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  • Rural Digital Europe
  • 2014-2023
  • Other research products
  • CemOA
  • Repositori Institucional URV

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Naud, O.; Verges, A.; Hebrard, O.; Codis, S.; +2 Authors

    National policies in Europe aim to reduce use of pesticides. Grapevine receives yearly many sprayings. There is a great variety of sprayers available for vineyards. We can sum up ques-tions addressed to research bodies by the following issues. Is it possible to sort out sprayers and practices according to crop protection and environmental performances? How much is it possible to save on amounts of chemicals sprayed when one uses an efficient sprayer? The present contribution to this research is based on a 4 rows, 10 meters length, physical full scale model of a vineyard. The Evasprayviti model of a vineyard row was designed to repro-duce different foliage volume and densities and to simulate the interaction of the canopy with the flow of plant protection product and air emitted by a mobile sprayer. It comprises a col-lecting device, and a complementary structure on each side of it. The collecting device ena-bles accurate and repeatable sampling of the spray deposits. It is composed of plastic sheets that simulate leaves, attached to vertical aluminium posts. The complementary structure pre-vents perturbative effects on the spray flow on the edges of the collecting device. Evasprayviti can be configured to simulate different growth stages (Codis&al, 2013). The test spray is a mix of a tracer, Tartrazine, and water. A standard pneumatic sprayer, an airblast sprayer and an air-assisted face to face sprayer were tested. The pneumatic sprayer was tested in 3 configurations, for spraying respectively 2, 3 and 4 rows at a time. The face to face sprayer and the airblast sprayer were configured to be used to spray 3 rows and 2 rows, respectively. The amount of product deposited in the canopy and its distribution according to depth and height of leaves was studied for early, intermediate and full growth stage, with respective Leaf Area Index (LAI) values of 0.24, 0.88 and 1.68 ha/ha. The sampling of a cross-section of the collecting device was divided in compartments (3 depths x 3 heights at full growth stage). Deposits on rows close to sprayer and on rows next to sprayer were compared when relevant. The mass of deposits per unit of leaf surface, normalised by amount sprayed per hectare of ground, was measured for each compartment. For precision assessment, this normalised deposit was divided by the reference potential deposit on the target, which is cal-culated for each growth stage according to the hypothesis that all the spray is homogeneous-ly deposited in the compartments. Results showed different deposition profiles, which are discussed. The face to face sprayer exhibited the best efficiency and homogeneity in full and intermediate growth stage, and best efficiency on early stage as well, with homogeneity comparable to the pneumatic sprayer's on this stage. The airblast sprayer used on two rows had a good overall efficiency for early and intermediate stages but a bad homogeneity at all stages.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    CemOA
    2014
    Data sources: CemOA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2014
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ait Mouheb, N.; Schillings, J.; Al Muhammad, J.; Bendoula, R.; +3 Authors

    To better understand the physical and biological clogging in drip-irrigation, a study was conducted on the impacts of hydrodynamic conditions on clay particle deposition and biofilm development in drippers using an optical method. A transparent milli-fluidic system composed of labyrinth channels was used to identify areas most susceptible to particle clogging using two different types of clay suspensions: sodium bentonite and kaolin. The impact of salt addition [(NaCl) = 200 mg L

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    CemOA
    2019
    Data sources: CemOA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2019
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: El Hajj, M.;

    In the context of increasing the pressure on water resources, the search for improved agricultural productivity of irrigation water leads to irrigation schedule optimization according to soil water conditions and crop development stages. Spatial remote sensing currently provides spatialized near real-time information of soil and vegetation characteristics. In particular, radar data, which showed a high potential for estimating soil moisture. Similarly, the optical data have long been used to estimate the vegetation parameters (biomass, yield). Such information can be integrated into crop models to predict yield evolution in real-time. The general aim of the thesis is to show how the information derived from remote sensing data with high spatial and temporal resolution can restore the water and vegetative dynamics of an irrigated perimeter. The approach is based on experiments conducted on a system of irrigated grasslands, with spatial and ground observations at high time repetitiveness, and the use of a crop model. The first part of the thesis evaluates the potential of radar data for cultivated soil water status monitoring. The X-band (3 cm wavelength) was chosen since X-band radar sensors allow plots monitoring with a high revisit time, and image acquisition at fine spatial resolution (about 1m), adapted to plots with small size. Results showed that the X-band radar signal allows soil moisture evolution monitoring even in the presence of a dense vegetation cover. In addition, results showed that the radar data are able to identify the water supplies even if the radar image is acquired three days after the irrigation event. The second part evaluates the potential of radar-optical coupling to estimate soil moisture in the presence of vegetation. The results showed that HH polarization combined with one vegetation parameter, derived from the optical data, allow soil moisture estimation with an accuracy around 5 vol.%. The methodology developed in this section of the thesis provides a multi-sensor approach (optical and radar) for operational soil moisture mapping in the presence of vegetation. The third part of the thesis study the potential of spatial data (radar and optical) to feed a crop model representing real-time biomass evolution. This part is based on the PILOTE model, which allows the prediction of crop sensitivity to water stress, and integrate criteria for irrigation launching and grassland harvest. Results showed that the integration of spatial data information estimates (LAI, harvest and irrigation dates) into PILOTE provides a good accuracy in yield prediction. The relevance of spatial information can then be analyzed in terms of acquisition frequency and accuracy of estimations produced, opening perspectives for the application of high temporal resolution remote sensing for the supervision and management of water supply in irrigated areas. / Dans un contexte d'accroissement des tensions sur les ressources en eau, la recherche d'une meilleure productivité agricole de l'eau d'irrigation amène à optimiser les calendriers d'arrosage en fonction des états hydriques des sols et des stades de développement de la culture. La télédétection spatiale permet aujourd'hui de fournir des informations spatialisées en temps quasi-réel sur les caractéristiques du sol et de la végétation. En particulier, les données radar ont montré un fort potentiel pour l'estimation de l'humidité du sol. De même, les données optiques sont utilisées depuis longtemps pour estimer les paramètres relatifs à la végétation (indice foliaire, biomasse, rendement). Ces informations peuvent être intégrées dans des modèles de culture pour simuler en temps réel l'évolution du rendement. L'objectif général de la thèse est de montrer comment les informations issues de la télédétection spatiale à haute résolution spatio-temporelle permettent de retrouver les dynamiques hydriques et végétatives d'un périmètre irrigué. La démarche repose sur des expérimentations menées sur un système de prairies irriguées, avec des observations spatiales et au sol à haute répétitivité temporelle, et l'utilisation d'un modèle de culture. Le premier volet de la thèse évalue le potentiel des données radar à suivre l'état hydrique d'un sol cultivé. La bande X (3 cm de longueur d'onde) a été choisie puisque les capteurs radar en bande X permettent un suivi des parcelles avec une forte répétitivité temporelle, et des acquisitions à une très haute résolution spatiale (environ 1 m), adaptée à des parcelles de petite taille. Les résultats ont montré que le signal radar en bande X permet de suivre l'évolution de l'humidité du sol même en présence d'un couvert végétal dense. De plus, les résultats ont montré que les données radar sont capables d'identifier les apports d'eau même si l'image radar est acquise trois jours après l'achèvement de l'irrigation. Le deuxième volet évalue le potentiel du couplage radar-optique pour estimer l'humidité du sol en présence de la végétation. Les résultats ont montré que la polarisation HH combinée avec un paramètre de la végétation, dérivée à partir des données optiques, permet d'estimer l'humidité du sol avec une précision de l'ordre de 5 vol.%. La méthodologie développée dans cette partie de la thèse permet de proposer une approche multi-capteur (optique et radar) pour une cartographie opérationnelle de l'humidité du sol en présence de végétation. La troisième partie de la thèse étudie le potentiel des données spatiales (radar et optique) pour alimenter un modèle de culture représentant l'évolution de la biomasse en temps réel. Cette partie s'appuie sur le modèle PILOTE, permettant de prédire la sensibilité de la culture au stress hydrique, et d'intégrer des critères de déclenchement des arrosages et de fauche des prairies. Les résultats ont montré que l'intégration dans PILOTE d'informations estimées à partir des données spatiales (LAI, dates des coupes et irrigations) permet de prédire le rendement avec une bonne précision. La pertinence des informations spatiales peut ainsi être analysée en termes de fréquence d'acquisition et de précision des estimations produites, ouvrant des perspectives pour l'application de la télédétection à haute résolution temporelle à la supervision et la gestion des apports d'eau dans les périmètres irrigués.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
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    CemOA
    2016
    Data sources: CemOA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2016
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fatras, C.; Borderies, P.; Baghdadi, N.; Zribi, M.; +3 Authors

    The behavior of the Ka-band backscattering coefficient at nadir and close-to-nadir angles for land applications is poorly documented. The measurements made during a ground-based campaign at Ka-band were performed at nadir and close-to-nadir angles over bare soils for different surface roughness and soil moisture conditions. The resulting backscattering levels exhibited a dynamic range of approximately 23 dB at nadir for soil moisture contents between 5 and 50 % m3/m3 over both smooth and rough surfaces. These results were then compared to the Geometrical Optics (GO) and Millimeter MicroWave (MMW) models. Generally, GO finely fit the backscattering coefficients close to nadir, and MMW appeared to fit for larger incidence angles or rough surfaces. The results obtained in this study can address pre-launch science and engineering considerations for the interferometry-altimetry SWOT mission operating at Ka-band.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
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    CemOA
    2016
    Data sources: CemOA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2016
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Viet Nguyen, L.; Tateishi, R.; Kondoh, A.; Sharma, R.C.; +3 Authors

    This research was carried out in a dense tropical forest region with the objective of improving the biomass estimates by a combination of ALOS-2 SAR, Landsat 8 optical, and field plots data. Using forest inventory based biomass data, the performance of different parameters from the two sensors was evaluated. The regression analysis with the biomass data showed that the backscatter from forest object (σ°forest) obtained from the SAR data was more sensitive to the biomass than HV polarization, SAR textures, and maximum NDVI parameters. However, the combination of the maximum NDVI from optical data, SAR textures from HV polarization, and σ°forest improved estimates of the biomass. The best model derived by the combination of multiple parameters from ALOS-2 SAR and Landsat 8 data was validated with inventory data. Then, the best validated model was used to produce an up-to-date biomass map for 2015 in Yok Don National Park, which is an important conservation area in Vietnam. The validation results showed that 74% of the variation of in biomass could be explained by our model.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    CemOA
    2016
    Data sources: CemOA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CemOAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2016
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Pedret A; Catalán Ú; Rubió L; Baiges I; +7 Authors

    © 2020 American Chemical Society. All rights reserved. Protein functional interactions could explain the biological response of secoiridoids (SECs), main phenolic compounds in virgin olive oil (VOO). The aim was to assess protein-protein interactions (PPIs) of the aorta gap junction alpha-1 (GJA1) and the heart peptidyl-prolyl cis-trans isomerase (FKBP1A), plus the phosphorylated heart proteome, to describe new molecular pathways in the cardiovascular system in rats using nanoliquid chromatography coupled with mass spectrometry. PPIs modified by SECs and associated with GJA1 in aorta rat tissue were calpain, TUBA1A, and HSPB1. Those associated with FKBP1A in rat heart tissue included SUCLG1, HSPE1, and TNNI3. In the heart, SECs modulated the phosphoproteome through the main canonical pathways PI3K/mTOR signaling (AKT1S1 and GAB2) and gap junction signaling (GAB2 and GJA1). PPIs associated with GJA1 and with FKBP1A, the phosphorylation of GAB2, and the dephosphorylation of GJA1 and AKT1S1 in rat tissues are promising protein targets promoting cardiovascular protection to explain the health benefits of VOO.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Repositori Instituci...arrow_drop_down
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    Authors: Jay, S.; Maupas, F.; Bendoula, R.; Gorretta, N.;

    Remote sensing has gained much attention for agronomic applications such as crop management or yield estimation. Crop phenotyping under field conditions has recently become another important application that requires specific needs: the considered remote-sensing method must be (1) as accurate as possible so that slight differences in phenotype can be detected and related to genotype, and (2) robust so that thousands of cultivars potentially quite different in terms of plant architecture can be characterized with a similar accuracy over different years and soil and weather conditions. In this study, the potential of nadir and off-nadir ground-based spectro-radiometric measurements to remotely sense five plant traits relevant for field phenotyping, namely, the leaf area index (LAI), leaf chlorophyll and nitrogen contents, and canopy chlorophyll and nitrogen contents, was evaluated over fourteen sugar beet (Beta vulgaris L.) cultivars, two years and three study sites. Among the diversity of existing remote-sensing methods, two popular approaches based on various selected Vegetation Indices (VI) and PROSAIL inversion were compared, especially in the perspective of using them for phenotyping applications. Overall, both approaches are promising to remotely estimate LAI and canopy chlorophyll content (RMSE'10%). In addition, VIs show a great potential to retrieve canopy nitrogen content (RMSE=10%). On the other hand, the estimation of leaf-level quantities is less accurate, the best accuracy being obtained for leaf chlorophyll content estimation based on VIs (RMSE=17%). As expected when observing the relationship between leaf chlorophyll and nitrogen contents, poor correlations are found between VIs and mass-based or area-based leaf nitrogen content. Importantly, the estimation accuracy is strongly dependent on sun-sensor geometry, the structural and biochemical plant traits being generally better estimated based on nadir and off-nadir observations, respectively. Ultimately, a preliminary comparison tends to indicate that, providing that enough samples are included in the calibration set, (1) VIs provide slightly more accurate performances than PROSAIL inversion, (2) VIs and PROSAIL inversion do not show significant differences in robustness across the different cultivars and years. Even if more data are still necessary to draw definitive conclusions, the results obtained with VIs are promising in the perspective of high-throughput phenotyping using UAV-embedded multispectral cameras, with which only a few wavebands are available.

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    CemOA
    2017
    Data sources: CemOA
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      CemOA
      2017
      Data sources: CemOA
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    Authors: Fayad, I.; Baghdadi, N.; Bailly, J.S.; Barbier, N.; +5 Authors

    LiDAR (Light Detection And Ranging) remote sensing has been shown to be a good technique for the estimation of forest parameters such as canopy heights and above ground biomass. Whilst airborne LiDAR data are in general very dense but only available over small areas due to the cost of their acquisition, spaceborne LiDAR data acquired from the Geoscience Laser Altimeter System (GLAS) have a coarser acquisition density associated with a global cover. It is therefore valuable to analyze the integration relevance of canopy heights estimated from LiDAR sensors with ancillary data such as geological, meteorological, and phenological variables in order to propose a forest canopy height map with good precision and high spatial resolution. In this study, canopy heights extracted from both airborne and spaceborne LiDAR, were first extrapolated from available environmental data (e.g. geology, slope, vegetation indices, etc.). The estimated canopy height maps using random forest (RF) regression from the airborne or GLAS calibration datasets showed similar precisions (RMSE better than 6.5 m). In order to improve the precision of the canopy height estimates regression-kriging (kriging of random forest regression residuals) was used. Results indicated an improvement in the RMSE (decrease from 6.5 to 4.2 m) for the regression-kriging maps from the GLAS dataset, and from 5.8 to 1.8 m for the regression-kriging map from the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on the precision of canopy height estimates, six subsets were derived from the initial airborne LiDAR dataset with flight line spacing of 5, 10, 20, 30, 40 and 50 km (corresponding to 0.29, 0.11, 0.08, 0.05, 0.04, and 0.03 points/km² respectively). Results indicated that using the regression-kriging approach achieved a precision of 1.8 m on the canopy height map with flight line spacing of 5 km and achieved an average RMSE of 4.8m for the configuration for the 50 km flight line spacing.

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    CemOA
    2015
    Data sources: CemOA
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    CemOA
    2016
    Data sources: CemOA
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      CemOA
      2015
      Data sources: CemOA
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      CemOA
      2016
      Data sources: CemOA
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Rajab Pourrahmati, M.;

    The importance of measuring forest biophysical parameters for ecosystem health monitoring and forest management encourages researchers to find precise, yet low-cost methods especially in mountainous and large areas. In the present study Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice Cloud and land Elevation Satellite) was used to estimate three biophysical characteristics of forests located in the north of Iran: 1) maximum canopy height (Hmax), 2) Lorey's height (HLorey), and 3) Forest volume (V). A large number of Multiple Linear Regressions (MLR), Random Forest (RF) and also Artificial Neural Network regressions were developed using two different sets of variables including waveform metrics and Principal Components (PCs) produced from Principal Component Analysis (PCA). To validate and compare models, statistical criteria were calculated based on a five-fold cross validation. Best model concerning the maximum height was an MLR (RMSE=5.0m) which combined two metrics extracted from waveforms (waveform extent "Wext" and height at 50% of waveform energy "H50"), and one from Digital Elevation Model (Terrain Index: TI). The mean absolute percentage error (MAPE) of maximum height estimates was 16.4%. For Lorey's height, an ANN model using PCs and waveform extent 'Wext' outperformed other models (RMSE=3.4m, MAPE=12.3%). In order to estimate forest volume, two approaches was employed: First, estimating volume using volume-height relationship while height is GLAS estimated height; Second, estimation of forest volume directly from GLAS data by developing regressions between in situ volume and GLAS metrics. The result from first approach (116.3 m3/ha) was slightly better than the result obtained by the second approach that is a PCs-based ANN model (119.9 m3/ha). But the ANN model performed better in very low ( 800 m3/ha) volume stands. In total, the relative error of estimated forest volume was about 26%. Generally, MLR and ANN models had better performance when compared to the RF models. In addition, the accuracy of height estimations using waveform metrics was better than those based on PCs. Given the suitable results of GLAS height models (maximum and Lorey's heights), production of wall to wall height maps from synergy of remote sensing (GLAS, PALSAR, SPOT5 and Landsat-TM) and environmental data (slope, aspect, classified elevation map and also geological map) was taken under consideration. Thus, MLR and RF régressions were built between all GLAS derived heights, inside of the study area, and indices extracted from mentioned remotely sensed and environmental data. The best resulted models for Hmax (RMSE=7.4m and Ra2=0.52) and HLorey (RMSE=5.5m and Ra2=0.59) were used to produce a wall to wall maximum canopy height and Lorey' height maps. Comparison of Hmax extracted from the resulted Hmax map with true height values at the location of 32 in situ plots produced an RMSE and R2 of 5.3m and 0.71, respectively. Such a comparison for HLorey led to an RMSE and R2 of 4.3m and 0.50, respectively. Regression-kriging method was also used to produce canopy height map with considering spatial correlation between canopy heights. This approach, with the aim of improving the precision of canopy height map provided from non-spatial method, was unsuccessful which could be due to the heterogeneity of the study area in case of forest structure and topography. / L'importance de mesurer les paramètres biophysiques de la forêt pour la surveillance de la santé des écosystèmes et la gestion forestière encourage les chercheurs à trouver des méthodes précises et à faible coût en particulier sur les zones étendues et montagneuses. Dans la présente étude, Le lidar satellitaire GLAS (Geoscience Laser Altimeter System) embarqué à bord du satellite ICESat (Ice Cloud and land Elevation Satellite) a été utilisé pour estimer trois caractéristiques biophysiques des forêts situées dans le nord de l'Iran: 1) hauteur maximale de la canopée (Hmax), 2) hauteur de Lorey (HLorey), et 3) le volume du bois (V). Des régressions linéaires multiples (RLM), des modèles basés sur les Forêts Aléatoires (FA : Random Forest) et aussi des réseaux de neurones (ANN) ont été développés à l'aide de deux ensembles différents de variables incluant des métriques obtenues à partir des formes d'onde GLAS et des composantes principales (CP) produites à partir de l'analyse en composantes principales (ACP) des données GLAS. Pour valider et comparer les modèles, des critères statistiques ont été calculées sur la base d'une validation croisée. Le meilleur modèle pour l'estimation de la hauteur maximale a été obtenu avec une régression RLM (RMSE = 5.0 m) qui combine deux métriques extraites des formes d'onde GLAS (étendue et hauteur pour une énergie à 50%, respectivement Wext et H50), et un paramètre issu du modèle numérique d'élévation (Indice de relief TI). L'erreur moyenne absolue en pourcentage (MAPE) sur les estimations de la hauteur maximale est de 16.4%. Pour la hauteur de Lorey, un modèle basé sur les réseaux de neurones et utilisant des CPs et le Wext fournit le meilleur résultat avec RMSE = 3.4 m et MAPE = 12.3%. Afin d'estimer le volume du bois, deux approches ont été utilisées: (1) estimation du volume à l'aide d'une relation volume-hauteur avec une hauteur estimée à partir de données GLAS et (2) estimation du volume du bois directement à partir des données GLAS en développant des régressions entre le volume in situ et les métriques GLAS. Le résultat de la première approche (RMSE=116.3 m3/ha) était légèrement meilleur que ceux obtenus avec la seconde approche. Par exemple, le réseau de neurones basé sur les PCs donnait un RMSE de 119.9 m3/ha mais avec des meilleurs résultats que l'approche basée sur la relation volume-hauteur pour les faibles ( 800 m3/ha) volumes. Au total, l'erreur relative sur le volume de bois est estimée à environ 26%. En général, les modèles RLM et ANN avaient des meilleures performances par rapport aux modèles de FA. En outre, la précision sur l'estimation de la hauteur à l'aide de métriques issues des formes d'onde GLAS est meilleure que celles basées sur les CPs. Compte tenu des bons résultats obtenus avec les modèles de hauteur GLAS (hauteurs maximale et de Lorey), la production de la carte des hauteurs d'étude par une utilisation combinée de données de télédétection lidar, radar et optique (GLAS, PALSAR, SPOT-5 et Landsat-TM) et de données environnementales (pente, aspect, et altitude du terrain ainsi que la carte géologique) a été effectuée à l'intérieur de notre zone. Ainsi, des régressions RLM et FA ont été construites entre toutes les hauteurs dérivées des données GLAS, à l'intérieur de la zone d'étude, et les indices extraits des données de télédétection et des paramètres environnementaux. Les meilleurs modèles entrainés pour estimer Hmax (RMSE = 7.4 m et Ra2=0.52) et HLorey (RMSE = 5.5 m et Ra2=0.59) ont été utilisées pour produire les cartes de hauteurs. La comparaison des Hmax de la carte obtenue avec les valeurs de Hmax in situ à l'endroit de 32 parcelles produit un RMSE de 5.3 m et un R2 de 0.71. Une telle comparaison pour HLorey conduit à un RMSE de 4.3m et un R2 de 0.50. Une méthode de régression-krigeage a également été utilisée pour produire une carte des hauteurs en considérant la corrélation spatiale entre les hauteurs. Cette approche, testée dans le but d'améliorer la précision de la carte de la hauteur du couvert fournie par la méthode non-spatiale, a échouée due à l'hétérogénéité de la zone d'étude en termes de la structure forestière et de la topographie.

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    CemOA
    2016
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      CemOA
      2016
      Data sources: CemOA
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    Authors: Urretavizcaya, I.; Santesteban, L.G.; Tisseyre, B.; Guillaume, S.; +2 Authors

    Early definition of oenologically significant zones within a vineyard is one of the main goals of precision viticulture, as it would allow an increase in profitability through the adaptation of agronomic practices to the specific requirements of each zone, and/or segregation of the harvest into different batches to produce wines with different qualities. The aim of this work was to evaluate whether early grape sampling is a relevant tool for within-vineyard zone definition. The study was carried out in 2010 and 2011 in a 4.2 ha vineyard, where a grid of 60 sampling points was defined. 300-berry samples were picked from each sampling point after veraison and at harvest, post-veraison information being used to define zones within the vineyard after fuzzy k-means analysis and subsequent application of a zoning procedure that took into account membership degree and neighbourhood criteria. Two variations of the zoning procedure were used, standard (StdZ) and top (TopZ) zoning. Each was designed to meet different requirements of wineries; StdZ gave the same oenological relevance to all the zones, and TopZ differentiated the zones producing "top class" grapes, minimizing the within-zone variability in the top-class zone. Grape composition obtained at harvest from the zones delineated post-veraison was compared. Zone delineation using post-veraison data was proved to be oenologically relevant, provided sampling is performed once veraison is completed. The two zoning algorithms designed were shown to be suitable for objective zone delineation according to the goals intended for each.

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    CemOA
    2014
    Data sources: CemOA
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      CemOA
      2014
      Data sources: CemOA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Naud, O.; Verges, A.; Hebrard, O.; Codis, S.; +2 Authors

    National policies in Europe aim to reduce use of pesticides. Grapevine receives yearly many sprayings. There is a great variety of sprayers available for vineyards. We can sum up ques-tions addressed to research bodies by the following issues. Is it possible to sort out sprayers and practices according to crop protection and environmental performances? How much is it possible to save on amounts of chemicals sprayed when one uses an efficient sprayer? The present contribution to this research is based on a 4 rows, 10 meters length, physical full scale model of a vineyard. The Evasprayviti model of a vineyard row was designed to repro-duce different foliage volume and densities and to simulate the interaction of the canopy with the flow of plant protection product and air emitted by a mobile sprayer. It comprises a col-lecting device, and a complementary structure on each side of it. The collecting device ena-bles accurate and repeatable sampling of the spray deposits. It is composed of plastic sheets that simulate leaves, attached to vertical aluminium posts. The complementary structure pre-vents perturbative effects on the spray flow on the edges of the collecting device. Evasprayviti can be configured to simulate different growth stages (Codis&al, 2013). The test spray is a mix of a tracer, Tartrazine, and water. A standard pneumatic sprayer, an airblast sprayer and an air-assisted face to face sprayer were tested. The pneumatic sprayer was tested in 3 configurations, for spraying respectively 2, 3 and 4 rows at a time. The face to face sprayer and the airblast sprayer were configured to be used to spray 3 rows and 2 rows, respectively. The amount of product deposited in the canopy and its distribution according to depth and height of leaves was studied for early, intermediate and full growth stage, with respective Leaf Area Index (LAI) values of 0.24, 0.88 and 1.68 ha/ha. The sampling of a cross-section of the collecting device was divided in compartments (3 depths x 3 heights at full growth stage). Deposits on rows close to sprayer and on rows next to sprayer were compared when relevant. The mass of deposits per unit of leaf surface, normalised by amount sprayed per hectare of ground, was measured for each compartment. For precision assessment, this normalised deposit was divided by the reference potential deposit on the target, which is cal-culated for each growth stage according to the hypothesis that all the spray is homogeneous-ly deposited in the compartments. Results showed different deposition profiles, which are discussed. The face to face sprayer exhibited the best efficiency and homogeneity in full and intermediate growth stage, and best efficiency on early stage as well, with homogeneity comparable to the pneumatic sprayer's on this stage. The airblast sprayer used on two rows had a good overall efficiency for early and intermediate stages but a bad homogeneity at all stages.

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    CemOA
    2014
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      CemOA
      2014
      Data sources: CemOA
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    Authors: Ait Mouheb, N.; Schillings, J.; Al Muhammad, J.; Bendoula, R.; +3 Authors

    To better understand the physical and biological clogging in drip-irrigation, a study was conducted on the impacts of hydrodynamic conditions on clay particle deposition and biofilm development in drippers using an optical method. A transparent milli-fluidic system composed of labyrinth channels was used to identify areas most susceptible to particle clogging using two different types of clay suspensions: sodium bentonite and kaolin. The impact of salt addition [(NaCl) = 200 mg L

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    CemOA
    2019
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      CemOA
      2019
      Data sources: CemOA
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    Authors: El Hajj, M.;

    In the context of increasing the pressure on water resources, the search for improved agricultural productivity of irrigation water leads to irrigation schedule optimization according to soil water conditions and crop development stages. Spatial remote sensing currently provides spatialized near real-time information of soil and vegetation characteristics. In particular, radar data, which showed a high potential for estimating soil moisture. Similarly, the optical data have long been used to estimate the vegetation parameters (biomass, yield). Such information can be integrated into crop models to predict yield evolution in real-time. The general aim of the thesis is to show how the information derived from remote sensing data with high spatial and temporal resolution can restore the water and vegetative dynamics of an irrigated perimeter. The approach is based on experiments conducted on a system of irrigated grasslands, with spatial and ground observations at high time repetitiveness, and the use of a crop model. The first part of the thesis evaluates the potential of radar data for cultivated soil water status monitoring. The X-band (3 cm wavelength) was chosen since X-band radar sensors allow plots monitoring with a high revisit time, and image acquisition at fine spatial resolution (about 1m), adapted to plots with small size. Results showed that the X-band radar signal allows soil moisture evolution monitoring even in the presence of a dense vegetation cover. In addition, results showed that the radar data are able to identify the water supplies even if the radar image is acquired three days after the irrigation event. The second part evaluates the potential of radar-optical coupling to estimate soil moisture in the presence of vegetation. The results showed that HH polarization combined with one vegetation parameter, derived from the optical data, allow soil moisture estimation with an accuracy around 5 vol.%. The methodology developed in this section of the thesis provides a multi-sensor approach (optical and radar) for operational soil moisture mapping in the presence of vegetation. The third part of the thesis study the potential of spatial data (radar and optical) to feed a crop model representing real-time biomass evolution. This part is based on the PILOTE model, which allows the prediction of crop sensitivity to water stress, and integrate criteria for irrigation launching and grassland harvest. Results showed that the integration of spatial data information estimates (LAI, harvest and irrigation dates) into PILOTE provides a good accuracy in yield prediction. The relevance of spatial information can then be analyzed in terms of acquisition frequency and accuracy of estimations produced, opening perspectives for the application of high temporal resolution remote sensing for the supervision and management of water supply in irrigated areas. / Dans un contexte d'accroissement des tensions sur les ressources en eau, la recherche d'une meilleure productivité agricole de l'eau d'irrigation amène à optimiser les calendriers d'arrosage en fonction des états hydriques des sols et des stades de développement de la culture. La télédétection spatiale permet aujourd'hui de fournir des informations spatialisées en temps quasi-réel sur les caractéristiques du sol et de la végétation. En particulier, les données radar ont montré un fort potentiel pour l'estimation de l'humidité du sol. De même, les données optiques sont utilisées depuis longtemps pour estimer les paramètres relatifs à la végétation (indice foliaire, biomasse, rendement). Ces informations peuvent être intégrées dans des modèles de culture pour simuler en temps réel l'évolution du rendement. L'objectif général de la thèse est de montrer comment les informations issues de la télédétection spatiale à haute résolution spatio-temporelle permettent de retrouver les dynamiques hydriques et végétatives d'un périmètre irrigué. La démarche repose sur des expérimentations menées sur un système de prairies irriguées, avec des observations spatiales et au sol à haute répétitivité temporelle, et l'utilisation d'un modèle de culture. Le premier volet de la thèse évalue le potentiel des données radar à suivre l'état hydrique d'un sol cultivé. La bande X (3 cm de longueur d'onde) a été choisie puisque les capteurs radar en bande X permettent un suivi des parcelles avec une forte répétitivité temporelle, et des acquisitions à une très haute résolution spatiale (environ 1 m), adaptée à des parcelles de petite taille. Les résultats ont montré que le signal radar en bande X permet de suivre l'évolution de l'humidité du sol même en présence d'un couvert végétal dense. De plus, les résultats ont montré que les données radar sont capables d'identifier les apports d'eau même si l'image radar est acquise trois jours après l'achèvement de l'irrigation. Le deuxième volet évalue le potentiel du couplage radar-optique pour estimer l'humidité du sol en présence de la végétation. Les résultats ont montré que la polarisation HH combinée avec un paramètre de la végétation, dérivée à partir des données optiques, permet d'estimer l'humidité du sol avec une précision de l'ordre de 5 vol.%. La méthodologie développée dans cette partie de la thèse permet de proposer une approche multi-capteur (optique et radar) pour une cartographie opérationnelle de l'humidité du sol en présence de végétation. La troisième partie de la thèse étudie le potentiel des données spatiales (radar et optique) pour alimenter un modèle de culture représentant l'évolution de la biomasse en temps réel. Cette partie s'appuie sur le modèle PILOTE, permettant de prédire la sensibilité de la culture au stress hydrique, et d'intégrer des critères de déclenchement des arrosages et de fauche des prairies. Les résultats ont montré que l'intégration dans PILOTE d'informations estimées à partir des données spatiales (LAI, dates des coupes et irrigations) permet de prédire le rendement avec une bonne précision. La pertinence des informations spatiales peut ainsi être analysée en termes de fréquence d'acquisition et de précision des estimations produites, ouvrant des perspectives pour l'application de la télédétection à haute résolution temporelle à la supervision et la gestion des apports d'eau dans les périmètres irrigués.

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    CemOA
    2016
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      CemOA
      2016
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    Authors: Fatras, C.; Borderies, P.; Baghdadi, N.; Zribi, M.; +3 Authors

    The behavior of the Ka-band backscattering coefficient at nadir and close-to-nadir angles for land applications is poorly documented. The measurements made during a ground-based campaign at Ka-band were performed at nadir and close-to-nadir angles over bare soils for different surface roughness and soil moisture conditions. The resulting backscattering levels exhibited a dynamic range of approximately 23 dB at nadir for soil moisture contents between 5 and 50 % m3/m3 over both smooth and rough surfaces. These results were then compared to the Geometrical Optics (GO) and Millimeter MicroWave (MMW) models. Generally, GO finely fit the backscattering coefficients close to nadir, and MMW appeared to fit for larger incidence angles or rough surfaces. The results obtained in this study can address pre-launch science and engineering considerations for the interferometry-altimetry SWOT mission operating at Ka-band.

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    CemOA
    2016
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      CemOA
      2016
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    Authors: Viet Nguyen, L.; Tateishi, R.; Kondoh, A.; Sharma, R.C.; +3 Authors

    This research was carried out in a dense tropical forest region with the objective of improving the biomass estimates by a combination of ALOS-2 SAR, Landsat 8 optical, and field plots data. Using forest inventory based biomass data, the performance of different parameters from the two sensors was evaluated. The regression analysis with the biomass data showed that the backscatter from forest object (σ°forest) obtained from the SAR data was more sensitive to the biomass than HV polarization, SAR textures, and maximum NDVI parameters. However, the combination of the maximum NDVI from optical data, SAR textures from HV polarization, and σ°forest improved estimates of the biomass. The best model derived by the combination of multiple parameters from ALOS-2 SAR and Landsat 8 data was validated with inventory data. Then, the best validated model was used to produce an up-to-date biomass map for 2015 in Yok Don National Park, which is an important conservation area in Vietnam. The validation results showed that 74% of the variation of in biomass could be explained by our model.

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    CemOA
    2016
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      CemOA
      2016
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    Authors: Pedret A; Catalán Ú; Rubió L; Baiges I; +7 Authors

    © 2020 American Chemical Society. All rights reserved. Protein functional interactions could explain the biological response of secoiridoids (SECs), main phenolic compounds in virgin olive oil (VOO). The aim was to assess protein-protein interactions (PPIs) of the aorta gap junction alpha-1 (GJA1) and the heart peptidyl-prolyl cis-trans isomerase (FKBP1A), plus the phosphorylated heart proteome, to describe new molecular pathways in the cardiovascular system in rats using nanoliquid chromatography coupled with mass spectrometry. PPIs modified by SECs and associated with GJA1 in aorta rat tissue were calpain, TUBA1A, and HSPB1. Those associated with FKBP1A in rat heart tissue included SUCLG1, HSPE1, and TNNI3. In the heart, SECs modulated the phosphoproteome through the main canonical pathways PI3K/mTOR signaling (AKT1S1 and GAB2) and gap junction signaling (GAB2 and GJA1). PPIs associated with GJA1 and with FKBP1A, the phosphorylation of GAB2, and the dephosphorylation of GJA1 and AKT1S1 in rat tissues are promising protein targets promoting cardiovascular protection to explain the health benefits of VOO.

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    Authors: Jay, S.; Maupas, F.; Bendoula, R.; Gorretta, N.;

    Remote sensing has gained much attention for agronomic applications such as crop management or yield estimation. Crop phenotyping under field conditions has recently become another important application that requires specific needs: the considered remote-sensing method must be (1) as accurate as possible so that slight differences in phenotype can be detected and related to genotype, and (2) robust so that thousands of cultivars potentially quite different in terms of plant architecture can be characterized with a similar accuracy over different years and soil and weather conditions. In this study, the potential of nadir and off-nadir ground-based spectro-radiometric measurements to remotely sense five plant traits relevant for field phenotyping, namely, the leaf area index (LAI), leaf chlorophyll and nitrogen contents, and canopy chlorophyll and nitrogen contents, was evaluated over fourteen sugar beet (Beta vulgaris L.) cultivars, two years and three study sites. Among the diversity of existing remote-sensing methods, two popular approaches based on various selected Vegetation Indices (VI) and PROSAIL inversion were compared, especially in the perspective of using them for phenotyping applications. Overall, both approaches are promising to remotely estimate LAI and canopy chlorophyll content (RMSE'10%). In addition, VIs show a great potential to retrieve canopy nitrogen content (RMSE=10%). On the other hand, the estimation of leaf-level quantities is less accurate, the best accuracy being obtained for leaf chlorophyll content estimation based on VIs (RMSE=17%). As expected when observing the relationship between leaf chlorophyll and nitrogen contents, poor correlations are found between VIs and mass-based or area-based leaf nitrogen content. Importantly, the estimation accuracy is strongly dependent on sun-sensor geometry, the structural and biochemical plant traits being generally better estimated based on nadir and off-nadir observations, respectively. Ultimately, a preliminary comparison tends to indicate that, providing that enough samples are included in the calibration set, (1) VIs provide slightly more accurate performances than PROSAIL inversion, (2) VIs and PROSAIL inversion do not show significant differences in robustness across the different cultivars and years. Even if more data are still necessary to draw definitive conclusions, the results obtained with VIs are promising in the perspective of high-throughput phenotyping using UAV-embedded multispectral cameras, with which only a few wavebands are available.

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    CemOA
    2017
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      CemOA
      2017
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    Authors: Fayad, I.; Baghdadi, N.; Bailly, J.S.; Barbier, N.; +5 Authors

    LiDAR (Light Detection And Ranging) remote sensing has been shown to be a good technique for the estimation of forest parameters such as canopy heights and above ground biomass. Whilst airborne LiDAR data are in general very dense but only available over small areas due to the cost of their acquisition, spaceborne LiDAR data acquired from the Geoscience Laser Altimeter System (GLAS) have a coarser acquisition density associated with a global cover. It is therefore valuable to analyze the integration relevance of canopy heights estimated from LiDAR sensors with ancillary data such as geological, meteorological, and phenological variables in order to propose a forest canopy height map with good precision and high spatial resolution. In this study, canopy heights extracted from both airborne and spaceborne LiDAR, were first extrapolated from available environmental data (e.g. geology, slope, vegetation indices, etc.). The estimated canopy height maps using random forest (RF) regression from the airborne or GLAS calibration datasets showed similar precisions (RMSE better than 6.5 m). In order to improve the precision of the canopy height estimates regression-kriging (kriging of random forest regression residuals) was used. Results indicated an improvement in the RMSE (decrease from 6.5 to 4.2 m) for the regression-kriging maps from the GLAS dataset, and from 5.8 to 1.8 m for the regression-kriging map from the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on the precision of canopy height estimates, six subsets were derived from the initial airborne LiDAR dataset with flight line spacing of 5, 10, 20, 30, 40 and 50 km (corresponding to 0.29, 0.11, 0.08, 0.05, 0.04, and 0.03 points/km² respectively). Results indicated that using the regression-kriging approach achieved a precision of 1.8 m on the canopy height map with flight line spacing of 5 km and achieved an average RMSE of 4.8m for the configuration for the 50 km flight line spacing.

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    CemOA
    2015
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    CemOA
    2016
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      CemOA
      2015
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      CemOA
      2016
      Data sources: CemOA
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    Authors: Rajab Pourrahmati, M.;

    The importance of measuring forest biophysical parameters for ecosystem health monitoring and forest management encourages researchers to find precise, yet low-cost methods especially in mountainous and large areas. In the present study Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice Cloud and land Elevation Satellite) was used to estimate three biophysical characteristics of forests located in the north of Iran: 1) maximum canopy height (Hmax), 2) Lorey's height (HLorey), and 3) Forest volume (V). A large number of Multiple Linear Regressions (MLR), Random Forest (RF) and also Artificial Neural Network regressions were developed using two different sets of variables including waveform metrics and Principal Components (PCs) produced from Principal Component Analysis (PCA). To validate and compare models, statistical criteria were calculated based on a five-fold cross validation. Best model concerning the maximum height was an MLR (RMSE=5.0m) which combined two metrics extracted from waveforms (waveform extent "Wext" and height at 50% of waveform energy "H50"), and one from Digital Elevation Model (Terrain Index: TI). The mean absolute percentage error (MAPE) of maximum height estimates was 16.4%. For Lorey's height, an ANN model using PCs and waveform extent 'Wext' outperformed other models (RMSE=3.4m, MAPE=12.3%). In order to estimate forest volume, two approaches was employed: First, estimating volume using volume-height relationship while height is GLAS estimated height; Second, estimation of forest volume directly from GLAS data by developing regressions between in situ volume and GLAS metrics. The result from first approach (116.3 m3/ha) was slightly better than the result obtained by the second approach that is a PCs-based ANN model (119.9 m3/ha). But the ANN model performed better in very low ( 800 m3/ha) volume stands. In total, the relative error of estimated forest volume was about 26%. Generally, MLR and ANN models had better performance when compared to the RF models. In addition, the accuracy of height estimations using waveform metrics was better than those based on PCs. Given the suitable results of GLAS height models (maximum and Lorey's heights), production of wall to wall height maps from synergy of remote sensing (GLAS, PALSAR, SPOT5 and Landsat-TM) and environmental data (slope, aspect, classified elevation map and also geological map) was taken under consideration. Thus, MLR and RF régressions were built between all GLAS derived heights, inside of the study area, and indices extracted from mentioned remotely sensed and environmental data. The best resulted models for Hmax (RMSE=7.4m and Ra2=0.52) and HLorey (RMSE=5.5m and Ra2=0.59) were used to produce a wall to wall maximum canopy height and Lorey' height maps. Comparison of Hmax extracted from the resulted Hmax map with true height values at the location of 32 in situ plots produced an RMSE and R2 of 5.3m and 0.71, respectively. Such a comparison for HLorey led to an RMSE and R2 of 4.3m and 0.50, respectively. Regression-kriging method was also used to produce canopy height map with considering spatial correlation between canopy heights. This approach, with the aim of improving the precision of canopy height map provided from non-spatial method, was unsuccessful which could be due to the heterogeneity of the study area in case of forest structure and topography. / L'importance de mesurer les paramètres biophysiques de la forêt pour la surveillance de la santé des écosystèmes et la gestion forestière encourage les chercheurs à trouver des méthodes précises et à faible coût en particulier sur les zones étendues et montagneuses. Dans la présente étude, Le lidar satellitaire GLAS (Geoscience Laser Altimeter System) embarqué à bord du satellite ICESat (Ice Cloud and land Elevation Satellite) a été utilisé pour estimer trois caractéristiques biophysiques des forêts situées dans le nord de l'Iran: 1) hauteur maximale de la canopée (Hmax), 2) hauteur de Lorey (HLorey), et 3) le volume du bois (V). Des régressions linéaires multiples (RLM), des modèles basés sur les Forêts Aléatoires (FA : Random Forest) et aussi des réseaux de neurones (ANN) ont été développés à l'aide de deux ensembles différents de variables incluant des métriques obtenues à partir des formes d'onde GLAS et des composantes principales (CP) produites à partir de l'analyse en composantes principales (ACP) des données GLAS. Pour valider et comparer les modèles, des critères statistiques ont été calculées sur la base d'une validation croisée. Le meilleur modèle pour l'estimation de la hauteur maximale a été obtenu avec une régression RLM (RMSE = 5.0 m) qui combine deux métriques extraites des formes d'onde GLAS (étendue et hauteur pour une énergie à 50%, respectivement Wext et H50), et un paramètre issu du modèle numérique d'élévation (Indice de relief TI). L'erreur moyenne absolue en pourcentage (MAPE) sur les estimations de la hauteur maximale est de 16.4%. Pour la hauteur de Lorey, un modèle basé sur les réseaux de neurones et utilisant des CPs et le Wext fournit le meilleur résultat avec RMSE = 3.4 m et MAPE = 12.3%. Afin d'estimer le volume du bois, deux approches ont été utilisées: (1) estimation du volume à l'aide d'une relation volume-hauteur avec une hauteur estimée à partir de données GLAS et (2) estimation du volume du bois directement à partir des données GLAS en développant des régressions entre le volume in situ et les métriques GLAS. Le résultat de la première approche (RMSE=116.3 m3/ha) était légèrement meilleur que ceux obtenus avec la seconde approche. Par exemple, le réseau de neurones basé sur les PCs donnait un RMSE de 119.9 m3/ha mais avec des meilleurs résultats que l'approche basée sur la relation volume-hauteur pour les faibles ( 800 m3/ha) volumes. Au total, l'erreur relative sur le volume de bois est estimée à environ 26%. En général, les modèles RLM et ANN avaient des meilleures performances par rapport aux modèles de FA. En outre, la précision sur l'estimation de la hauteur à l'aide de métriques issues des formes d'onde GLAS est meilleure que celles basées sur les CPs. Compte tenu des bons résultats obtenus avec les modèles de hauteur GLAS (hauteurs maximale et de Lorey), la production de la carte des hauteurs d'étude par une utilisation combinée de données de télédétection lidar, radar et optique (GLAS, PALSAR, SPOT-5 et Landsat-TM) et de données environnementales (pente, aspect, et altitude du terrain ainsi que la carte géologique) a été effectuée à l'intérieur de notre zone. Ainsi, des régressions RLM et FA ont été construites entre toutes les hauteurs dérivées des données GLAS, à l'intérieur de la zone d'étude, et les indices extraits des données de télédétection et des paramètres environnementaux. Les meilleurs modèles entrainés pour estimer Hmax (RMSE = 7.4 m et Ra2=0.52) et HLorey (RMSE = 5.5 m et Ra2=0.59) ont été utilisées pour produire les cartes de hauteurs. La comparaison des Hmax de la carte obtenue avec les valeurs de Hmax in situ à l'endroit de 32 parcelles produit un RMSE de 5.3 m et un R2 de 0.71. Une telle comparaison pour HLorey conduit à un RMSE de 4.3m et un R2 de 0.50. Une méthode de régression-krigeage a également été utilisée pour produire une carte des hauteurs en considérant la corrélation spatiale entre les hauteurs. Cette approche, testée dans le but d'améliorer la précision de la carte de la hauteur du couvert fournie par la méthode non-spatiale, a échouée due à l'hétérogénéité de la zone d'étude en termes de la structure forestière et de la topographie.

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    CemOA
    2016
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      CemOA
      2016
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    Authors: Urretavizcaya, I.; Santesteban, L.G.; Tisseyre, B.; Guillaume, S.; +2 Authors

    Early definition of oenologically significant zones within a vineyard is one of the main goals of precision viticulture, as it would allow an increase in profitability through the adaptation of agronomic practices to the specific requirements of each zone, and/or segregation of the harvest into different batches to produce wines with different qualities. The aim of this work was to evaluate whether early grape sampling is a relevant tool for within-vineyard zone definition. The study was carried out in 2010 and 2011 in a 4.2 ha vineyard, where a grid of 60 sampling points was defined. 300-berry samples were picked from each sampling point after veraison and at harvest, post-veraison information being used to define zones within the vineyard after fuzzy k-means analysis and subsequent application of a zoning procedure that took into account membership degree and neighbourhood criteria. Two variations of the zoning procedure were used, standard (StdZ) and top (TopZ) zoning. Each was designed to meet different requirements of wineries; StdZ gave the same oenological relevance to all the zones, and TopZ differentiated the zones producing "top class" grapes, minimizing the within-zone variability in the top-class zone. Grape composition obtained at harvest from the zones delineated post-veraison was compared. Zone delineation using post-veraison data was proved to be oenologically relevant, provided sampling is performed once veraison is completed. The two zoning algorithms designed were shown to be suitable for objective zone delineation according to the goals intended for each.

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    CemOA
    2014
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      CemOA
      2014
      Data sources: CemOA