Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

The effects of climate extremes on global agricultural yields
Elisabeth Vogel, Markus G. Donat, Lisa V. Alexander, et al.
Environmental Research Letters (2019) Vol. 14, Iss. 5, pp. 054010-054010
Open Access | Times Cited: 615

Showing 1-25 of 615 citing articles:

Impact of extreme weather conditions on European crop production in 2018
Damien Beillouin, Bernhard Schauberger, Ana Bastos, et al.
Philosophical Transactions of the Royal Society B Biological Sciences (2020) Vol. 375, Iss. 1810, pp. 20190510-20190510
Open Access | Times Cited: 331
Seed germination and vigor: ensuring crop sustainability in a changing climate
R. Reed, Kent J. Bradford, Imtiyaz Khanday
Heredity (2022) Vol. 128, Iss. 6, pp. 450-459
Open Access | Times Cited: 251
Severity of drought and heatwave crop losses tripled over the last five decades in Europe
Teresa Bras, Júlia Seixas, Nuno Carvalhais, et al.
Environmental Research Letters (2021) Vol. 16, Iss. 6, pp. 065012-065012
Open Access | Times Cited: 230
Compound heat and moisture extreme impacts on global crop yields under climate change
Corey Lesk, Weston Anderson, A. J. Rigden, et al.
Nature Reviews Earth & Environment (2022) Vol. 3, Iss. 12, pp. 872-889
Closed Access | Times Cited: 206
Stronger temperature–moisture couplings exacerbate the impact of climate warming on global crop yields
Corey Lesk, Ethan Coffel, Jonathan M. Winter, et al.
Nature Food (2021) Vol. 2, Iss. 9, pp. 683-691
Closed Access | Times Cited: 200
Global food self-sufficiency in the 21st century under sustainable intensification of agriculture
Areidy Beltran‐Peña, Lorenzo Rosa, Paolo D’Odorico
Environmental Research Letters (2020) Vol. 15, Iss. 9, pp. 095004-095004
Open Access | Times Cited: 192
Abiotic Stress in Crop Production
Romana Kopecká, Michaela Kameniarová, Martin Černý, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 7, pp. 6603-6603
Open Access | Times Cited: 151
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
Adapting agriculture to climate change via sustainable irrigation: biophysical potentials and feedbacks
Lorenzo Rosa
Environmental Research Letters (2022) Vol. 17, Iss. 6, pp. 063008-063008
Open Access | Times Cited: 114
Modern plant biotechnology as a strategy in addressing climate change and attaining food security
T. I. K. Munaweera, Nadeeka U. Jayawardana, Rathiverni Rajaratnam, et al.
Agriculture & Food Security (2022) Vol. 11, Iss. 1
Open Access | Times Cited: 112
Climate change and future of agri-food production
Lalit Kumar, Ngawang Chhogyel, Tharani Gopalakrishnan, et al.
Elsevier eBooks (2022), pp. 49-79
Closed Access | Times Cited: 105
Engineering plants with carbon nanotubes: a sustainable agriculture approach
Mahpara Safdar, Woochan Kim, Sunho Park, et al.
Journal of Nanobiotechnology (2022) Vol. 20, Iss. 1
Open Access | Times Cited: 101
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
Extreme rainfall reduces one-twelfth of China’s rice yield over the last two decades
Jin Fu, Yiwei Jian, Xuhui Wang, et al.
Nature Food (2023) Vol. 4, Iss. 5, pp. 416-426
Closed Access | Times Cited: 94
The negative impact of increasing temperatures on rice yields in southern China
Yanling Song, Chunyi Wang, Hans W. Linderholm, et al.
The Science of The Total Environment (2022) Vol. 820, pp. 153262-153262
Open Access | Times Cited: 82
Increased probability of hot and dry weather extremes during the growing season threatens global crop yields
Matias Heino, Pekka Kinnunen, Weston Anderson, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 67
Evidence of human influence on Northern Hemisphere snow loss
Alexander R. Gottlieb, Justin Mankin
Nature (2024) Vol. 625, Iss. 7994, pp. 293-300
Open Access | Times Cited: 46
Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models
Guoyong Leng, Jim W. Hall
Environmental Research Letters (2020) Vol. 15, Iss. 4, pp. 044027-044027
Open Access | Times Cited: 128
Quantifying irrigation cooling benefits to maize yield in the US Midwest
Yan Li, Kaiyu Guan, Bin Peng, et al.
Global Change Biology (2020) Vol. 26, Iss. 5, pp. 3065-3078
Closed Access | Times Cited: 93
Use of Mineral Weathering Bacteria to Enhance Nutrient Availability in Crops: A Review
Igor Daniel Alves Ribeiro, Camila Gazolla Volpiano, Luciano Kayser Vargas, et al.
Frontiers in Plant Science (2020) Vol. 11
Open Access | Times Cited: 86
Net benefits to US soy and maize yields from intensifying hourly rainfall
Corey Lesk, Ethan Coffel, Radley Horton
Nature Climate Change (2020) Vol. 10, Iss. 9, pp. 819-822
Closed Access | Times Cited: 75
Drivers of Summer Extreme Precipitation Events Over East China
Yong Tang, Anning Huang, Peili Wu, et al.
Geophysical Research Letters (2021) Vol. 48, Iss. 11
Closed Access | Times Cited: 72
Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation – a modeling analysis
Xiangyu Luan, Giulia Vico
Hydrology and earth system sciences (2021) Vol. 25, Iss. 3, pp. 1411-1423
Open Access | Times Cited: 70
Machine learning in crop yield modelling: A powerful tool, but no surrogate for science
Gunnar Lischeid, Heidi Webber, Michael Sommer, et al.
Agricultural and Forest Meteorology (2021) Vol. 312, pp. 108698-108698
Open Access | Times Cited: 69
Complex drought patterns robustly explain global yield loss for major crops
Monia Santini, Sergio Noce, Marta Antonelli, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 68
Page 1 - Next Page

Scroll to top