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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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 |
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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 |
work_keys_str_mv |
AT kumaruttam compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel AT lazamarebecca compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel AT souliejeanchristophe compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel AT pascorichard compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel AT mendezkharlas compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel AT dingkuhnmichael compensatoryphenotypicplasticityinirrigatedricesequentialformationofyieldcomponentsandsimulationwithsamaramodel |
_version_ |
1792499082211622912 |
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 |