Assessment of Greenhouse Tomato Anthesis Rate Through Metabolomics Using LASSO Regularized Linear Regression Model

Assessment of Greenhouse Tomato Anthesis Rate Through Metabolomics Using LASSO Regularized Linear Regression Model

While the high year-round production of tomatoes has been facilitated by solar greenhouse cultivation, these yields readily fluctuate in response to changing environmental conditions. Mathematic modeling has been applied to forecast phenotypes of tomatoes using environmental measurements (e.g., temp...

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Bibliographic Details
Main Authors: Ratklao Siriwach, Jun Matsuzaki, Takeshi Saito, Hiroshi Nishimura, Masahide Isozaki, Yosuke Isoyama, Muneo Sato, Masanori Arita, Shotaro Akaho, Tadahisa Higashide, Kentaro Yano, Masami Yokota Hirai
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Molecular Biosciences
Subjects:
metabolome
metabolites
tomato
anthesis rate
machine learning
LASSO
Online Access:https://www.frontiersin.org/articles/10.3389/fmolb.2022.839051/full

Internet

https://www.frontiersin.org/articles/10.3389/fmolb.2022.839051/full

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