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