Crop Phenotyping Based on Artificial Intelligence Methods

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Plant Science".

Deadline for manuscript submissions: 29 February 2024 | Viewed by 317

Special Issue Editor

Dr. Rongsheng Zhu
E-Mail Website
Guest Editor
College of Arts and Sciences, Northeast Agricultural University, Harbin 150030, China
Interests: crop phenotyping; bioinformatics; deep learning; image processing

Special Issue Information

Dear Colleagues,

Crop phenomics, as one of the core key technologies in the development process from traditional agriculture to smart agriculture, has been increasingly emphasized by the majority of agricultural scientists. With the rapid development of artificial intelligence technology represented by deep learning, the development of crop phenomics technology has been greatly promoted. This Special Issue, titled "Crop Phenotyping Based on Artificial Intelligence Methods", will focus on the solution of new problems in crop phenomics, the proposal of new methods and technologies for phenotyping, and the release of new platforms for phenotyping and analyzing driven by AI technology. This Special Issue will focus on the above topics, but its content is not limited to these topics, as the study of the pattern of change of crop phenotypes, the genetic analysis of phenotypic changes, and the study of functional phenotypes of crops, etc., will also be covered.

Dr. Rongsheng Zhu
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • crop phenomics
  • image processing
  • deep learning
  • machine learning
  • agronomy traits
  • UAV
  • growth and development period
  • biotic and abiotic stresses
  • IoT
  • physiological phenotype

Published Papers

This special issue is now open for submission.
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