artificial neural network for optimizing in vitro germination and growth indices of industrial hemp (Cannabis sativa L.)
Muhammad Aasım, Ramazan Katırcı, Ozlem Akgur, et al.
Industrial Crops and Products (2022) Vol. 181, pp. 114801-114801
Closed Access | Times Cited: 57
Current status and future prospects in cannabinoid production through in vitro culture and synthetic biology
Mohsen Hesami, Marco Pepe, Austin Baiton, et al.
Biotechnology Advances (2022) Vol. 62, pp. 108074-108074
Closed Access | Times Cited: 54
Application of artificial neural network and machine learning algorithms for modeling the in vitro regeneration of chickpea (Cicer arietinum L.)
Arife Kirtiş, Muhammad Aasım, Ramazan Katırcı
Plant Cell Tissue and Organ Culture (PCTOC) (2022) Vol. 150, Iss. 1, pp. 141-152
Closed Access | Times Cited: 36
Toward sustainable culture media: Using artificial intelligence to optimize reduced-serum formulations for cultivated meat
Amin Nikkhah, Abbas Rohani, Mohammad Zarei, et al.
The Science of The Total Environment (2023) Vol. 894, pp. 164988-164988
Open Access | Times Cited: 23
Optimizing Micropropagation and Rooting Protocols for Diverse Lavender Genotypes: A Synergistic Approach Integrating Machine Learning Techniques
Özhan Şimşek, Akife Dalda Şekerci, Musab A. Isak, et al.
Horticulturae (2024) Vol. 10, Iss. 1, pp. 52-52
Open Access | Times Cited: 10
Machine Learning Offers Insights into the Impact of In Vitro Drought Stress on Strawberry Cultivars
Özhan Şimşek
Agriculture (2024) Vol. 14, Iss. 2, pp. 294-294
Open Access | Times Cited: 7
Applications of Machine Learning in Cannabis Research: A Scoping Review
Jeremy Y. Ng, Mrinal M. Lad, Dhruv Patel, et al.
European Journal of Integrative Medicine (2025)
Closed Access
Machine Learning-Mediated Development and Optimization of Disinfection Protocol and Scarification Method for Improved In Vitro Germination of Cannabis Seeds
Marco Pepe, Mohsen Hesami, Andrew Maxwell Phineas Jones
Plants (2021) Vol. 10, Iss. 11, pp. 2397-2397
Open Access | Times Cited: 45
Comparative Analysis of Machine Learning and Evolutionary Optimization Algorithms for Precision Micropropagation of Cannabis sativa: Prediction and Validation of in vitro Shoot Growth and Development Based on the Optimization of Light and Carbohydrate Sources
Marco Pepe, Mohsen Hesami, Finlay Small, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 41
New Insight into Ornamental Applications of Cannabis: Perspectives and Challenges
Mohsen Hesami, Marco Pepe, Austin Baiton, et al.
Plants (2022) Vol. 11, Iss. 18, pp. 2383-2383
Open Access | Times Cited: 33
In vitro plant tissue culture as the fifth generation of bioenergy
Omid Norouzi, Mohsen Hesami, Marco Pepe, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 29
Prediction of sugar beet yield and quality parameters with varying nitrogen fertilization using ensemble decision trees and artificial neural networks
Ivana Varga, Dorijan Radočaj, Mladen Jurišić, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108076-108076
Closed Access | Times Cited: 19
Challenges and potentials of new breeding techniques in Cannabis sativa
Christina Ingvardsen, Henrik Brinch‐Pedersen
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 14
Application of artificial neural networks and genetic algorithm to predict and optimize greenhouse banana fruit yield through nitrogen, potassium and magnesium
Mahmoud Reza Ramezanpour, Mostafa Farajpour
PLoS ONE (2022) Vol. 17, Iss. 2, pp. e0264040-e0264040
Open Access | Times Cited: 24
Artificial neural network modeling for deciphering the in vitro induced salt stress tolerance in chickpea (Cicer arietinum L)
Muhammad Aasım, Fatma Ebru Akın, Syed Amjad Ali, et al.
Physiology and Molecular Biology of Plants (2023)
Open Access | Times Cited: 11
Machine learning-mediated Passiflora caerulea callogenesis optimization
Marziyeh Jafari, Mohammad Hosein Daneshvar
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0292359-e0292359
Open Access | Times Cited: 3
A novel approach for direct shoot regeneration, anatomical characterization, and withanolides content in micropropagated plants of Withania somnifera (L.) Dunal—an important medicinal plant
Ganesan Mahendran, Laiq ur Rahman
In Vitro Cellular & Developmental Biology - Plant (2024) Vol. 60, Iss. 3, pp. 365-377
Closed Access | Times Cited: 3
Leveraging machine learning to unravel the impact of cadmium stress on goji berry micropropagation
Musab A. Isak, Taner Bozkurt, Mehmet Tütüncü, et al.
PLoS ONE (2024) Vol. 19, Iss. 6, pp. e0305111-e0305111
Open Access | Times Cited: 3
Machine Learning-Assisted In Vitro Rooting Optimization in Passiflora caerulea
Marziyeh Jafari, Mohammad Hosein Daneshvar, Sahar Jafari, et al.
Forests (2022) Vol. 13, Iss. 12, pp. 2020-2020
Open Access | Times Cited: 19
Polyacrylamide Hydrogel Enriched with Amber for In Vitro Plant Rooting
Л. О. Керносенко, Kateryna Samchenko, Olena Goncharuk, et al.
Plants (2023) Vol. 12, Iss. 5, pp. 1196-1196
Open Access | Times Cited: 10
Prediction and optimization of indirect shoot regeneration of Passiflora caerulea using machine learning and optimization algorithms
Marziyeh Jafari, Mohammad Hosein Daneshvar
BMC Biotechnology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 10
Comparative analysis of different artificial neural networks for predicting and optimizing in vitro seed germination and sterilization of petunia
Hamed Rezaei, Asghar Mirzaie-Asl, Mohammad Reza Abdollahi, et al.
PLoS ONE (2023) Vol. 18, Iss. 5, pp. e0285657-e0285657
Open Access | Times Cited: 9
Modeling Callus Induction and Regeneration in Hypocotyl Explant of Fodder Pea (Pisum sativum var. arvense L.) Using Machine Learning Algorithm Method
Aras Türkoğlu, Parisa Bolouri, Kamil Haliloğlu, et al.
Agronomy (2023) Vol. 13, Iss. 11, pp. 2835-2835
Open Access | Times Cited: 9
Application of machine learning algorithms and feature selection in rapeseed (Brassica napus L.) breeding for seed yield
Masoud Shahsavari, Valiollah Mohammadi, Bahram Alizadeh, et al.
Plant Methods (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 8
Enhancing petunia tissue culture efficiency with machine learning: A pathway to improved callogenesis
Hamed Rezaei, Asghar Mirzaie-Asl, Mohammad Reza Abdollahi, et al.
PLoS ONE (2023) Vol. 18, Iss. 11, pp. e0293754-e0293754
Open Access | Times Cited: 8
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