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Wyszukujesz frazę "multidimensional statistical analysis," wg kryterium: Temat


Wyświetlanie 1-1 z 1
Tytuł:
Early detection of phosphorus deficiency stress in cucumber at the cellular level using chlorophyll fluorescence signals
Autorzy:
Sieczko, Leszek
Dąbrowski, Piotr
Kowalczyk, Katarzyna
Gajc-Wolska, Janina
Borucki, Wojciech
Janaszek-Mańkowska, Monika
Kowalczyk, Waldemar
Farci, Domenica
Kalaji, Hazem M.
Powiązania:
https://bibliotekanauki.pl/articles/2203572.pdf
Data publikacji:
2022
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
abiotic stress
chlorophyll fluorescence
cucumber
JIP test
multidimensional statistical analysis
photosynthesis
Opis:
Abiotic stressors contribute to growth restriction and developmental disorders in plants. Early detection of the first signs of changes in plant functioning is very important. The objective of this study was to identify chlorophyll fluorescence parameters that change under phosphorus deficiency stress in cucumber. In this work, a trail to study the early changes caused by phosphorus deficiency in cucumber plants by analysing their photosynthetic performance is presented. Chlorophyll-a fluorescence (ChF) parameters were measured every 7 days for a period of 28 days. Measurements were made separately on young and old leaves and on cucumber fruit. Parameters that decreased during the stress were: p2G, PI abs, PI total, REo/CSo, and TRo/CSo. P deficiency decreased total electron carriers per RC (ECo/RC), yields (TRo/ABS (Fv/Fm), ETo/TRo, REo/ETo, ETo/ABS and REo/ABS), fluxes (REo/RC and REo/CSo) and fractional reduction of PSI end electron acceptors, and damaged all photochemical and non-photochemical redox reactions. Principal component analysis revealed a group of ChF parameters that may indicate early phosphorus deficiency in cucumber plants. Our results are used in the discovery of sensitive bioindicators of phosphorus deficiency in cucumber plants. Most JIP test parameters are linked to mathematical equations, so we recommend using of advanced statistical tools, such as principal component analysis, which should be considered very useful for stress identification. It has also been shown to be more effective in multivariate methods compared to univariate statistical methods was demonstrated.
Źródło:
Journal of Water and Land Development; 2022, Special Issue; 176--186
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-1 z 1

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