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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:

Integration of Genomics with Crop Modeling for Predicting Rice Days to Flowering: A Multi-Model Analysis
Yubin Yang, Lloyd T. Wilson, Tao Li, et al.
Field Crops Research (2021) Vol. 276, pp. 108394-108394
Open Access | Times Cited: 11

Showing 11 citing articles:

Climate change may outpace current wheat breeding yield improvements in North America
Tianyi Zhang, Yong He, R. M. DePauw, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 41
Integrating crop models, single nucleotide polymorphism, and climatic indices to develop genotype-environment interaction model: A case study on rice flowering time
Jinhan Zhang, Shaoyuan Zhang, Yubin Yang, et al.
Plant Phenomics (2025), pp. 100007-100007
Open Access
Harnessing crop models and machine learning for a spatial-temporal characterization of irrigated rice breeding environments in Brazil
Alexandre Bryan Heinemann, Germano Costa‐Neto, David Henriques da Matta, et al.
Field Crops Research (2024) Vol. 315, pp. 109452-109452
Closed Access | Times Cited: 4
Heritage genetics for adaptation to marginal soils in barley
Sidsel Birkelund Schmidt, Lawrie K. Brown, Allan Booth, et al.
Trends in Plant Science (2023) Vol. 28, Iss. 5, pp. 544-551
Open Access | Times Cited: 8
Simulating the effects of low-temperature stress during flowering stage on leaf-level photosynthesis with current rice models
Min Kang, Siyuan Wang, Zhenkai Xu, et al.
Agricultural and Forest Meteorology (2024) Vol. 354, pp. 110087-110087
Closed Access | Times Cited: 2
Dual ensemble approach to predict rice heading date by integrating multiple rice phenology models and machine learning-based genetic parameter regression models
Satoshi Kawakita, Masanori Yamasaki, Ryo Teratani, et al.
Agricultural and Forest Meteorology (2023) Vol. 344, pp. 109821-109821
Closed Access | Times Cited: 4
Redefining the accumulated temperature index for accurate prediction of rice flowering time in diverse environments
Xingbing Xu, Qiong Jia, Sijia Li, et al.
Plant Biotechnology Journal (2024)
Open Access
Variability in Estimating Crop Model Genotypic Parameters: The Impact of Different Sampling Methods and Sizes
Xintian Ma, Xiangyi Wang, Yingbin He, et al.
Agriculture (2023) Vol. 13, Iss. 12, pp. 2207-2207
Open Access | Times Cited: 1
Performance evaluation of the ORYZA_V3 model for rice growth and organ nitrogen content
Jin Yu, Zhipeng Ren, Honghu Li, et al.
Agronomy Journal (2023) Vol. 115, Iss. 6, pp. 2938-2949
Closed Access
Genetic analysis of genotype-specific parameters in the DSSTA-CROPGRO-soybean phenology simulation model via a multi-GWAS method
Wenliang Yan, Haiyan Jiang, Junjie Xu, et al.
Field Crops Research (2023) Vol. 304, pp. 109165-109165
Closed Access
Calibration and Multiple-Parameter Optimization of the Hybrid-Maize Model for Improve Simulation of Soil Moisture and Grain Yield in Farmer's Fields
Anthony Amori, Olufemi Abimbola, Trenton E. Franz, et al.
SSRN Electronic Journal (2022)
Closed Access
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