Simulation of crop growth, time to maturity and yield by an improved sigmoidal model

Abstract Models that accurately estimate maximum crop biomass to obtain a reliable forecast of yield are useful in crop improvement programs and aiding establishment of government policies, including those addressing issues of food security. Here, we present a new sigmoidal growth model (NSG) and co...

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Autores principales:	Jun-He Liu, Yan Yan, Abid Ali, Ming-Fu Yu, Qi-Jie Xu, Pei-Jian Shi, Lei Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5c102d423cb3432283ebf73bece1db8f
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spelling	oai:doaj.org-article:5c102d423cb3432283ebf73bece1db8f2021-12-02T11:40:46ZSimulation of crop growth, time to maturity and yield by an improved sigmoidal model10.1038/s41598-018-24705-42045-2322https://doaj.org/article/5c102d423cb3432283ebf73bece1db8f2018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-24705-4https://doaj.org/toc/2045-2322Abstract Models that accurately estimate maximum crop biomass to obtain a reliable forecast of yield are useful in crop improvement programs and aiding establishment of government policies, including those addressing issues of food security. Here, we present a new sigmoidal growth model (NSG) and compare its performance with the beta sigmoidal growth model (BSG) for capturing the growth trajectories of eight crop species. Results indicated that both the NSG and the BSG fitted all the growth datasets well (R 2 > 0.98). However, the NSG performed better than the BSG based on the calculated value of Akaike’s information criterion (AIC). The NSG provided a consistent estimate for when maximum biomass occurred; this suggests that the parameters of the BSG may have less biological importance as compared to those in the NSG. In summary, the new sigmoidal growth model is superior to the beta sigmoidal growth model, which can be applied to capture the growth trajectory of various plant species regardless of the initial biomass values at the beginning of a growth period. Findings of this study will be helpful to understand the growth trajectory of different plant species regardless of their initial biomass values at the beginning of a growth period.Jun-He LiuYan YanAbid AliMing-Fu YuQi-Jie XuPei-Jian ShiLei ChenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-6 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jun-He Liu Yan Yan Abid Ali Ming-Fu Yu Qi-Jie Xu Pei-Jian Shi Lei Chen Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
description	Abstract Models that accurately estimate maximum crop biomass to obtain a reliable forecast of yield are useful in crop improvement programs and aiding establishment of government policies, including those addressing issues of food security. Here, we present a new sigmoidal growth model (NSG) and compare its performance with the beta sigmoidal growth model (BSG) for capturing the growth trajectories of eight crop species. Results indicated that both the NSG and the BSG fitted all the growth datasets well (R 2 > 0.98). However, the NSG performed better than the BSG based on the calculated value of Akaike’s information criterion (AIC). The NSG provided a consistent estimate for when maximum biomass occurred; this suggests that the parameters of the BSG may have less biological importance as compared to those in the NSG. In summary, the new sigmoidal growth model is superior to the beta sigmoidal growth model, which can be applied to capture the growth trajectory of various plant species regardless of the initial biomass values at the beginning of a growth period. Findings of this study will be helpful to understand the growth trajectory of different plant species regardless of their initial biomass values at the beginning of a growth period.
format	article
author	Jun-He Liu Yan Yan Abid Ali Ming-Fu Yu Qi-Jie Xu Pei-Jian Shi Lei Chen
author_facet	Jun-He Liu Yan Yan Abid Ali Ming-Fu Yu Qi-Jie Xu Pei-Jian Shi Lei Chen
author_sort	Jun-He Liu
title	Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
title_short	Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
title_full	Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
title_fullStr	Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
title_full_unstemmed	Simulation of crop growth, time to maturity and yield by an improved sigmoidal model
title_sort	simulation of crop growth, time to maturity and yield by an improved sigmoidal model
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/5c102d423cb3432283ebf73bece1db8f
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Simulation of crop growth, time to maturity and yield by an improved sigmoidal model

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