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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:

Predicting spatial patterns of within-field crop yield variability
Bernardo Maestrini, Bruno Basso
Field Crops Research (2018) Vol. 219, pp. 106-112
Open Access | Times Cited: 104

Showing 1-25 of 104 citing articles:

Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques
Ahmed Kayad, Marco Sozzi, Simone Gatto, et al.
Remote Sensing (2019) Vol. 11, Iss. 23, pp. 2873-2873
Open Access | Times Cited: 134
Yield stability analysis reveals sources of large-scale nitrogen loss from the US Midwest
Bruno Basso, Guanyuan Shuai, Jinshui Zhang, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 109
Drivers of within-field spatial and temporal variability of crop yield across the US Midwest
Bernardo Maestrini, Bruno Basso
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 107
Using NDVI for the assessment of canopy cover in agricultural crops within modelling research
Tomás R. Tenreiro, Margarita García‐Vila, José A. Gómez, et al.
Computers and Electronics in Agriculture (2021) Vol. 182, pp. 106038-106038
Open Access | Times Cited: 83
Redefining marginal land for bioenergy crop production
Madhu Khanna, Luoye Chen, Bruno Basso, et al.
GCB Bioenergy (2021) Vol. 13, Iss. 10, pp. 1590-1609
Open Access | Times Cited: 82
The Digital Agricultural Revolution: A Bibliometric Analysis Literature Review
Riccardo Bertoglio, Chiara Corbo, Filippo Renga, et al.
IEEE Access (2021) Vol. 9, pp. 134762-134782
Open Access | Times Cited: 75
Subfield maize yield prediction improves when in-season crop water deficit is included in remote sensing imagery-based models
Guanyuan Shuai, Bruno Basso
Remote Sensing of Environment (2022) Vol. 272, pp. 112938-112938
Open Access | Times Cited: 46
Identifying Advantages and Disadvantages of Variable Rate Irrigation: An Updated Review
Susan A. O’Shaughnessy, Steven R. Evett, Paul D. Colaizzi, et al.
Applied Engineering in Agriculture (2019) Vol. 35, Iss. 6, pp. 837-852
Open Access | Times Cited: 70
Unstable crop yields reveal opportunities for site-specific adaptations to climate variability
Rafael A. Martinez‐Feria, Bruno Basso
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 63
Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision
Sherrie Wang, François Waldner, David B. Lobell
Remote Sensing (2022) Vol. 14, Iss. 22, pp. 5738-5738
Open Access | Times Cited: 36
Dynamic Maize Yield Predictions Using Machine Learning on Multi-Source Data
Michele Croci, Giorgio Impollonia, Michele Meroni, et al.
Remote Sensing (2022) Vol. 15, Iss. 1, pp. 100-100
Open Access | Times Cited: 31
Time Series from Sentinel-2 for Organic Durum Wheat Yield Prediction Using Functional Data Analysis and Deep Learning
Adriano Mancini, Francesco Solfanelli, Luca Coviello, et al.
Agronomy (2024) Vol. 14, Iss. 1, pp. 109-109
Open Access | Times Cited: 6
Re-designing organic grain legume cropping systems using systems agronomy
Moritz Reckling, Göran Bergkvist, Christine Watson, et al.
European Journal of Agronomy (2019) Vol. 112, pp. 125951-125951
Open Access | Times Cited: 50
Using a Crop Modeling Framework for Precision Cost-Benefit Analysis of Variable Seeding and Nitrogen Application Rates
Gabriel Sean McNunn, Emily A. Heaton, Sotirios V. Archontoulis, et al.
Frontiers in Sustainable Food Systems (2019) Vol. 3
Open Access | Times Cited: 43
Modeling spatial and temporal optimal N fertilizer rates to reduce nitrate leaching while improving grain yield and quality in malting barley
Davide Cammarano, Bruno Basso, Jonathan E. Holland, et al.
Computers and Electronics in Agriculture (2021) Vol. 182, pp. 105997-105997
Closed Access | Times Cited: 35
Optimizing N applications increases maize yield and reduces environmental costs in a 12-year wheat-maize system
Shuaijie Shen, Biao Feng, Datong Zhang, et al.
Field Crops Research (2025) Vol. 322, pp. 109741-109741
Closed Access
A brief history of remote sensing of soybean
Joby M. Prince Czarnecki, Sathishkumar Samiappan, Raju Bheemanahalli, et al.
Agronomy Journal (2025) Vol. 117, Iss. 1
Open Access
Remote Sensor Images and Vegetation Indices to Optimize Rice Yield Analysis for Specific Growth Stages Within Extensive Data
David Fita, Constanza Rubio, Antonio Uris, et al.
Applied Sciences (2025) Vol. 15, Iss. 7, pp. 3870-3870
Open Access
Workflow to Establish Time-Specific Zones in Precision Agriculture by Spatiotemporal Integration of Plant and Soil Sensing Data
Elia Scudiero, Pietro Teatini, Gabriele Manoli, et al.
Agronomy (2018) Vol. 8, Iss. 11, pp. 253-253
Open Access | Times Cited: 42
How much will precision nitrogen management pay off? An evaluation based on simulating thousands of corn fields over the US Corn-Belt
Zhenong Jin, Sotirios V. Archontoulis, David B. Lobell
Field Crops Research (2019) Vol. 240, pp. 12-22
Closed Access | Times Cited: 37
Soybean Yield Estimation and Its Components: A Linear Regression Approach
Marcelo Chan Fu Wei, José Paulo Molin
Agriculture (2020) Vol. 10, Iss. 8, pp. 348-348
Open Access | Times Cited: 36
Cotton Yield Estimate Using Sentinel-2 Data and an Ecosystem Model over the Southern US
Liming He, G. Mostovoy
Remote Sensing (2019) Vol. 11, Iss. 17, pp. 2000-2000
Open Access | Times Cited: 35
Strip-Till One-Pass Technology in Central and Eastern Europe: A MZURI Pro-Til Hybrid Machine Case Study
Iwona Jaskulska, Dariusz Jaskulski
Agronomy (2020) Vol. 10, Iss. 7, pp. 925-925
Open Access | Times Cited: 34
Agricultural drought severity in NE Italy: Variability, bias, and future scenarios
Giulia Sofia, Claudio Zaccone, Paolo Tarolli
International Soil and Water Conservation Research (2023) Vol. 12, Iss. 2, pp. 403-418
Open Access | Times Cited: 11
Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm
Changwei Tan, Xinxing Zhou, Pengpeng Zhang, et al.
PLoS ONE (2020) Vol. 15, Iss. 3, pp. e0228500-e0228500
Open Access | Times Cited: 27
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