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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:

Prediction of Stem Water Potential in Olive Orchards Using High-Resolution Planet Satellite Images and Machine Learning Techniques
Simone Pietro Garofalo, Vincenzo Giannico, Leonardo Costanza, et al.
Agronomy (2023) Vol. 14, Iss. 1, pp. 1-1
Open Access | Times Cited: 17

Showing 17 citing articles:

Predicting carob tree physiological parameters under different irrigation systems using Random Forest and Planet satellite images
Simone Pietro Garofalo, Vincenzo Giannico, Beatriz Lorente, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 10
Continuous Plant-Based and Remote Sensing for Determination of Fruit Tree Water Status
Alessandro Carella, Pedro Tomás Bulacio Fischer, Roberto Massenti, et al.
Horticulturae (2024) Vol. 10, Iss. 5, pp. 516-516
Open Access | Times Cited: 9
Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence
Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, et al.
Agronomy (2025) Vol. 15, Iss. 1, pp. 241-241
Open Access | Times Cited: 1
A Machine Learning Approach to Monitor the Physiological and Water Status of an Irrigated Peach Orchard under Semi-Arid Conditions by Using Multispectral Satellite Data
Pasquale Campi, Anna Francesca Modugno, Gabriele De Carolis, et al.
Water (2024) Vol. 16, Iss. 16, pp. 2224-2224
Open Access | Times Cited: 7
Application of Unmanned Aerial Vehicle (UAV) Sensing for Water Status Estimation in Vineyards under Different Pruning Strategies
Juan Nowack, Luz Karime Atencia, Ana M. Tarquís, et al.
Plants (2024) Vol. 13, Iss. 10, pp. 1350-1350
Open Access | Times Cited: 5
Ecophysiological Recovery of Micropropagated Olive Cultivars: Field Research in an Irrigated Super-High-Density Orchard
Francesco Maldera, Simone Pietro Garofalo, Salvatore Camposeo
Agronomy (2024) Vol. 14, Iss. 7, pp. 1560-1560
Open Access | Times Cited: 5
Ecological optima show the potential diffusion of minor tree crops in Xylella fastidiosa subsp. pauca-infected areas through a GIS-based approach
Leonardo Costanza, Francesco Maldera, Simone Pietro Garofalo, et al.
Frontiers in Agronomy (2024) Vol. 6
Open Access | Times Cited: 4
A practical data-driven approach for precise stem water potential monitoring in pistachio and almond orchards using supervised machine learning algorithms
Mehrad Mortazavi, Stefano Carpin, Arash Toudeshki, et al.
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 110004-110004
Open Access
Advanced monitoring of almond orchard water status using machine learning and remote sensing
Srinivasa Rao Peddinti, Isaya Kisekka
Scientia Horticulturae (2025) Vol. 342, pp. 114020-114020
Open Access
Assessing the spatial-temporal performance of machine learning in predicting grapevine water status from Landsat 8 imagery via block-out and date-out cross-validation
Eve Laroche-Pinel, Vincenzo Cianciola, Khushwinder Singh, et al.
Agricultural Water Management (2024) Vol. 306, pp. 109163-109163
Open Access | Times Cited: 2
Explainable Artificial Intelligence to Predict the Water Status of Cotton (Gossypium hirsutum L., 1763) from Sentinel-2 Images in the Mediterranean Area
Simone Pietro Garofalo, Anna Francesca Modugno, Gabriele De Carolis, et al.
Plants (2024) Vol. 13, Iss. 23, pp. 3325-3325
Open Access | Times Cited: 2
Estimation of Intercepted Solar Radiation and Stem Water Potential in a Table Grape Vineyard Covered by Plastic Film Using Sentinel-2 Data: A Comparison of OLS-, MLR-, and ML-Based Methods
Alessandro Farbo, Nicola Gerardo Trombetta, L. de Palma, et al.
Plants (2024) Vol. 13, Iss. 9, pp. 1203-1203
Open Access | Times Cited: 1
Research on a Method for Estimating Potato Fraction Vegetation Coverage (FVC) Based on the Vegetation Index Intersection Method
Xiaoyi Shi, Huanbo Yang, Yiwen Chen, et al.
(2024)
Open Access
Research on Estimating Potato Fraction Vegetation Coverage (FVC) Based on the Vegetation Index Intersection Method
Xiaoyi Shi, Huanbo Yang, Yiwen Chen, et al.
Agronomy (2024) Vol. 14, Iss. 8, pp. 1620-1620
Open Access
First insights of cotton intercropping with peach trees under Mediterranean conditions
Gabriele De Carolis, Simone Pietro Garofalo, Nicola Sanitate, et al.
Agroforestry Systems (2024)
Closed Access
Physical Ripening Indices Improve the Assessment of Mechanical Harvesting Time for Olive Cultivars Resistant to Xylella fastidiosa subsp. pauca
Simone Pietro Garofalo, Francesco Maldera, Francesco Nicolì, et al.
Horticulturae (2024) Vol. 10, Iss. 10, pp. 1108-1108
Open Access
Harnessing Data-Driven Technologies for Sustainable Farming Practices
Sergio Vélez, Sara Álvarez
Agronomy (2024) Vol. 14, Iss. 12, pp. 2969-2969
Open Access
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