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Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation


Akiyama, Reiko; Goto, Takao; Tameshige, Toshiaki; Sugisaka, Jiro; Kuroki, Ken; Sun, Jianqiang; Akita, Junichi; Hatakeyama, Masaomi; Kudoh, Hiroshi; Kenta, Tanaka; Tonouchi, Aya; Shimahara, Yuki; Sese, Jun; Kutsuna, Natsumaro; Shimizu-Inatsugi, Rie; Shimizu, Kentaro K (2023). Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation. Nature Communications, 14(1):5792.

Abstract

Long-term field monitoring of leaf pigment content is informative for understanding plant responses to environments distinct from regulated chambers but is impractical by conventional destructive measurements. We developed PlantServation, a method incorporating robust image-acquisition hardware and deep learning-based software that extracts leaf color by detecting plant individuals automatically. As a case study, we applied PlantServation to examine environmental and genotypic effects on the pigment anthocyanin content estimated from leaf color. We processed >4 million images of small individuals of four Arabidopsis species in the field, where the plant shape, color, and background vary over months. Past radiation, coldness, and precipitation significantly affected the anthocyanin content. The synthetic allopolyploid A. kamchatica recapitulated the fluctuations of natural polyploids by integrating diploid responses. The data support a long-standing hypothesis stating that allopolyploids can inherit and combine the traits of progenitors. PlantServation facilitates the study of plant responses to complex environments termed "in natura".

Abstract

Long-term field monitoring of leaf pigment content is informative for understanding plant responses to environments distinct from regulated chambers but is impractical by conventional destructive measurements. We developed PlantServation, a method incorporating robust image-acquisition hardware and deep learning-based software that extracts leaf color by detecting plant individuals automatically. As a case study, we applied PlantServation to examine environmental and genotypic effects on the pigment anthocyanin content estimated from leaf color. We processed >4 million images of small individuals of four Arabidopsis species in the field, where the plant shape, color, and background vary over months. Past radiation, coldness, and precipitation significantly affected the anthocyanin content. The synthetic allopolyploid A. kamchatica recapitulated the fluctuations of natural polyploids by integrating diploid responses. The data support a long-standing hypothesis stating that allopolyploids can inherit and combine the traits of progenitors. PlantServation facilitates the study of plant responses to complex environments termed "in natura".

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Functional Genomics Center Zurich
07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
08 Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:590 Animals (Zoology)
570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > General Chemistry
Life Sciences > General Biochemistry, Genetics and Molecular Biology
Physical Sciences > General Physics and Astronomy
Language:English
Date:22 September 2023
Deposited On:10 Oct 2023 15:16
Last Modified:29 Jun 2024 01:39
Publisher:Nature Publishing Group
ISSN:2041-1723
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/s41467-023-41260-3
PubMed ID:37737204
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)
  • Content: Supplemental Material
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)