Colonization and infestation ability of <i><scp>B</scp>olboschoenus maritimus</i> Palla in rice paddies of the <scp>C</scp>amargue, <scp>F</scp>rance

Audebert, Alain; Mouret, Jean-Claude; Roques, Sandrine; Carrara, Alain; Hammond, Roy; Gaungoo, Azaad; Sanusan, Suchada; Marnotte, Pascal

doi:10.1111/wbm.12012

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Another source of error can be due to the presence of weeds in certain fields. Weeds have a strong negative impact on yield (Audebert et al 2013;Delmotte et al 2011), but not necessarily on LAI estimations. The majority of farms use chemical treatments (herbicides) to control weeds (only approximately 10% use organic management practices).…”

Section: Discussionmentioning

confidence: 94%

STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

Courault

Hossard²,

Demarez

et al. 2021

Agron. Sustain. Dev.

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The assessment of rice yield at territory level is important for strategic economic decisions. Assessing spatial and temporal yield variability at regional scale is difficult because of the numerous factors involved, including agricultural practices, phenological calendars, and environmental contexts. New remote sensing data acquired at decametric resolution (Sentinel missions) can provide information on this spatial variability. The study objective was thus to evaluate the potential of Sentinel-2 images for monitoring rice cropping systems and yield from farm to region scales. The approach considered both observations and modeling. Indepth farmers surveys were carried out in the Camargue region, Southeastern France. The novelty was to use operational tools (BVNET and PHENOTB) to compute leaf area index, to daily interpolate this biophysical variable from 44 images acquired in 2016 and 2017 for each rice field, and to derive key phenological parameters from the analysis of the temporal profiles. The STICS crop model was spatially used, considering the biophysical variables derived from remote sensing. We tested four simulation strategies, differing in the integration intensity of remote sensing information into the model. Results have shown that (1) Sentinel-2 data allowed distinguishing early and late rice varieties. (2) The phenological stages mapped at the regional level allowed to better understand the agricultural practices of farmers. (3) The assimilation of remote sensing data to the STICS crop model significantly improved yield estimation and provided useful information on the spatial variability observed at regional scale. It was the first time that Sentinel-2 data are used with STICS crop model to assess rice yield at both farm and regional scale in the Camargue area. The proposed method is based on free open data and free access model, easily reproducible in other environmental contexts.

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Section: Discussionmentioning

confidence: 94%

STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

Courault

Hossard²,

Demarez

et al. 2021

Agron. Sustain. Dev.

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“…However, field-based evaluations and screening in controlled conditions are jointly used in breeding programs as stress tolerance at the seedling stage may not fully correlate with field performance. In our experiments, a moderate stress level, corresponding to a degree of salinity commonly observed in the Camargue region of France was used [ 60 ]. Considerable variability was observed in the phenotypic response to salt stress in both the RP and BP41, consistent with the findings of previous studies on japonica accessions [ 15 , 16 , 61 ].…”

Section: Discussionmentioning

confidence: 99%

Genomic selection for salinity tolerance in japonica rice

Bartholomé,

Frouin,

Brottier

et al. 2023

PLoS ONE

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Improving plant performance in salinity-prone conditions is a significant challenge in breeding programs. Genomic selection is currently integrated into many plant breeding programs as a tool for increasing selection intensity and precision for complex traits and for reducing breeding cycle length. A rice reference panel (RP) of 241 Oryza sativa L. japonica accessions genotyped with 20,255 SNPs grown in control and mild salinity stress conditions was evaluated at the vegetative stage for eight morphological traits and ion mass fractions (Na and K). Weak to strong genotype-by-condition interactions were found for the traits considered. Cross-validation showed that the predictive ability of genomic prediction methods ranged from 0.25 to 0.64 for multi-environment models with morphological traits and from 0.05 to 0.40 for indices of stress response and ion mass fractions. The performances of a breeding population (BP) comprising 393 japonica accessions were predicted with models trained on the RP. For validation of the predictive performances of the models, a subset of 41 accessions was selected from the BP and phenotyped under the same experimental conditions as the RP. The predictive abilities estimated on this subset ranged from 0.00 to 0.66 for the multi-environment models, depending on the traits, and were strongly correlated with the predictive abilities on cross-validation in the RP in salt condition (r = 0.69). We show here that genomic selection is efficient for predicting the salt stress tolerance of breeding lines. Genomic selection could improve the efficiency of rice breeding strategies for salinity-prone environments.

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“…Firstly, B. maritimus could have been a companion weed to S. italica cultivated in damp conditions. Today, for example, this weed is characteristic of Camargue rice fields(Audebert et al 2013). On the other hand, its presence could be linked to the consumption of its roots and tubers(Wollstonecroft et al 2008), or the use of its stalks for wickerwork or construction materials such as for roofing, as mentioned above (Claret de la Tourrette 1796, p 168).…”

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confidence: 99%

Plant uses and storage in the 5th century bc Etruscan quarter of the city of Lattara, France

Alonso

Rovira²

2016

Veget Hist Archaeobot

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An area between land and water was chosen in the 7th century BC by native Gauls and foreign Etruscan and Greek merchants to establish a commercial enclave. Then, in the early 5th century BC, this initial settlement at La Cougourlude with post-built houses on the banks of the small coastal river Lironde was relocated to the margins of a nearby lagoon along the Mediterranean coast, giving rise to the walled port city of Lattara. Archaeological excavations undertaken in the 2000s along the southern wall of Lattara in Quarter 27 revealed three houses which contained almost exclusively Etruscan pottery. The objective of this study is to analyse the archaeobotanical remains from these dwellings so as to identify the plant foods which were consumed and used by their inhabitants, as well as the methods of storage. The question arises whether anything particularly relating to Etruscan origins can be detected from the diet of the inhabitants. To study this aspect we have compared the data collected during the excavation with research undertaken at neighbouring settlements dating from periods either older, contemporary with or younger than Lattara, as well as research undertaken at sites in the Etruscan area of Italy.

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Colonization and infestation ability of Bolboschoenus maritimus Palla in rice paddies of the Camargue, France

Cited by 5 publications

References 5 publications

STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

Genomic selection for salinity tolerance in japonica rice

Plant uses and storage in the 5th century bc Etruscan quarter of the city of Lattara, France

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