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High-Throughput Phenotyping and Machine Learning for Plant Breeding

Dear Colleagues,

High-throughput phenotyping (HTP) of plants in field and controlled conditions has the potential to accelerate selection of genotypes with improved trait characteristics for plant breeding. Unmanned aerial vehicles, ground vehicles and hand-held sensors have shown tremendous potential for field phenotyping.High-throughput phenotyping facilities in controlled conditions can further accelerate germplasm characterization. Challenges remain in acquisition of the phenotypic data, data management, curation, analysis and sharing. This special issue on High-Throughput Phenotyping and Machine Learning for Plant Breeding aims to compile articles demonstrating the implementation of HTP in plant breeding. Both research and review articles are welcome.

Potential topics for the special issue:

  Implementation of HTP to improve genetic gain
  New advances in HTP methods
  Estimation of cost-efficiency of HTP
  New HTP methods for affordable phenotyping
  Deep learning approaches to identify and quantify key traits
  Application of machine learning for data integration
  New open source software for analysis of phenotypic data
  New databases for management and sharing of phenotypic data

Associate Professor Aakash Chawade

Guest Editor

Associate Professor Aakash Chawade

Department of Plant Breeding, Swedish University of Agricultural Sciences, SE-23053 Alnarp, Sweden


High-throughput phenotyping

Plant breeding

Genetic gain




Plant diseases

Submission Deadline: 15 September 2020

Online Submission

Manuscripts should be submitted online through Hapres Online Submission System. Please visit Guide for Authors before submitting a manuscript. Authors are encouraged to submit a paper as soon as it is ready and don’t need to wait until the deadline. Submissions will be sent to peer-review in order of arrival. Accepted papers will be published continuously in Crop Breeding, Genetics and Genomics (CBGG) and then gathered together on the special issue webpage. We welcome Research articles, Review papers and Short Communications. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for approval.


Virtual Special Issue (VSI) is a collection of papers centered around a specific topic, led by an expert (Guest Editor) in the field. Virtual Special Issues are an important component of our journal and cover current hot topics within the scope of the journal.

All papers belonging to a Virtual Special Issue will be gathered together on a single webpage. They are published in the regular issues of the journal as soon as publishable, and labeled as belonging to the Virtual Special Issue. A link from each paper will take you to the Virtual Special Issue website.

Submissions to Virtual Special Issues will undergo the same rigorous peer-review process as regular papers submitted to the journal.

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