Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model

High-yielding rice varieties (HYV) show strong compensation among sequentially developed yield components (YC). This phenotypic plasticity has adaptive value but for crop improvement, more information is needed on its effects on yield. SAMARA, a deterministic crop model predicting trait-trait and trait-environment interactions by simulating morphogenetic processes and competition among sinks for assimilates, was developed to study crop phenotypic plasticity. Dynamics of YC and morphology were observed on the HYV IR72 planted at standard and 4-fold greater density in 4 environments in the Philippines in 2012/13. Data for other years/seasons were obtained for model validation. Sequential path analysis was used to determine the phenotypic plasticity of traits consecutively contributing to yield. Tiller number at flowering (R2 = 0.94) and maturity (R2 = 0.84) and grain yield (R2 = 0.77) were predicted accurately for independent datasets. The model also predicted accurately density effects on aboveground dry weight (agdw), plant height, leaf size, spikelet number per panicle and filling percentage. Tiller and leaf mortality were over-estimated under high density. Overall, the model predicted satisfactorily the sequential compensation processes among YCs. They led to stable grain yield despite large morphological differences among density treatments and environments. Sensitivity analysis of simulation outcomes vs. variation in crop parameters indicated that modified genotypic tillering ability, phyllochron or leaf size had little effect on final grain yield because of compensations by other traits, although IR72 appeared to have an optimal combination of parameter values. Larger effects on grain yield were predicted for variation of parameters affecting the sensitivity of leaf and tiller mortality to assimilate resources and the ability to mobilize stem non-structural carbohydrates during grain filling. The model will be used next to perform physiological trait dissection and plasticity analyses for diverse genotypes.

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Main Authors: Kumar, Uttam, Laza, Ma. Rebecca, Soulie, Jean-Christophe, Pasco, Richard, Mendez, Kharla S., Dingkuhn, Michaël
Format: article biblioteca
Language:eng
Subjects:F01 - Culture des plantes, F62 - Physiologie végétale - Croissance et développement, U10 - Informatique, mathématiques et statistiques, F30 - Génétique et amélioration des plantes, Oryza sativa, riz irrigué, intéraction génotype environnement, phénotype, phénologie, variété, rendement des cultures, croissance, adaptabilité, espacement, facteur du milieu, adaptation, modélisation des cultures, modèle mathématique, modèle de simulation, génotype, facteur climatique, http://aims.fao.org/aos/agrovoc/c_5438, http://aims.fao.org/aos/agrovoc/c_15724, http://aims.fao.org/aos/agrovoc/c_24577, http://aims.fao.org/aos/agrovoc/c_5776, http://aims.fao.org/aos/agrovoc/c_5774, http://aims.fao.org/aos/agrovoc/c_8157, http://aims.fao.org/aos/agrovoc/c_10176, http://aims.fao.org/aos/agrovoc/c_3394, http://aims.fao.org/aos/agrovoc/c_35024, http://aims.fao.org/aos/agrovoc/c_7272, http://aims.fao.org/aos/agrovoc/c_2594, http://aims.fao.org/aos/agrovoc/c_117, http://aims.fao.org/aos/agrovoc/c_9000024, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_24242, http://aims.fao.org/aos/agrovoc/c_3225, http://aims.fao.org/aos/agrovoc/c_29554, http://aims.fao.org/aos/agrovoc/c_5783,
Online Access:http://agritrop.cirad.fr/580979/
http://agritrop.cirad.fr/580979/1/1-s2.0-S0378429016301320-main.pdf
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id dig-cirad-fr-580979
record_format koha
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic F01 - Culture des plantes
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
F30 - Génétique et amélioration des plantes
Oryza sativa
riz irrigué
intéraction génotype environnement
phénotype
phénologie
variété
rendement des cultures
croissance
adaptabilité
espacement
facteur du milieu
adaptation
modélisation des cultures
modèle mathématique
modèle de simulation
génotype
facteur climatique
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_15724
http://aims.fao.org/aos/agrovoc/c_24577
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_5774
http://aims.fao.org/aos/agrovoc/c_8157
http://aims.fao.org/aos/agrovoc/c_10176
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_35024
http://aims.fao.org/aos/agrovoc/c_7272
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_117
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_29554
http://aims.fao.org/aos/agrovoc/c_5783
F01 - Culture des plantes
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
F30 - Génétique et amélioration des plantes
Oryza sativa
riz irrigué
intéraction génotype environnement
phénotype
phénologie
variété
rendement des cultures
croissance
adaptabilité
espacement
facteur du milieu
adaptation
modélisation des cultures
modèle mathématique
modèle de simulation
génotype
facteur climatique
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_15724
http://aims.fao.org/aos/agrovoc/c_24577
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_5774
http://aims.fao.org/aos/agrovoc/c_8157
http://aims.fao.org/aos/agrovoc/c_10176
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_35024
http://aims.fao.org/aos/agrovoc/c_7272
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_117
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_29554
http://aims.fao.org/aos/agrovoc/c_5783
spellingShingle F01 - Culture des plantes
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
F30 - Génétique et amélioration des plantes
Oryza sativa
riz irrigué
intéraction génotype environnement
phénotype
phénologie
variété
rendement des cultures
croissance
adaptabilité
espacement
facteur du milieu
adaptation
modélisation des cultures
modèle mathématique
modèle de simulation
génotype
facteur climatique
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_15724
http://aims.fao.org/aos/agrovoc/c_24577
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_5774
http://aims.fao.org/aos/agrovoc/c_8157
http://aims.fao.org/aos/agrovoc/c_10176
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_35024
http://aims.fao.org/aos/agrovoc/c_7272
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_117
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_29554
http://aims.fao.org/aos/agrovoc/c_5783
F01 - Culture des plantes
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
F30 - Génétique et amélioration des plantes
Oryza sativa
riz irrigué
intéraction génotype environnement
phénotype
phénologie
variété
rendement des cultures
croissance
adaptabilité
espacement
facteur du milieu
adaptation
modélisation des cultures
modèle mathématique
modèle de simulation
génotype
facteur climatique
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_15724
http://aims.fao.org/aos/agrovoc/c_24577
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_5774
http://aims.fao.org/aos/agrovoc/c_8157
http://aims.fao.org/aos/agrovoc/c_10176
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_35024
http://aims.fao.org/aos/agrovoc/c_7272
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_117
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_29554
http://aims.fao.org/aos/agrovoc/c_5783
Kumar, Uttam
Laza, Ma. Rebecca
Soulie, Jean-Christophe
Pasco, Richard
Mendez, Kharla S.
Dingkuhn, Michaël
Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
description High-yielding rice varieties (HYV) show strong compensation among sequentially developed yield components (YC). This phenotypic plasticity has adaptive value but for crop improvement, more information is needed on its effects on yield. SAMARA, a deterministic crop model predicting trait-trait and trait-environment interactions by simulating morphogenetic processes and competition among sinks for assimilates, was developed to study crop phenotypic plasticity. Dynamics of YC and morphology were observed on the HYV IR72 planted at standard and 4-fold greater density in 4 environments in the Philippines in 2012/13. Data for other years/seasons were obtained for model validation. Sequential path analysis was used to determine the phenotypic plasticity of traits consecutively contributing to yield. Tiller number at flowering (R2 = 0.94) and maturity (R2 = 0.84) and grain yield (R2 = 0.77) were predicted accurately for independent datasets. The model also predicted accurately density effects on aboveground dry weight (agdw), plant height, leaf size, spikelet number per panicle and filling percentage. Tiller and leaf mortality were over-estimated under high density. Overall, the model predicted satisfactorily the sequential compensation processes among YCs. They led to stable grain yield despite large morphological differences among density treatments and environments. Sensitivity analysis of simulation outcomes vs. variation in crop parameters indicated that modified genotypic tillering ability, phyllochron or leaf size had little effect on final grain yield because of compensations by other traits, although IR72 appeared to have an optimal combination of parameter values. Larger effects on grain yield were predicted for variation of parameters affecting the sensitivity of leaf and tiller mortality to assimilate resources and the ability to mobilize stem non-structural carbohydrates during grain filling. The model will be used next to perform physiological trait dissection and plasticity analyses for diverse genotypes.
format article
topic_facet F01 - Culture des plantes
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
F30 - Génétique et amélioration des plantes
Oryza sativa
riz irrigué
intéraction génotype environnement
phénotype
phénologie
variété
rendement des cultures
croissance
adaptabilité
espacement
facteur du milieu
adaptation
modélisation des cultures
modèle mathématique
modèle de simulation
génotype
facteur climatique
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_15724
http://aims.fao.org/aos/agrovoc/c_24577
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_5774
http://aims.fao.org/aos/agrovoc/c_8157
http://aims.fao.org/aos/agrovoc/c_10176
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_35024
http://aims.fao.org/aos/agrovoc/c_7272
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_117
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_29554
http://aims.fao.org/aos/agrovoc/c_5783
author Kumar, Uttam
Laza, Ma. Rebecca
Soulie, Jean-Christophe
Pasco, Richard
Mendez, Kharla S.
Dingkuhn, Michaël
author_facet Kumar, Uttam
Laza, Ma. Rebecca
Soulie, Jean-Christophe
Pasco, Richard
Mendez, Kharla S.
Dingkuhn, Michaël
author_sort Kumar, Uttam
title Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
title_short Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
title_full Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
title_fullStr Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
title_full_unstemmed Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model
title_sort compensatory phenotypic plasticity in irrigated rice: sequential formation of yield components and simulation with samara model
url http://agritrop.cirad.fr/580979/
http://agritrop.cirad.fr/580979/1/1-s2.0-S0378429016301320-main.pdf
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AT dingkuhnmichael compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel
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spelling dig-cirad-fr-5809792024-01-28T23:35:49Z http://agritrop.cirad.fr/580979/ http://agritrop.cirad.fr/580979/ Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model. Kumar Uttam, Laza Ma. Rebecca, Soulie Jean-Christophe, Pasco Richard, Mendez Kharla S., Dingkuhn Michaël. 2016. Field Crops Research, 193 : 164-177.https://doi.org/10.1016/j.fcr.2016.04.036 <https://doi.org/10.1016/j.fcr.2016.04.036> Compensatory phenotypic plasticity in irrigated rice: Sequential formation of yield components and simulation with SAMARA model Kumar, Uttam Laza, Ma. Rebecca Soulie, Jean-Christophe Pasco, Richard Mendez, Kharla S. Dingkuhn, Michaël eng 2016 Field Crops Research F01 - Culture des plantes F62 - Physiologie végétale - Croissance et développement U10 - Informatique, mathématiques et statistiques F30 - Génétique et amélioration des plantes Oryza sativa riz irrigué intéraction génotype environnement phénotype phénologie variété rendement des cultures croissance adaptabilité espacement facteur du milieu adaptation modélisation des cultures modèle mathématique modèle de simulation génotype facteur climatique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_15724 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_5774 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_35024 http://aims.fao.org/aos/agrovoc/c_7272 http://aims.fao.org/aos/agrovoc/c_2594 http://aims.fao.org/aos/agrovoc/c_117 http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_29554 Philippines http://aims.fao.org/aos/agrovoc/c_5783 High-yielding rice varieties (HYV) show strong compensation among sequentially developed yield components (YC). This phenotypic plasticity has adaptive value but for crop improvement, more information is needed on its effects on yield. SAMARA, a deterministic crop model predicting trait-trait and trait-environment interactions by simulating morphogenetic processes and competition among sinks for assimilates, was developed to study crop phenotypic plasticity. Dynamics of YC and morphology were observed on the HYV IR72 planted at standard and 4-fold greater density in 4 environments in the Philippines in 2012/13. Data for other years/seasons were obtained for model validation. Sequential path analysis was used to determine the phenotypic plasticity of traits consecutively contributing to yield. Tiller number at flowering (R2 = 0.94) and maturity (R2 = 0.84) and grain yield (R2 = 0.77) were predicted accurately for independent datasets. The model also predicted accurately density effects on aboveground dry weight (agdw), plant height, leaf size, spikelet number per panicle and filling percentage. Tiller and leaf mortality were over-estimated under high density. Overall, the model predicted satisfactorily the sequential compensation processes among YCs. They led to stable grain yield despite large morphological differences among density treatments and environments. Sensitivity analysis of simulation outcomes vs. variation in crop parameters indicated that modified genotypic tillering ability, phyllochron or leaf size had little effect on final grain yield because of compensations by other traits, although IR72 appeared to have an optimal combination of parameter values. Larger effects on grain yield were predicted for variation of parameters affecting the sensitivity of leaf and tiller mortality to assimilate resources and the ability to mobilize stem non-structural carbohydrates during grain filling. The model will be used next to perform physiological trait dissection and plasticity analyses for diverse genotypes. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/580979/1/1-s2.0-S0378429016301320-main.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.fcr.2016.04.036 10.1016/j.fcr.2016.04.036 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fcr.2016.04.036 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.fcr.2016.04.036