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Volumn 57, Issue , 2017, Pages 14-23

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

Author keywords

Artificial neural networks; Corn; Forecast; Formosat 2; Microwave; Optical; Radarsat 2; Spot 4 5; TerraSAR X; Yield estimates

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CROP YIELD; ESTIMATION METHOD; FORECASTING METHOD; FORMOSAT; MAIZE; RADAR; RADARSAT; SATELLITE DATA; TERRASAR-X;

EID: 85032195573     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2016.12.011     Document Type: Article
Times cited : (88)

References (60)
  • 2
    • 0026291736 scopus 로고
    • SPOT 4: a new generation of SPOT satellites
    • Arnaud, M., Leroy, M., SPOT 4: a new generation of SPOT satellites. ISPRS J. Photogramm. Remote Sens. 46:4 (1991), 205–215.
    • (1991) ISPRS J. Photogramm. Remote Sens. , vol.46 , Issue.4 , pp. 205-215
    • Arnaud, M.1    Leroy, M.2
  • 3
    • 0001371584 scopus 로고
    • Estimating absorbed photosynthetic radiation and leaf-area index from spectral reflectance in wheat
    • Asrar, G., Fuchs, M., Kanemasu, E.T., Hatfield, J.L., Estimating absorbed photosynthetic radiation and leaf-area index from spectral reflectance in wheat. Agron. J. 76 (1984), 300–306.
    • (1984) Agron. J. , vol.76 , pp. 300-306
    • Asrar, G.1    Fuchs, M.2    Kanemasu, E.T.3    Hatfield, J.L.4
  • 5
    • 0026305589 scopus 로고
    • Potentials and limits of vegetation indexes for LAI and APAR assessment
    • Baret, F., Guyot, G., Potentials and limits of vegetation indexes for LAI and APAR assessment. Remote Sens. Environ. 35 (1991), 161–173.
    • (1991) Remote Sens. Environ. , vol.35 , pp. 161-173
    • Baret, F.1    Guyot, G.2
  • 6
    • 84989829890 scopus 로고    scopus 로고
    • Estimating maize biomass and yield over large areas using high spatial and temporal resolution Sentinel-2 like remote sensing data
    • Battude, M., Al Bitar, A., Morin, D., Cros, J., Huc, M., Marais Sicre, C., Le Dantec, V., Demarez, V., Estimating maize biomass and yield over large areas using high spatial and temporal resolution Sentinel-2 like remote sensing data. Remote Sens. Environ. 184 (2016), 668–681.
    • (2016) Remote Sens. Environ. , vol.184 , pp. 668-681
    • Battude, M.1    Al Bitar, A.2    Morin, D.3    Cros, J.4    Huc, M.5    Marais Sicre, C.6    Le Dantec, V.7    Demarez, V.8
  • 9
    • 85029022692 scopus 로고    scopus 로고
    • Sensitivity of X-band (σ°, γ) and optical (NDVI) satellite data to corn biophysical parameters
    • Baup, F., Villa, L., Fieuzal, R., Ameline, M., Sensitivity of X-band (σ°, γ) and optical (NDVI) satellite data to corn biophysical parameters. Adv. Remote Sens. 5 (2016), 103–117.
    • (2016) Adv. Remote Sens. , vol.5 , pp. 103-117
    • Baup, F.1    Villa, L.2    Fieuzal, R.3    Ameline, M.4
  • 10
    • 84979725341 scopus 로고    scopus 로고
    • Assimilation of LAI and Dry Biomass data from optical and SAR images into an agro-meteorological model to estimate soybean yield
    • Betbeder, J., Fieuzal, R., Baup, F., Assimilation of LAI and Dry Biomass data from optical and SAR images into an agro-meteorological model to estimate soybean yield. IEEE J. Select. Topics Appl. Earth Observ. Remote Sens. 9:6 (2016), 2540–2553.
    • (2016) IEEE J. Select. Topics Appl. Earth Observ. Remote Sens. , vol.9 , Issue.6 , pp. 2540-2553
    • Betbeder, J.1    Fieuzal, R.2    Baup, F.3
  • 11
    • 84977641072 scopus 로고    scopus 로고
    • Contribution of multi-temporal polarimetric SAR data for monitoring winter wheat and rapeseed crops
    • Betbeder, J., Fieuzal, R., Philippets, Y., Ferro-Famil, L., Baup, F., Contribution of multi-temporal polarimetric SAR data for monitoring winter wheat and rapeseed crops. J. Appl. Remote Sens., 10(2), 2016, 026020.
    • (2016) J. Appl. Remote Sens. , vol.10 , Issue.2 , pp. 026020
    • Betbeder, J.1    Fieuzal, R.2    Philippets, Y.3    Ferro-Famil, L.4    Baup, F.5
  • 13
    • 53249115287 scopus 로고    scopus 로고
    • Taiwan's second remote sensing satellite
    • Chern, J.-S., Ling, J., Weng, S.-L., Taiwan's second remote sensing satellite. Acta Astronaut. 63:11–12 (2008), 1305–1311.
    • (2008) Acta Astronaut. , vol.63 , Issue.11-12 , pp. 1305-1311
    • Chern, J.-S.1    Ling, J.2    Weng, S.-L.3
  • 15
    • 85065100595 scopus 로고    scopus 로고
    • Direction Régionale De l'Alimentation
    • de l'Agriculture et de la Forêt Languedoc-Roussillon-Midi-Pyrénées
    • DRAAF, Direction Régionale De l'Alimentation. 2016, de l'Agriculture et de la Forêt Languedoc-Roussillon-Midi-Pyrénées http://draaf.languedoc-roussillon-midi-pyrenees.agriculture.gouv.fr/.
    • (2016)
    • DRAAF1
  • 16
    • 84923543554 scopus 로고    scopus 로고
    • Wheat yield forecasting for punjab province from vegetation index time series and historic crop statistics
    • Dempewolf, J., Adusei, B., Becker-Reshef, I., Hansen, M., Potapov, P., Khan, A., Barker, B., Wheat yield forecasting for punjab province from vegetation index time series and historic crop statistics. Remote Sens. 6 (2014), 9653–9675.
    • (2014) Remote Sens. , vol.6 , pp. 9653-9675
    • Dempewolf, J.1    Adusei, B.2    Becker-Reshef, I.3    Hansen, M.4    Potapov, P.5    Khan, A.6    Barker, B.7
  • 17
    • 40649093793 scopus 로고    scopus 로고
    • Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield
    • Dente, L., Satalino, G., Mattia, F., Rinaldi, M., Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield. Remote Sens. Environ. 112 (2008), 1395–1407.
    • (2008) Remote Sens. Environ. , vol.112 , pp. 1395-1407
    • Dente, L.1    Satalino, G.2    Mattia, F.3    Rinaldi, M.4
  • 18
    • 84930032716 scopus 로고    scopus 로고
    • Impact of sowing date on yield and water-use-efficiency of wheat analyzed through spatial modeling and FORMOSAT-2 images
    • Duchemin, B., Fieuzal, R., Rivera, M.A., Ezzahar, J., Jarlan, L., Rodriguez, J.C., Hagolle, O., Watts, C., Impact of sowing date on yield and water-use-efficiency of wheat analyzed through spatial modeling and FORMOSAT-2 images. Remote Sens. 7 (2015), 5951–5979.
    • (2015) Remote Sens. , vol.7 , pp. 5951-5979
    • Duchemin, B.1    Fieuzal, R.2    Rivera, M.A.3    Ezzahar, J.4    Jarlan, L.5    Rodriguez, J.C.6    Hagolle, O.7    Watts, C.8
  • 19
    • 85065096740 scopus 로고    scopus 로고
    • HYdraulic PRoperties of European Soils (HYPRES). Texture Classes
    • (HYPRES Website. Available online:)
    • European Soil Bureau working group, HYdraulic PRoperties of European Soils (HYPRES). Texture Classes. 2016 (HYPRES Website. Available online: http://www.macaulay.ac.uk/hypres/hypressoil.html).
    • (2016)
    • European Soil Bureau working group1
  • 20
    • 43049100761 scopus 로고    scopus 로고
    • Corn yield estimation through assimilation of remotely sensed data into the CSM‐CERES Maize model
    • Fang, H., Liang, S., Hoogenboom, G., Teasdale, J., Cavigelli, M., Corn yield estimation through assimilation of remotely sensed data into the CSM‐CERES Maize model. Int. J. Remote Sens. 29:10 (2008), 3011–3032.
    • (2008) Int. J. Remote Sens. , vol.29 , Issue.10 , pp. 3011-3032
    • Fang, H.1    Liang, S.2    Hoogenboom, G.3    Teasdale, J.4    Cavigelli, M.5
  • 21
    • 84973928852 scopus 로고    scopus 로고
    • Estimation of leaf area index and crop height of sunflowers using multi-temporal optical and SAR satellite data
    • Fieuzal, R., Baup, F., Estimation of leaf area index and crop height of sunflowers using multi-temporal optical and SAR satellite data. Int. J. Remote Sens. – RADARSAT-2: Appl. 37:12 (2016), 2780–2809.
    • (2016) Int. J. Remote Sens. – RADARSAT-2: Appl. , vol.37 , Issue.12 , pp. 2780-2809
    • Fieuzal, R.1    Baup, F.2
  • 22
  • 24
    • 84886652203 scopus 로고    scopus 로고
    • Monitoring wheat and rapeseed by using synchronous optical and radar satellite data—from temporal signatures to crop parameters estimation
    • Fieuzal, R., Baup, F., Marais-Sicre, C., Monitoring wheat and rapeseed by using synchronous optical and radar satellite data—from temporal signatures to crop parameters estimation. Adv. Remote Sens. 2:2 (2013), 162–180.
    • (2013) Adv. Remote Sens. , vol.2 , Issue.2 , pp. 162-180
    • Fieuzal, R.1    Baup, F.2    Marais-Sicre, C.3
  • 25
    • 85065078212 scopus 로고    scopus 로고
    • Estimation of sunflower yield using a simplified agro-meteorological model controlled by multi-spectral satellite data (optical or radar), under review in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
    • Fieuzal, R., Marais-Sicre, C., Baup, F., 2016. Estimation of sunflower yield using a simplified agro-meteorological model controlled by multi-spectral satellite data (optical or radar), under review in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
    • (2016)
    • Fieuzal, R.1    Marais-Sicre, C.2    Baup, F.3
  • 26
    • 78649558433 scopus 로고    scopus 로고
    • TerraSAR-X Ground Segment Basic Product Specification Document
    • DLR London p. 103
    • Fritz, T., Eineder, M., Mittermayer, J., Roth, A., Börner, E., Breit, H., TerraSAR-X Ground Segment Basic Product Specification Document. 2008, DLR, London p. 103.
    • (2008)
    • Fritz, T.1    Eineder, M.2    Mittermayer, J.3    Roth, A.4    Börner, E.5    Breit, H.6
  • 27
    • 33646491431 scopus 로고    scopus 로고
    • A two-way interaction of input variables in an artificial neural network model
    • Gevrey, M., Dimopoulos, I., Lek, S., A two-way interaction of input variables in an artificial neural network model. Ecol. Modell. 195 (2006), 43–50.
    • (2006) Ecol. Modell. , vol.195 , pp. 43-50
    • Gevrey, M.1    Dimopoulos, I.2    Lek, S.3
  • 28
    • 1842431418 scopus 로고    scopus 로고
    • Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture
    • Haboudane, D., Miller, J.R., Pattey, E., Zarco-Tejada, P.J., Strachan, I.B., Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture. Remote Sens. Environ. 90:3 (2004), 337–352.
    • (2004) Remote Sens. Environ. , vol.90 , Issue.3 , pp. 337-352
    • Haboudane, D.1    Miller, J.R.2    Pattey, E.3    Zarco-Tejada, P.J.4    Strachan, I.B.5
  • 29
    • 40949131913 scopus 로고    scopus 로고
    • Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: application to Formosat-2 images
    • Hagolle, O., Dedieu, G., Mougenot, B., Debaecker, V., Duchemin, B., Meygret, A., Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: application to Formosat-2 images. Remote Sens. Environ. 112:4 (2008), 1689–1701.
    • (2008) Remote Sens. Environ. , vol.112 , Issue.4 , pp. 1689-1701
    • Hagolle, O.1    Dedieu, G.2    Mougenot, B.3    Debaecker, V.4    Duchemin, B.5    Meygret, A.6
  • 30
    • 0242488102 scopus 로고    scopus 로고
    • The potential of remote sensing data for decision makers at the state, local and tribal level: experiences from NASA's syn- ergy program
    • Kalluri, S., Gilruth, P., Bergman, R., The potential of remote sensing data for decision makers at the state, local and tribal level: experiences from NASA's syn- ergy program. Environ. Sci. Policy 6:6 (2003), 487–500.
    • (2003) Environ. Sci. Policy , vol.6 , Issue.6 , pp. 487-500
    • Kalluri, S.1    Gilruth, P.2    Bergman, R.3
  • 31
    • 84923626148 scopus 로고    scopus 로고
    • Assessing the performance of MODIS NDVI and EVI for seasonal crop yield forecasting at the ecodistrict scale
    • Kouadio, L., Newlands, N.K., Davidson, A., Zhang, Y., Chipanshi, A., Assessing the performance of MODIS NDVI and EVI for seasonal crop yield forecasting at the ecodistrict scale. Remote Sens. 6 (2014), 10193–10214.
    • (2014) Remote Sens. , vol.6 , pp. 10193-10214
    • Kouadio, L.1    Newlands, N.K.2    Davidson, A.3    Zhang, Y.4    Chipanshi, A.5
  • 33
    • 0344604541 scopus 로고    scopus 로고
    • Artificial neural networks as a tool in ecological modelling. an introduction
    • Lek, S., Guegan, J.F., Artificial neural networks as a tool in ecological modelling. an introduction. Ecol. Modell. 120 (1999), 65–73.
    • (1999) Ecol. Modell. , vol.120 , pp. 65-73
    • Lek, S.1    Guegan, J.F.2
  • 36
    • 84901593748 scopus 로고    scopus 로고
    • Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images
    • Marais Sicre, C., Baup, F., Fieuzal, R., Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images. ISPRS J. Photogramm. Remote Sens. 94 (2014), 127–142.
    • (2014) ISPRS J. Photogramm. Remote Sens. , vol.94 , pp. 127-142
    • Marais Sicre, C.1    Baup, F.2    Fieuzal, R.3
  • 37
    • 85029032648 scopus 로고    scopus 로고
    • Early detection of summer crops using high spatio-temporal resolution optical images time series
    • Marais Sicre, C., Inglada, J., Fieuzal, R., Baup, F., Valero, S., Cros, J., Huc, M., Demarez, V., Early detection of summer crops using high spatio-temporal resolution optical images time series. Remote Sens., 8(7), 2016, 591.
    • (2016) Remote Sens. , vol.8 , Issue.7 , pp. 591
    • Marais Sicre, C.1    Inglada, J.2    Fieuzal, R.3    Baup, F.4    Valero, S.5    Cros, J.6    Huc, M.7    Demarez, V.8
  • 38
    • 84863513848 scopus 로고    scopus 로고
    • By-plant prediction of corn grain yield using optical sensor readings and measured plant height
    • Martin, K., Raun, W., Solie, J., By-plant prediction of corn grain yield using optical sensor readings and measured plant height. J. Plant Nutr. 35 (2012), 1429–1439.
    • (2012) J. Plant Nutr. , vol.35 , pp. 1429-1439
    • Martin, K.1    Raun, W.2    Solie, J.3
  • 41
    • 84859441310 scopus 로고    scopus 로고
    • Stades Phénologiques Des Mono- Et Dico-tylédones Cultivées
    • Centre Fédéral de Recherches Bio- logiques pour l‘Agriculture et les Forêts 2001
    • Meier, U., Stades Phénologiques Des Mono- Et Dico-tylédones Cultivées. 2001, Centre Fédéral de Recherches Bio- logiques pour l‘Agriculture et les Forêts, 2001 www.agroedieurope.fr/ref/doc/BBCH.pdf.
    • (2001)
    • Meier, U.1
  • 43
    • 4944259834 scopus 로고    scopus 로고
    • An introduction to the RADARSAT-2 mission
    • Morena, L.C., James, K.V., Beck, J., An introduction to the RADARSAT-2 mission. Can. J. Remote Sens. 30:3 (2004), 221–234, 10.5589/m04-004.
    • (2004) Can. J. Remote Sens. , vol.30 , Issue.3 , pp. 221-234
    • Morena, L.C.1    James, K.V.2    Beck, J.3
  • 44
    • 85065059866 scopus 로고    scopus 로고
    • Next ESA.SAR Toolbox.
    • Next ESA.SAR Toolbox. http://nest.array.ca/web/nest.
  • 45
    • 31044453033 scopus 로고    scopus 로고
    • Crop yield estimation model for Iowa using remote sensing and surface parameters
    • Prasad, A.K., Chai, L., Singh, R.P., Kafatos, M., Crop yield estimation model for Iowa using remote sensing and surface parameters. Int. J. Appl. Earth Obs. Geoinf. 8:1 (2006), 26–33.
    • (2006) Int. J. Appl. Earth Obs. Geoinf. , vol.8 , Issue.1 , pp. 26-33
    • Prasad, A.K.1    Chai, L.2    Singh, R.P.3    Kafatos, M.4
  • 46
    • 84890323297 scopus 로고    scopus 로고
    • Assimilation of COSMO-SkyMed-derived LAI maps into the AQUATER crop growth simulation model. Capitanata (Southern Italy) case study
    • Rinaldi, M., Satalino, G., Mattia, F., Balenzano, A., Perego, A., Acutis, M., Ruggieri, S., Assimilation of COSMO-SkyMed-derived LAI maps into the AQUATER crop growth simulation model. Capitanata (Southern Italy) case study. Eur. J. Remote Sens. 46 (2013), 891–908.
    • (2013) Eur. J. Remote Sens. , vol.46 , pp. 891-908
    • Rinaldi, M.1    Satalino, G.2    Mattia, F.3    Balenzano, A.4    Perego, A.5    Acutis, M.6    Ruggieri, S.7
  • 49
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • Rumelhart, D.E., Hinton, G.E., Williams, R.J., Learning representations by back-propagating errors. Nature 323 (1986), 533–536.
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 50
    • 84899506400 scopus 로고    scopus 로고
    • Use of corn height to improve the relationship between active opticals sensor readings and yield estimates
    • Sharma, L.K., Franzen, D.W., Use of corn height to improve the relationship between active opticals sensor readings and yield estimates. Precis. Agric. 15 (2014), 331–345.
    • (2014) Precis. Agric. , vol.15 , pp. 331-345
    • Sharma, L.K.1    Franzen, D.W.2
  • 51
    • 0033318080 scopus 로고    scopus 로고
    • Multi- temporal C- and L-band polarimetric signatures of crops
    • Skriver, H., Svendsen, M.T., Thomsen, A.G., Multi- temporal C- and L-band polarimetric signatures of crops. IEEE Trans. Geosci. Remote Sens. 37:5 (1999), 2413–2429.
    • (1999) IEEE Trans. Geosci. Remote Sens. , vol.37 , Issue.5 , pp. 2413-2429
    • Skriver, H.1    Svendsen, M.T.2    Thomsen, A.G.3
  • 52
    • 85065103650 scopus 로고    scopus 로고
    • Radarsat-2 Product Description. RN-SP-52-1238, Issue 1/6: November 2.
    • Slade, B., 2009. Radarsat-2 Product Description. RN-SP-52-1238, Issue 1/6: November 2.
    • (2009)
    • Slade, B.1
  • 53
    • 0342871690 scopus 로고    scopus 로고
    • Introduction to multi-layer feed-forward neural networks
    • Svozil, D., Kvasnicka, V., Pospichal, J., Introduction to multi-layer feed-forward neural networks. Chemom. Intell. Lab. Syst. 39:-1 (1997), 43–62.
    • (1997) Chemom. Intell. Lab. Syst. , vol.39 , Issue.-1 , pp. 43-62
    • Svozil, D.1    Kvasnicka, V.2    Pospichal, J.3
  • 54
    • 0018457755 scopus 로고
    • Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: part II-vegetation-covered soil
    • Ulaby, F.T., Bradley, G.A., Dobson, M.C., Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: part II-vegetation-covered soil. IEEE Trans. Geosci. Electron. 17:2 (1979), 33–40.
    • (1979) IEEE Trans. Geosci. Electron. , vol.17 , Issue.2 , pp. 33-40
    • Ulaby, F.T.1    Bradley, G.A.2    Dobson, M.C.3
  • 55
    • 0037379640 scopus 로고    scopus 로고
    • Neural maps in remote sensing image analysis
    • Villmann, T., Merényi, E., Hammer, B., Neural maps in remote sensing image analysis. Neural Netw. 16:3–4 (2003), 389–403.
    • (2003) Neural Netw. , vol.16 , Issue.3-4 , pp. 389-403
    • Villmann, T.1    Merényi, E.2    Hammer, B.3
  • 56
    • 84896926443 scopus 로고    scopus 로고
    • A production efficiency model-based method for satellite estimates of corn and soybean yields in the midwestern US
    • Xin, Q., Gong, P., Yu, C., Yu, L., Broich, M., Suyker, A.E., Myneni, R.B., A production efficiency model-based method for satellite estimates of corn and soybean yields in the midwestern US. Remote Sens. 5 (2013), 5926–5943.
    • (2013) Remote Sens. , vol.5 , pp. 5926-5943
    • Xin, Q.1    Gong, P.2    Yu, C.3    Yu, L.4    Broich, M.5    Suyker, A.E.6    Myneni, R.B.7
  • 57
    • 84912126342 scopus 로고    scopus 로고
    • Temporal polarimetric behavior of oilseed rape (Brassica napus L.) at C-band for early season sowing date monitoring
    • Yang, H., Li, Z., Chen, E., Zhao, C., Yang, G., Casa, R., Pignatti, S., Feng, Q., Temporal polarimetric behavior of oilseed rape (Brassica napus L.) at C-band for early season sowing date monitoring. Remote Sens. 6 (2014), 10375–10394.
    • (2014) Remote Sens. , vol.6 , pp. 10375-10394
    • Yang, H.1    Li, Z.2    Chen, E.3    Zhao, C.4    Yang, G.5    Casa, R.6    Pignatti, S.7    Feng, Q.8
  • 59
    • 80053929599 scopus 로고    scopus 로고
    • Improvement in regression of corn yield with plant height using relative data
    • Yin, X., McClure, M.A., Hayes, R.M., Improvement in regression of corn yield with plant height using relative data. J. Sci. Food Agric. 91 (2011), 2606–2612.
    • (2011) J. Sci. Food Agric. , vol.91 , pp. 2606-2612
    • Yin, X.1    McClure, M.A.2    Hayes, R.M.3
  • 60
    • 84866160065 scopus 로고    scopus 로고
    • Assessment of plant biomass and nitrogen nutrition with plant height in early-to mid-season corn
    • Yin, X., Hayes, R.M., McClure, M.A., Savoy, H.J., Assessment of plant biomass and nitrogen nutrition with plant height in early-to mid-season corn. J. Sci. Food Agric. 92–13 (2012), 2611–2617.
    • (2012) J. Sci. Food Agric. , vol.92-13 , pp. 2611-2617
    • Yin, X.1    Hayes, R.M.2    McClure, M.A.3    Savoy, H.J.4


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