Study of the radioecological sensitivity of rice to radioactive contamination

This study focused on the radioecology of rice and explored how the French specificities of rice cultivation can be taken into account in risk assessment. The objective of the study was to characterize the radioecological sensitivity of rice with respect to an accidental release of radioactivity. We want to know if a uniform and specific deposit would involve the same contamination on representative paddy fields of Camargue. To model the transfer of the radionuclides in the rice caryopsis following an accidental atmospheric pollution, we used the classical modelling for the cereals which considers first the interception by the foliage (modelled by an interception ratio) then the translocation to the grain (modelled by a translocation factor). The values of the parameters (interception ratio, translocation factor and yield) were regionalized with the agronomical software ORIZA2000, developed by the IRRI (International Rice Research Institute). We partly calibrated ORIZA2000 for a French rice variety: Ariete, thanks to physiological data provided for International Cooperation Centre in Agronomical Research for Development (CIRAD). ORIZA2000 proposes a daily follow-up of the leaf area index which can be correlated with the interception ratio. Five simulations with various climates, irrigation managements, and technical uses have been inputted on ORIZA2000. The data inputted were extracted from the database AGROSYST from the French Institute for Agronomical Research (INRA) and from the CIRAD. We established two scenarios of contamination. The first one consisted in a single contamination of water. In this case, there is almost no difference between simulations. However, in each simulation (except for organic farming) it is relevant to notice that the fourth depletion of water leads to a significant variation of contamination. The second contamination scenario consisted in a double contamination of water and of air. In that case, technical practices are responsible of the highest source of variability of the grain contamination. The variability of the contamination is mainly due to the variability of the yield which has in the radioecological modelling a dilution effect. The rice produced by organic farming is more sensitive than the rice produced by conventional farming because of low yields.

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Bibliographic Details
Main Authors: Pey, B., Mercat-Rommens, C., Audebert, Alain, Mouret, Jean Claude
Format: article biblioteca
Language:eng
Subjects:P02 - Pollution, F01 - Culture des plantes, F60 - Physiologie et biochimie végétale, U10 - Informatique, mathématiques et statistiques, riz, Oryza sativa, contamination radioactive, radioactivité, radioécologie, modèle mathématique, modélisation environnementale, pollution atmosphérique, pollution de l'eau, modèle de simulation, http://aims.fao.org/aos/agrovoc/c_6599, http://aims.fao.org/aos/agrovoc/c_5438, http://aims.fao.org/aos/agrovoc/c_28321, http://aims.fao.org/aos/agrovoc/c_6426, http://aims.fao.org/aos/agrovoc/c_35784, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_9000056, http://aims.fao.org/aos/agrovoc/c_228, http://aims.fao.org/aos/agrovoc/c_8321, http://aims.fao.org/aos/agrovoc/c_24242, http://aims.fao.org/aos/agrovoc/c_3081, http://aims.fao.org/aos/agrovoc/c_4188,
Online Access:http://agritrop.cirad.fr/568804/
http://agritrop.cirad.fr/568804/1/document_568804.pdf
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id dig-cirad-fr-568804
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 P02 - Pollution
F01 - Culture des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
riz
Oryza sativa
contamination radioactive
radioactivité
radioécologie
modèle mathématique
modélisation environnementale
pollution atmosphérique
pollution de l'eau
modèle de simulation
http://aims.fao.org/aos/agrovoc/c_6599
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_28321
http://aims.fao.org/aos/agrovoc/c_6426
http://aims.fao.org/aos/agrovoc/c_35784
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_228
http://aims.fao.org/aos/agrovoc/c_8321
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_4188
P02 - Pollution
F01 - Culture des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
riz
Oryza sativa
contamination radioactive
radioactivité
radioécologie
modèle mathématique
modélisation environnementale
pollution atmosphérique
pollution de l'eau
modèle de simulation
http://aims.fao.org/aos/agrovoc/c_6599
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_28321
http://aims.fao.org/aos/agrovoc/c_6426
http://aims.fao.org/aos/agrovoc/c_35784
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_228
http://aims.fao.org/aos/agrovoc/c_8321
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_4188
spellingShingle P02 - Pollution
F01 - Culture des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
riz
Oryza sativa
contamination radioactive
radioactivité
radioécologie
modèle mathématique
modélisation environnementale
pollution atmosphérique
pollution de l'eau
modèle de simulation
http://aims.fao.org/aos/agrovoc/c_6599
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_28321
http://aims.fao.org/aos/agrovoc/c_6426
http://aims.fao.org/aos/agrovoc/c_35784
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_228
http://aims.fao.org/aos/agrovoc/c_8321
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_4188
P02 - Pollution
F01 - Culture des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
riz
Oryza sativa
contamination radioactive
radioactivité
radioécologie
modèle mathématique
modélisation environnementale
pollution atmosphérique
pollution de l'eau
modèle de simulation
http://aims.fao.org/aos/agrovoc/c_6599
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_28321
http://aims.fao.org/aos/agrovoc/c_6426
http://aims.fao.org/aos/agrovoc/c_35784
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_228
http://aims.fao.org/aos/agrovoc/c_8321
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_4188
Pey, B.
Mercat-Rommens, C.
Audebert, Alain
Mouret, Jean Claude
Study of the radioecological sensitivity of rice to radioactive contamination
description This study focused on the radioecology of rice and explored how the French specificities of rice cultivation can be taken into account in risk assessment. The objective of the study was to characterize the radioecological sensitivity of rice with respect to an accidental release of radioactivity. We want to know if a uniform and specific deposit would involve the same contamination on representative paddy fields of Camargue. To model the transfer of the radionuclides in the rice caryopsis following an accidental atmospheric pollution, we used the classical modelling for the cereals which considers first the interception by the foliage (modelled by an interception ratio) then the translocation to the grain (modelled by a translocation factor). The values of the parameters (interception ratio, translocation factor and yield) were regionalized with the agronomical software ORIZA2000, developed by the IRRI (International Rice Research Institute). We partly calibrated ORIZA2000 for a French rice variety: Ariete, thanks to physiological data provided for International Cooperation Centre in Agronomical Research for Development (CIRAD). ORIZA2000 proposes a daily follow-up of the leaf area index which can be correlated with the interception ratio. Five simulations with various climates, irrigation managements, and technical uses have been inputted on ORIZA2000. The data inputted were extracted from the database AGROSYST from the French Institute for Agronomical Research (INRA) and from the CIRAD. We established two scenarios of contamination. The first one consisted in a single contamination of water. In this case, there is almost no difference between simulations. However, in each simulation (except for organic farming) it is relevant to notice that the fourth depletion of water leads to a significant variation of contamination. The second contamination scenario consisted in a double contamination of water and of air. In that case, technical practices are responsible of the highest source of variability of the grain contamination. The variability of the contamination is mainly due to the variability of the yield which has in the radioecological modelling a dilution effect. The rice produced by organic farming is more sensitive than the rice produced by conventional farming because of low yields.
format article
topic_facet P02 - Pollution
F01 - Culture des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
riz
Oryza sativa
contamination radioactive
radioactivité
radioécologie
modèle mathématique
modélisation environnementale
pollution atmosphérique
pollution de l'eau
modèle de simulation
http://aims.fao.org/aos/agrovoc/c_6599
http://aims.fao.org/aos/agrovoc/c_5438
http://aims.fao.org/aos/agrovoc/c_28321
http://aims.fao.org/aos/agrovoc/c_6426
http://aims.fao.org/aos/agrovoc/c_35784
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_228
http://aims.fao.org/aos/agrovoc/c_8321
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_4188
author Pey, B.
Mercat-Rommens, C.
Audebert, Alain
Mouret, Jean Claude
author_facet Pey, B.
Mercat-Rommens, C.
Audebert, Alain
Mouret, Jean Claude
author_sort Pey, B.
title Study of the radioecological sensitivity of rice to radioactive contamination
title_short Study of the radioecological sensitivity of rice to radioactive contamination
title_full Study of the radioecological sensitivity of rice to radioactive contamination
title_fullStr Study of the radioecological sensitivity of rice to radioactive contamination
title_full_unstemmed Study of the radioecological sensitivity of rice to radioactive contamination
title_sort study of the radioecological sensitivity of rice to radioactive contamination
url http://agritrop.cirad.fr/568804/
http://agritrop.cirad.fr/568804/1/document_568804.pdf
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AT mercatrommensc studyoftheradioecologicalsensitivityofricetoradioactivecontamination
AT audebertalain studyoftheradioecologicalsensitivityofricetoradioactivecontamination
AT mouretjeanclaude studyoftheradioecologicalsensitivityofricetoradioactivecontamination
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spelling dig-cirad-fr-5688042024-01-28T21:20:24Z http://agritrop.cirad.fr/568804/ http://agritrop.cirad.fr/568804/ Study of the radioecological sensitivity of rice to radioactive contamination. Pey B., Mercat-Rommens C., Audebert Alain, Mouret Jean Claude. 2009. Radioprotection, 44 (5) : 339-343.https://doi.org/10.1051/radiopro/20095066 <https://doi.org/10.1051/radiopro/20095066> Study of the radioecological sensitivity of rice to radioactive contamination Pey, B. Mercat-Rommens, C. Audebert, Alain Mouret, Jean Claude eng 2009 Radioprotection P02 - Pollution F01 - Culture des plantes F60 - Physiologie et biochimie végétale U10 - Informatique, mathématiques et statistiques riz Oryza sativa contamination radioactive radioactivité radioécologie modèle mathématique modélisation environnementale pollution atmosphérique pollution de l'eau modèle de simulation http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_28321 http://aims.fao.org/aos/agrovoc/c_6426 http://aims.fao.org/aos/agrovoc/c_35784 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_228 http://aims.fao.org/aos/agrovoc/c_8321 http://aims.fao.org/aos/agrovoc/c_24242 France Languedoc-Roussillon http://aims.fao.org/aos/agrovoc/c_3081 http://aims.fao.org/aos/agrovoc/c_4188 This study focused on the radioecology of rice and explored how the French specificities of rice cultivation can be taken into account in risk assessment. The objective of the study was to characterize the radioecological sensitivity of rice with respect to an accidental release of radioactivity. We want to know if a uniform and specific deposit would involve the same contamination on representative paddy fields of Camargue. To model the transfer of the radionuclides in the rice caryopsis following an accidental atmospheric pollution, we used the classical modelling for the cereals which considers first the interception by the foliage (modelled by an interception ratio) then the translocation to the grain (modelled by a translocation factor). The values of the parameters (interception ratio, translocation factor and yield) were regionalized with the agronomical software ORIZA2000, developed by the IRRI (International Rice Research Institute). We partly calibrated ORIZA2000 for a French rice variety: Ariete, thanks to physiological data provided for International Cooperation Centre in Agronomical Research for Development (CIRAD). ORIZA2000 proposes a daily follow-up of the leaf area index which can be correlated with the interception ratio. Five simulations with various climates, irrigation managements, and technical uses have been inputted on ORIZA2000. The data inputted were extracted from the database AGROSYST from the French Institute for Agronomical Research (INRA) and from the CIRAD. We established two scenarios of contamination. The first one consisted in a single contamination of water. In this case, there is almost no difference between simulations. However, in each simulation (except for organic farming) it is relevant to notice that the fourth depletion of water leads to a significant variation of contamination. The second contamination scenario consisted in a double contamination of water and of air. In that case, technical practices are responsible of the highest source of variability of the grain contamination. The variability of the contamination is mainly due to the variability of the yield which has in the radioecological modelling a dilution effect. The rice produced by organic farming is more sensitive than the rice produced by conventional farming because of low yields. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/568804/1/document_568804.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1051/radiopro/20095066 10.1051/radiopro/20095066 info:eu-repo/semantics/altIdentifier/doi/10.1051/radiopro/20095066 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1051/radiopro/20095066