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:

How well do crop modeling groups predict wheat phenology, given calibration data from the target population?
Daniel Wallach, Taru Palosuo, Peter J. Thorburn, et al.
European Journal of Agronomy (2021) Vol. 124, pp. 126195-126195
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise
Daniel Wallach, Taru Palosuo, Peter J. Thorburn, et al.
Environmental Modelling & Software (2021) Vol. 145, pp. 105206-105206
Open Access | Times Cited: 71
A calibration protocol for soil-crop models
Daniel Wallach, Samuel Buis, Diana-Maria Seserman, et al.
Environmental Modelling & Software (2024) Vol. 180, pp. 106147-106147
Open Access | Times Cited: 9
Evaluating the AgMIP calibration protocol for crop models; case study and new diagnostic tests
Daniel Wallach, Kwang Soo Kim, Shinwoo Hyun, et al.
European Journal of Agronomy (2025) Vol. 168, pp. 127659-127659
Open Access | Times Cited: 1
Mixing process-based and data-driven approaches in yield prediction
Bernardo Maestrini, Gordan Mimić, P.A.J. van Oort, et al.
European Journal of Agronomy (2022) Vol. 139, pp. 126569-126569
Open Access | Times Cited: 37
Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework
Yongfa You, Hanqin Tian, Shufen Pan, et al.
Agricultural and Forest Meteorology (2022) Vol. 325, pp. 109144-109144
Open Access | Times Cited: 30
Proposal and extensive test of a calibration protocol for crop phenology models
Daniel Wallach, Taru Palosuo, Peter J. Thorburn, et al.
Agronomy for Sustainable Development (2023) Vol. 43, Iss. 4
Open Access | Times Cited: 18
The optimization of model ensemble composition and size can enhance the robustness of crop yield projections
Linchao Li, Bin Wang, Puyu Feng, et al.
Communications Earth & Environment (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 17
Same soil, different climate: Crop model intercomparison on translocated lysimeters
Jannis Groh, Efstathios Diamantopoulos, Xiaohong Duan, et al.
Vadose Zone Journal (2022) Vol. 21, Iss. 4
Open Access | Times Cited: 22
Impacts of land use, climate change and hydrological model structure on nitrate fluxes: Magnitudes and uncertainties
Ida Karlsson Seidenfaden, Torben O. Sonnenborg, Christen Duus Børgesen, et al.
The Science of The Total Environment (2022) Vol. 830, pp. 154671-154671
Closed Access | Times Cited: 21
Enhancing crop model parameter estimation across computing environments: Utilizing the GLUE method and parallel computing for determining genetic coefficients
Thiago Berton Ferreira, Vakhtang Shelia, Cheryl Porter, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109513-109513
Closed Access | Times Cited: 4
A comparison of multiple calibration and ensembling methods for estimating genetic coefficients of CERES-Rice to simulate phenology and yields
Prakash Kumar Jha, Amor V.M. Ines, Eunjin Han, et al.
Field Crops Research (2022) Vol. 284, pp. 108560-108560
Open Access | Times Cited: 17
Remote Monitoring of Crop Nitrogen Nutrition to Adjust Crop Models: A Review
Luís Silva, Luís Alcino Conceição, Fernando Cebola Lidon, et al.
Agriculture (2023) Vol. 13, Iss. 4, pp. 835-835
Open Access | Times Cited: 10
Dire need for quantification of environmental impacts associated with breeding climate-resilient crops
Chunhu Wang, Matthew Tom Harrison, De Li Liu, et al.
Agricultural Systems (2025) Vol. 227, pp. 104352-104352
Open Access
Multi-model evaluation of phenology prediction for wheat in Australia
Daniel Wallach, Taru Palosuo, Peter J. Thorburn, et al.
Agricultural and Forest Meteorology (2021) Vol. 298-299, pp. 108289-108289
Open Access | Times Cited: 23
Evaluating differences among crop models in simulating soybean in-season growth
Kritika Kothari, Rafael Battisti, Kenneth J. Boote, et al.
Field Crops Research (2024) Vol. 309, pp. 109306-109306
Closed Access | Times Cited: 3
Overcoming mechanistic limitations of process-based phenological models: A data clustering method for large-scale applications
Jiaojiao Tan, Gang Zhao, Qi Tian, et al.
Agricultural and Forest Meteorology (2024) Vol. 356, pp. 110167-110167
Closed Access | Times Cited: 3
The urgency for investment on local data for advancing food assessments in Africa: A review case study for APSIM crop modeling
Ana Julia Paula Carcedo, Nilson Aparecido Vieira, Lucia Marziotte, et al.
Environmental Modelling & Software (2023) Vol. 161, pp. 105633-105633
Open Access | Times Cited: 8
Using Satellite Data to Optimize Wheat Yield and Quality under Climate Change
Shilo Shiff, Itamar M. Lensky, David J. Bonfil
Remote Sensing (2021) Vol. 13, Iss. 11, pp. 2049-2049
Open Access | Times Cited: 18
The Impact of Global Warming on the Winter Wheat Production of China
Yu Zhang, Xiaolei Qiu, Tingwei Yin, et al.
Agronomy (2021) Vol. 11, Iss. 9, pp. 1845-1845
Open Access | Times Cited: 15
Regional uncertainty analysis between crop phenology model structures and optimal parameters
Chenyao Yang, Na Lei, Christoph Menz, et al.
Agricultural and Forest Meteorology (2024) Vol. 355, pp. 110137-110137
Open Access | Times Cited: 2
Bayesian multi-level calibration of a process-based maize phenology model
Michelle Viswanathan, Andreas Scheidegger, Thilo Streck, et al.
Ecological Modelling (2022) Vol. 474, pp. 110154-110154
Open Access | Times Cited: 10
Simultaneous Calibration of Grapevine Phenology and Yield with a Soil–Plant–Atmosphere System Model Using the Frequentist Method
Chenyao Yang, Christoph Menz, Hélder Fraga, et al.
Agronomy (2021) Vol. 11, Iss. 8, pp. 1659-1659
Open Access | Times Cited: 13
Selection for yield over five decades favored anisohydric and phenological adaptations to early-season drought in Australian wheat
Faisal Khan, Yupeng Feng, Jairo A. Palta, et al.
Plant and Soil (2022) Vol. 476, Iss. 1-2, pp. 511-526
Closed Access | Times Cited: 9
Performance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties
Chenyao Yang, Andrej Ceglar, Christoph Menz, et al.
Agricultural and Forest Meteorology (2023) Vol. 331, pp. 109342-109342
Open Access | Times Cited: 5
Integrating Field Data and a Modeling Approach to Inform Optimum Planting Date × Maturity Group for Soybeans under Current and Future Weather Conditions in Kansas
Emmanuela van Versendaal, Ana Julia Paula Carcedo, Eric Adee, et al.
Sustainability (2023) Vol. 15, Iss. 2, pp. 1081-1081
Open Access | Times Cited: 4
Page 1 - Next Page

Scroll to top