The potential of dynamic physiological traits in young tomato plants to predict field-yield performance

Copyright © 2021 Elsevier B.V. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Plant science : an international journal of experimental plant biology. - 1985. - 315(2022) vom: 24. Feb., Seite 111122
1. Verfasser: Gosa, Sanbon Chaka (VerfasserIn)
Weitere Verfasser: Koch, Amit, Shenhar, Itamar, Hirschberg, Joseph, Zamir, Dani, Moshelion, Menachem
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Plant science : an international journal of experimental plant biology
Schlagworte:Comparative Study Journal Article Drought tolerance Functional phenotyping Physiological trait Time-series measurements Tomato Yield prediction
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520 |a To address the challenge of predicting tomato yields in the field, we used whole-plant functional phenotyping to evaluate water relations under well-irrigated and drought conditions. The genotypes tested are known to exhibit variability in their yields in wet and dry fields. The examined lines included two lines with recessive mutations that affect carotenoid biosynthesis, zeta z2083 and tangerine t3406, both isogenic to the processing tomato variety M82. The two mutant lines were reciprocally grafted onto M82, and multiple physiological characteristics were measured continuously, before, during and after drought treatment in the greenhouse. A comparative analysis of greenhouse and field yields showed that the whole-canopy stomatal conductance (gsc) in the morning and cumulative transpiration (CT) were strongly correlated with field measurements of total yield (TY: r2 = 0.9 and 0.77, respectively) and plant vegetative weight (PW: r2 = 0.6 and 0.94, respectively). Furthermore, the minimum CT during drought and the rate of recovery when irrigation was resumed were both found to predict resilience 
650 4 |a Comparative Study 
650 4 |a Journal Article 
650 4 |a Drought tolerance 
650 4 |a Functional phenotyping 
650 4 |a Physiological trait 
650 4 |a Time-series measurements 
650 4 |a Tomato 
650 4 |a Yield prediction 
700 1 |a Koch, Amit  |e verfasserin  |4 aut 
700 1 |a Shenhar, Itamar  |e verfasserin  |4 aut 
700 1 |a Hirschberg, Joseph  |e verfasserin  |4 aut 
700 1 |a Zamir, Dani  |e verfasserin  |4 aut 
700 1 |a Moshelion, Menachem  |e verfasserin  |4 aut 
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