SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination-Reference-Cited by-同舟云学术

SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination

Published:2020-07-17 Issue:2 Volume:228 Page:778-793
ISSN:0028-646X
Container-title:New Phytologist
language:en
Short-container-title:New Phytol

Author:

Colmer Joshua¹^ORCID,O'Neill Carmel M.²,Wells Rachel²^ORCID,Bostrom Aaron¹^ORCID,Reynolds Daniel¹^ORCID,Websdale Danny¹,Shiralagi Gagan²,Lu Wei³,Lou Qiaojun⁴,Le Cornu Thomas¹,Ball Joshua¹^ORCID,Renema Jim⁵,Flores Andaluz Gema⁵,Benjamins Rene⁵,Penfield Steven²^ORCID,Zhou Ji⁶⁷^ORCID

Affiliation:

1. Engineering biology Earlham Institute Norwich Research Park NorwichNR4 7UZ UK

2. Crop Genetics John Innes Centre Norwich Research Park NorwichNR4 7UH UK

3. College of Engineering Nanjing Agricultural University NanjingJiangsu210095 China

4. Shanghai Agrobiological Gene Center Shanghai Academy of Agricultural Sciences Shanghai201106 China

5. Syngenta Seeds BV Enkhuizen1601 BK the Netherlands

6. State Key Laboratory of Crop Genetics & Germplasm Enhancement Plant Phenomics Research Center Jiangsu Collaborative Innovation Center for Modern Crop Production co‐sponsored by Province and Ministry Nanjing Agricultural University Nanjing210095 China

7. Cambridge Crop Research National Institute of Agricultural Botany CambridgeCB3 0LE UK

Funder

Biotechnology and Biological Sciences Research Council

Syngenta International

Publisher

Wiley

Subject

Plant Science,Physiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/nph.16736

Reference72 articles.

1. Maintaining dryness during storage contributes to higher maize seed quality