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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:

Crop yield prediction integrating genotype and weather variables using deep learning
Johnathon M. Shook, Tryambak Gangopadhyay, Linjiang Wu, et al.
PLoS ONE (2021) Vol. 16, Iss. 6, pp. e0252402-e0252402
Open Access | Times Cited: 146

Showing 1-25 of 146 citing articles:

Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
Tawseef Ayoub Shaikh, Tabasum Rasool, Faisal Rasheed Lone
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107119-107119
Closed Access | Times Cited: 430
Remote Sensing in Field Crop Monitoring: A Comprehensive Review of Sensor Systems, Data Analyses and Recent Advances
Emmanuel Omia, Hyungjin Bae, Eunsung Park, et al.
Remote Sensing (2023) Vol. 15, Iss. 2, pp. 354-354
Open Access | Times Cited: 117
Winter wheat yield prediction using convolutional neural networks from environmental and phenological data
Amit Kumar Srivastava, Nima Safaei, Saeed Khaki, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 100
Fruit classification using attention-based MobileNetV2 for industrial applications
Tej Bahadur Shahi, Chiranjibi Sitaula, Arjun Neupane, et al.
PLoS ONE (2022) Vol. 17, Iss. 2, pp. e0264586-e0264586
Open Access | Times Cited: 99
Machine learning bridges omics sciences and plant breeding
Jun Yan, Xiangfeng Wang
Trends in Plant Science (2022) Vol. 28, Iss. 2, pp. 199-210
Closed Access | Times Cited: 74
Multispectral Crop Yield Prediction Using 3D-Convolutional Neural Networks and Attention Convolutional LSTM Approaches
Seyed Mahdi Mirhoseini Nejad, Dariush Abbasi‐Moghadam, Alireza Sharifi, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022) Vol. 16, pp. 254-266
Open Access | Times Cited: 70
Interpretability of deep learning models for crop yield forecasting
Dilli Paudel, Allard de Wit, Hendrik Boogaard, et al.
Computers and Electronics in Agriculture (2023) Vol. 206, pp. 107663-107663
Open Access | Times Cited: 54
Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield
Tongxi Hu, Xuesong Zhang, Gil Bohrer, et al.
Agricultural and Forest Meteorology (2023) Vol. 336, pp. 109458-109458
Open Access | Times Cited: 45
Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India
Anurag Satpathi, Parul Setiya, Bappa Das, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 2786-2786
Open Access | Times Cited: 42
Mapping smart farming: Addressing agricultural challenges in data-driven era
Dongyang Huo, Asad Waqar Malik, Sri Devi Ravana, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 113858-113858
Open Access | Times Cited: 42
A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction
Wei Zhou, Zhengxiao Yan, Liting Zhang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 28
Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods
Tongxi Hu, Xuesong Zhang, Sami Khanal, et al.
Environmental Modelling & Software (2024) Vol. 179, pp. 106119-106119
Closed Access | Times Cited: 19
UAS-Based Plant Phenotyping for Research and Breeding Applications
Wei Guo, Matthew E. Carroll, Arti Singh, et al.
Plant Phenomics (2021) Vol. 2021
Open Access | Times Cited: 95
Plant Genotype to Phenotype Prediction Using Machine Learning
Monica F. Danilevicz, Mitchell Gill, Robyn Anderson, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 56
Quick and accurate monitoring peanut seedlings emergence rate through UAV video and deep learning
Yongda Lin, Tingting Chen, Shiyuan Liu, et al.
Computers and Electronics in Agriculture (2022) Vol. 197, pp. 106938-106938
Closed Access | Times Cited: 51
Estimation of soybean grain yield from multispectral high-resolution UAV data with machine learning models in West Africa
Tunrayo Alabi, Abush Tesfaye, Godfree Chigeza, et al.
Remote Sensing Applications Society and Environment (2022) Vol. 27, pp. 100782-100782
Open Access | Times Cited: 46
Machine Learning for Plant Stress Modeling: A Perspective towards Hormesis Management
Amanda Kim Rico-Chávez, Jesus Alejandro Franco, Arturo A. Fernandez‐Jaramillo, et al.
Plants (2022) Vol. 11, Iss. 7, pp. 970-970
Open Access | Times Cited: 43
Multimodal Deep Learning for Rice Yield Prediction Using UAV-Based Multispectral Imagery and Weather Data
Md. Suruj Mia, Ryoya Tanabe, Luthfan Nur Habibi, et al.
Remote Sensing (2023) Vol. 15, Iss. 10, pp. 2511-2511
Open Access | Times Cited: 30
Applications of deep learning in understanding gene regulation
Zhongxiao Li, Elva Gao, Juexiao Zhou, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 1, pp. 100384-100384
Open Access | Times Cited: 27
A predictive analytics model for crop suitability and productivity with tree-based ensemble learning
Isaac Kofi Nti, Muhammad Adib Uz Zaman, Owusu Nyarko‐Boateng, et al.
Decision Analytics Journal (2023) Vol. 8, pp. 100311-100311
Open Access | Times Cited: 26
Cyber-agricultural systems for crop breeding and sustainable production
Soumik Sarkar, Baskar Ganapathysubramanian, Arti Singh, et al.
Trends in Plant Science (2023) Vol. 29, Iss. 2, pp. 130-149
Open Access | Times Cited: 26
Red fox optimization with ensemble recurrent neural network for crop recommendation and yield prediction model
P. S. S. Gopi, M. Karthikeyan
Multimedia Tools and Applications (2023) Vol. 83, Iss. 5, pp. 13159-13179
Closed Access | Times Cited: 24
Predicting and optimizing reactive oxygen species metabolism in Punica granatum L. through machine learning: role of exogenous GABA on antioxidant enzyme activity under drought and salinity stress
Saeedeh Zarbakhsh, Ali Reza Shahsavar, Ali Afaghi, et al.
BMC Plant Biology (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 11
Predicting Potato Crop Yield with Machine Learning and Deep Learning for Sustainable Agriculture
El-Sayed M. El-kenawy, Amel Ali Alhussan, Nima Khodadadi, et al.
Potato Research (2024)
Open Access | Times Cited: 10
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