Author

Ji Zhou

Nanjing Agricultural UniversityORCID 0000-0002-5752-5524Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Ji Zhou3 papers · University of Connecticut

Biology Disciplines

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Bioinformatics· 2 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Assay:imaging· 3 Approach:deep learning· 2 Organism:Arabidopsis· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:experimental assay· 1

Frequent Co-Authors

Gang SuniD· 2 shared Jie ZhouiD· 2 shared Aaron George BostromiD· 1 shared Adela Gaja Jezierska-Suwinska· 1 shared Alan BaueriD· 1 shared Andrea Díaz-Tendero Bravo· 1 shared Anika DammiD· 1 shared Beatrice Senatori· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersPathology

Gang SunORCID

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Author profile →

3 papers

Recent·Most cited

3D printing and deep learning enable holistic and dynamic analyses of tens of thousands of parasites infecting hundreds of genotypes

Siyuan Wei, Jie Zhou, Olaf Prosper Kranse, Unnati Sonawala, Gang Sun, Ziyang He, Beatrice Senatori, Clément Pellegrin, Andrea Díaz-Tendero Bravo, Roberta Healey, Victor Hugo Moura de Souza, Vincent C. T. Hanlon, George Harpum, Tithira Wijayathilake, Adela Gaja Jezierska-Suwinska, , Sebastian Eves‐van den Akker

This study uses 3D printing and deep learning to analyze parasite dynamics across hundreds of plant genotypes, identifying host genetic control of parasite traits and new QTLs.

bioRxiv · Aug 18, 2026 · PreprintPathology

Large-scale field phenotyping using backpack LiDAR and GUI-based CropQuant-3D to measure structural responses to different nitrogen treatments in wheat

Yulei Zhu, Gang Sun, Guohui Ding, Jie Zhou, Mingxing Wen, Shichao Jin, Qiang Zhao, Joshua Colmer, Yanfeng Ding, Eric S. Ober, Ji Zhou

This paper introduces a backpack LiDAR and GUI-based software solution for large-scale wheat phenotyping, showing it can accurately measure crop traits and respond to nitrogen treatments.

PLANT PHYSIOLOGY · Jul 14, 2021Peer-reviewedBioinformatics

AirSurf-Lettuce: an aerial image analysis platform for ultra-scale field phenotyping and precision agriculture using computer vision and deep learning

Alan Bauer, Aaron George Bostrom, Joshua Ball, Christopher Applegate, Tao Cheng, Stephen D. Laycock, Sergio Moreno Rojas, Jacob Kirwan, Ji Zhou

AirSurf-Lettuce analyzes aerial images to measure lettuce phenotypes and support precision agriculture decisions.

bioRxiv · Jan 23, 2019 · PreprintBioinformatics