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Soybean-BioCro: a semi-mechanistic model of soybean growth

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Soybean-BioCro: a semi-mechanistic model of soybean growth. / Matthews, Megan L; Marshall-Colón, Amy; McGrath, Justin M et al.
In: in silico Plants, Vol. 4, No. 1, diab032, 28.02.2022, p. 1-11.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Matthews, ML, Marshall-Colón, A, McGrath, JM, Lochocki, EB & Long, SP 2022, 'Soybean-BioCro: a semi-mechanistic model of soybean growth', in silico Plants, vol. 4, no. 1, diab032, pp. 1-11. https://doi.org/10.1093/insilicoplants/diab032

APA

Matthews, M. L., Marshall-Colón, A., McGrath, J. M., Lochocki, E. B., & Long, S. P. (2022). Soybean-BioCro: a semi-mechanistic model of soybean growth. in silico Plants, 4(1), 1-11. Article diab032. https://doi.org/10.1093/insilicoplants/diab032

Vancouver

Matthews ML, Marshall-Colón A, McGrath JM, Lochocki EB, Long SP. Soybean-BioCro: a semi-mechanistic model of soybean growth. in silico Plants. 2022 Feb 28;4(1):1-11. diab032. Epub 2021 Dec 5. doi: 10.1093/insilicoplants/diab032

Author

Matthews, Megan L ; Marshall-Colón, Amy ; McGrath, Justin M et al. / Soybean-BioCro : a semi-mechanistic model of soybean growth. In: in silico Plants. 2022 ; Vol. 4, No. 1. pp. 1-11.

Bibtex

@article{dcb5be1a3f35442f947cb205b8567d09,
title = "Soybean-BioCro: a semi-mechanistic model of soybean growth",
abstract = "Abstract Soybean is a major global source of protein and oil. Understanding how soybean crops will respond to the changing climate and identifying the responsible molecular machinery are important for facilitating bioengineering and breeding to meet the growing global food demand. The BioCro family of crop models are semi-mechanistic models scaling from biochemistry to whole crop growth and yield. BioCro was previously parameterized and proved effective for the biomass crops Miscanthus, coppice willow and Brazilian sugarcane. Here, we present Soybean-BioCro, the first food crop to be parameterized for BioCro. Two new module sets were incorporated into the BioCro framework describing the rate of soybean development and carbon partitioning and senescence. The model was parameterized using field measurements collected over the 2002 and 2005 growing seasons at the open air [CO2] enrichment (SoyFACE) facility under ambient atmospheric [CO2]. We demonstrate that Soybean-BioCro successfully predicted how elevated [CO2] impacted field-grown soybean growth without a need for re-parameterization, by predicting soybean growth under elevated atmospheric [CO2] during the 2002 and 2005 growing seasons, and under both ambient and elevated [CO2] for the 2004 and 2006 growing seasons. Soybean-BioCro provides a useful foundational framework for incorporating additional primary and secondary metabolic processes or gene regulatory mechanisms that can further aid our understanding of how future soybean growth will be impacted by climate change.",
keywords = "Plant Science, Agronomy and Crop Science, Biochemistry, Genetics and Molecular Biology (miscellaneous), Modeling and Simulation",
author = "Matthews, {Megan L} and Amy Marshall-Col{\'o}n and McGrath, {Justin M} and Lochocki, {Edward B} and Long, {Stephen P}",
year = "2022",
month = feb,
day = "28",
doi = "10.1093/insilicoplants/diab032",
language = "English",
volume = "4",
pages = "1--11",
journal = "in silico Plants",
issn = "2517-5025",
publisher = "Oxford University Press (OUP)",
number = "1",

}

RIS

TY - JOUR

T1 - Soybean-BioCro

T2 - a semi-mechanistic model of soybean growth

AU - Matthews, Megan L

AU - Marshall-Colón, Amy

AU - McGrath, Justin M

AU - Lochocki, Edward B

AU - Long, Stephen P

PY - 2022/2/28

Y1 - 2022/2/28

N2 - Abstract Soybean is a major global source of protein and oil. Understanding how soybean crops will respond to the changing climate and identifying the responsible molecular machinery are important for facilitating bioengineering and breeding to meet the growing global food demand. The BioCro family of crop models are semi-mechanistic models scaling from biochemistry to whole crop growth and yield. BioCro was previously parameterized and proved effective for the biomass crops Miscanthus, coppice willow and Brazilian sugarcane. Here, we present Soybean-BioCro, the first food crop to be parameterized for BioCro. Two new module sets were incorporated into the BioCro framework describing the rate of soybean development and carbon partitioning and senescence. The model was parameterized using field measurements collected over the 2002 and 2005 growing seasons at the open air [CO2] enrichment (SoyFACE) facility under ambient atmospheric [CO2]. We demonstrate that Soybean-BioCro successfully predicted how elevated [CO2] impacted field-grown soybean growth without a need for re-parameterization, by predicting soybean growth under elevated atmospheric [CO2] during the 2002 and 2005 growing seasons, and under both ambient and elevated [CO2] for the 2004 and 2006 growing seasons. Soybean-BioCro provides a useful foundational framework for incorporating additional primary and secondary metabolic processes or gene regulatory mechanisms that can further aid our understanding of how future soybean growth will be impacted by climate change.

AB - Abstract Soybean is a major global source of protein and oil. Understanding how soybean crops will respond to the changing climate and identifying the responsible molecular machinery are important for facilitating bioengineering and breeding to meet the growing global food demand. The BioCro family of crop models are semi-mechanistic models scaling from biochemistry to whole crop growth and yield. BioCro was previously parameterized and proved effective for the biomass crops Miscanthus, coppice willow and Brazilian sugarcane. Here, we present Soybean-BioCro, the first food crop to be parameterized for BioCro. Two new module sets were incorporated into the BioCro framework describing the rate of soybean development and carbon partitioning and senescence. The model was parameterized using field measurements collected over the 2002 and 2005 growing seasons at the open air [CO2] enrichment (SoyFACE) facility under ambient atmospheric [CO2]. We demonstrate that Soybean-BioCro successfully predicted how elevated [CO2] impacted field-grown soybean growth without a need for re-parameterization, by predicting soybean growth under elevated atmospheric [CO2] during the 2002 and 2005 growing seasons, and under both ambient and elevated [CO2] for the 2004 and 2006 growing seasons. Soybean-BioCro provides a useful foundational framework for incorporating additional primary and secondary metabolic processes or gene regulatory mechanisms that can further aid our understanding of how future soybean growth will be impacted by climate change.

KW - Plant Science

KW - Agronomy and Crop Science

KW - Biochemistry, Genetics and Molecular Biology (miscellaneous)

KW - Modeling and Simulation

U2 - 10.1093/insilicoplants/diab032

DO - 10.1093/insilicoplants/diab032

M3 - Journal article

VL - 4

SP - 1

EP - 11

JO - in silico Plants

JF - in silico Plants

SN - 2517-5025

IS - 1

M1 - diab032

ER -