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Mixed Models as a Tool for Comparing Groups of Time Series in Plant Sciences

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F21%3A00119682" target="_blank" >RIV/00216224:14740/21:00119682 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/60646594:_____/21:N0000008

  • Výsledek na webu

    <a href="https://www.mdpi.com/2223-7747/10/2/362" target="_blank" >https://www.mdpi.com/2223-7747/10/2/362</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/plants10020362" target="_blank" >10.3390/plants10020362</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Mixed Models as a Tool for Comparing Groups of Time Series in Plant Sciences

  • Popis výsledku v původním jazyce

    Plants adapt to continual changes in environmental conditions throughout their life spans. High-throughput phenotyping methods have been developed to noninvasively monitor the physiological responses to abiotic/biotic stresses on a scale spanning a long time, covering most of the vegetative and reproductive stages. However, some of the physiological events comprise almost immediate and very fast responses towards the changing environment which might be overlooked in long-term observations. Additionally, there are certain technical difficulties and restrictions in analyzing phenotyping data, especially when dealing with repeated measurements. In this study, a method for comparing means at different time points using generalized linear mixed models combined with classical time series models is presented. As an example, we use multiple chlorophyll time series measurements from different genotypes. The use of additional time series models as random effects is essential as the residuals of the initial mixed model may contain autocorrelations that bias the result. The nature of mixed models offers a viable solution as these can incorporate time series models for residuals as random effects. The results from analyzing chlorophyll content time series show that the autocorrelation is successfully eliminated from the residuals and incorporated into the final model. This allows the use of statistical inference.

  • Název v anglickém jazyce

    Mixed Models as a Tool for Comparing Groups of Time Series in Plant Sciences

  • Popis výsledku anglicky

    Plants adapt to continual changes in environmental conditions throughout their life spans. High-throughput phenotyping methods have been developed to noninvasively monitor the physiological responses to abiotic/biotic stresses on a scale spanning a long time, covering most of the vegetative and reproductive stages. However, some of the physiological events comprise almost immediate and very fast responses towards the changing environment which might be overlooked in long-term observations. Additionally, there are certain technical difficulties and restrictions in analyzing phenotyping data, especially when dealing with repeated measurements. In this study, a method for comparing means at different time points using generalized linear mixed models combined with classical time series models is presented. As an example, we use multiple chlorophyll time series measurements from different genotypes. The use of additional time series models as random effects is essential as the residuals of the initial mixed model may contain autocorrelations that bias the result. The nature of mixed models offers a viable solution as these can incorporate time series models for residuals as random effects. The results from analyzing chlorophyll content time series show that the autocorrelation is successfully eliminated from the residuals and incorporated into the final model. This allows the use of statistical inference.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10611 - Plant sciences, botany

Návaznosti výsledku

  • Projekt

    Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2021

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    PLANTS-BASEL

  • ISSN

    2223-7747

  • e-ISSN

  • Svazek periodika

    10

  • Číslo periodika v rámci svazku

    2

  • Stát vydavatele periodika

    CH - Švýcarská konfederace

  • Počet stran výsledku

    16

  • Strana od-do

    362

  • Kód UT WoS článku

    000622990500001

  • EID výsledku v databázi Scopus

    2-s2.0-85100827958