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Volumn 38, Issue , 2017, Pages 184-192

High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field

Author keywords

[No Author keywords available]

Indexed keywords

BREEDING; CROP; MACHINE LEARNING; PHYSIOLOGY;

EID: 85025090008     PISSN: 13695266     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pbi.2017.05.006     Document Type: Review
Times cited : (236)

References (68)
  • 1
    • 84055178582 scopus 로고    scopus 로고
    • Global food demand and the sustainable intensification of agriculture
    • Tilman, D., Balzer, C., Hill, J., Befort, B.L., Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci U S A 108 (2011), 20260–20264.
    • (2011) Proc Natl Acad Sci U S A , vol.108 , pp. 20260-20264
    • Tilman, D.1    Balzer, C.2    Hill, J.3    Befort, B.L.4
  • 2
    • 85013408970 scopus 로고    scopus 로고
    • Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice
    • This article succinctly reviews the use of optical sensors for the assessment of plant diseases. While our review is focused on field-level phenotyping for crop improvement and disease screening, this article reviews the use of sensors for monitoring disease in both indoor and outdoor settings.
    • Tanger, P., Klassen, S., Mojica, J.P., Lovell, J.T., Moyers, B.T., Baraoidan, M., Naredo, M.E.B., McNally, K.L., Poland, J., Bush, D.R., Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. Sci Rep, 7, 2017 This article succinctly reviews the use of optical sensors for the assessment of plant diseases. While our review is focused on field-level phenotyping for crop improvement and disease screening, this article reviews the use of sensors for monitoring disease in both indoor and outdoor settings.
    • (2017) Sci Rep , vol.7
    • Tanger, P.1    Klassen, S.2    Mojica, J.P.3    Lovell, J.T.4    Moyers, B.T.5    Baraoidan, M.6    Naredo, M.E.B.7    McNally, K.L.8    Poland, J.9    Bush, D.R.10
  • 3
    • 84978922953 scopus 로고    scopus 로고
    • Plant disease detection by imaging sensors — parallels and specific demands for precision agriculture and plant phenotyping
    • Mahlein, A.-K., Plant disease detection by imaging sensors — parallels and specific demands for precision agriculture and plant phenotyping. Plant Dis 100 (2016), 241–251.
    • (2016) Plant Dis , vol.100 , pp. 241-251
    • Mahlein, A.-K.1
  • 4
    • 84928676430 scopus 로고    scopus 로고
    • A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture
    • Anisi, M.H., Abdul-Salaam, G., Abdullah, A.H., A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precis Agric 16 (2015), 216–238.
    • (2015) Precis Agric , vol.16 , pp. 216-238
    • Anisi, M.H.1    Abdul-Salaam, G.2    Abdullah, A.H.3
  • 5
    • 85010850421 scopus 로고    scopus 로고
    • Vinobot and vinoculer: two robotic platforms for high-throughput field phenotyping
    • Shafiekhani, A., Kadam, S., Fritschi, F.B., DeSouza, G.N., Vinobot and vinoculer: two robotic platforms for high-throughput field phenotyping. Sensors, 17, 2017, 214.
    • (2017) Sensors , vol.17 , pp. 214
    • Shafiekhani, A.1    Kadam, S.2    Fritschi, F.B.3    DeSouza, G.N.4
  • 6
    • 84908509157 scopus 로고    scopus 로고
    • Proximal remote sensing buggies and potential applications for field-based phenotyping
    • Deery, D., Jimenez-Berni, J., Jones, H., Sirault, X., Furbank, R., Proximal remote sensing buggies and potential applications for field-based phenotyping. Agronomy 4 (2014), 349–379.
    • (2014) Agronomy , vol.4 , pp. 349-379
    • Deery, D.1    Jimenez-Berni, J.2    Jones, H.3    Sirault, X.4    Furbank, R.5
  • 7
    • 85006253072 scopus 로고    scopus 로고
    • Field scanalyzer: an automated robotic field phenotyping platform for detailed crop monitoring
    • Virlet, N., Sabermanesh, K., Sadeghi-Tehran, P., Hawkesford, M.J., Field scanalyzer: an automated robotic field phenotyping platform for detailed crop monitoring. Funct Plant Biol 44 (2017), 143–153.
    • (2017) Funct Plant Biol , vol.44 , pp. 143-153
    • Virlet, N.1    Sabermanesh, K.2    Sadeghi-Tehran, P.3    Hawkesford, M.J.4
  • 8
    • 84928266341 scopus 로고    scopus 로고
    • Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach
    • This study highlights the use and advantages of low-altitude zeppelins in high throughput field phenotyping. Many aerial platforms focus exclusively on the use of drones and aircraft, and this article demonstrates how a zeppelin can overcome issues of limited payload capacity and image blurring that are common in conventional aerial platforms.
    • Liebisch, F., Kirchgessner, N., Schneider, D., Walter, A., Hund, A., Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach. Plant Methods, 11, 2015, 9 This study highlights the use and advantages of low-altitude zeppelins in high throughput field phenotyping. Many aerial platforms focus exclusively on the use of drones and aircraft, and this article demonstrates how a zeppelin can overcome issues of limited payload capacity and image blurring that are common in conventional aerial platforms.
    • (2015) Plant Methods , vol.11 , pp. 9
    • Liebisch, F.1    Kirchgessner, N.2    Schneider, D.3    Walter, A.4    Hund, A.5
  • 9
    • 85008689739 scopus 로고    scopus 로고
    • Feasibility assessment of multi-spectral satellite sensors in monitoring and discriminating wheat diseases and insects
    • Yuan, L., Zhang, H., Zhang, Y., Xing, C., Bao, Z., Feasibility assessment of multi-spectral satellite sensors in monitoring and discriminating wheat diseases and insects. Optik — Int J Light Electron Opt 131 (2017), 598–608.
    • (2017) Optik — Int J Light Electron Opt , vol.131 , pp. 598-608
    • Yuan, L.1    Zhang, H.2    Zhang, Y.3    Xing, C.4    Bao, Z.5
  • 10
    • 84938953917 scopus 로고    scopus 로고
    • An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities
    • Lee, C.M., Cable, M.L., Hook, S.J., Green, R.O., Ustin, S.L., Mandl, D.J., Middleton, E.M., An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities. Rem Sens Environ 167 (2015), 6–19.
    • (2015) Rem Sens Environ , vol.167 , pp. 6-19
    • Lee, C.M.1    Cable, M.L.2    Hook, S.J.3    Green, R.O.4    Ustin, S.L.5    Mandl, D.J.6    Middleton, E.M.7
  • 13
    • 84924917101 scopus 로고    scopus 로고
    • Automated characterization of flowering dynamics in rice using field-acquired time-series RGB images
    • Guo, W., Fukatsu, T., Ninomiya, S., Automated characterization of flowering dynamics in rice using field-acquired time-series RGB images. Plant Methods, 11, 2015, 7.
    • (2015) Plant Methods , vol.11 , pp. 7
    • Guo, W.1    Fukatsu, T.2    Ninomiya, S.3
  • 14
    • 63149166446 scopus 로고    scopus 로고
    • Image pattern classification for the identification of disease causing agents in plants
    • Camargo, A., Smith, J., Image pattern classification for the identification of disease causing agents in plants. Comput Electron Agric 66 (2009), 121–125.
    • (2009) Comput Electron Agric , vol.66 , pp. 121-125
    • Camargo, A.1    Smith, J.2
  • 16
    • 77950942373 scopus 로고    scopus 로고
    • Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging
    • Bock, C., Poole, G., Parker, P., Gottwald, T., Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. Crit Rev Plant Sci 29 (2010), 59–107.
    • (2010) Crit Rev Plant Sci , vol.29 , pp. 59-107
    • Bock, C.1    Poole, G.2    Parker, P.3    Gottwald, T.4
  • 17
    • 46549085311 scopus 로고    scopus 로고
    • Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software
    • Wijekoon, C., Goodwin, P., Hsiang, T., Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software. J Microbiol Methods 74 (2008), 94–101.
    • (2008) J Microbiol Methods , vol.74 , pp. 94-101
    • Wijekoon, C.1    Goodwin, P.2    Hsiang, T.3
  • 18
    • 84968862680 scopus 로고    scopus 로고
    • Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle
    • Sugiura, R., Tsuda, S., Tamiya, S., Itoh, A., Nishiwaki, K., Murakami, N., Shibuya, Y., Hirafuji, M., Nuske, S., Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle. Biosyst Eng 148 (2016), 1–10.
    • (2016) Biosyst Eng , vol.148 , pp. 1-10
    • Sugiura, R.1    Tsuda, S.2    Tamiya, S.3    Itoh, A.4    Nishiwaki, K.5    Murakami, N.6    Shibuya, Y.7    Hirafuji, M.8    Nuske, S.9
  • 19
    • 84930208782 scopus 로고    scopus 로고
    • Field phenotyping of grapevine growth using dense stereo reconstruction
    • Klodt, M., Herzog, K., Töpfer, R., Cremers, D., Field phenotyping of grapevine growth using dense stereo reconstruction. BMC Bioinformatics, 16, 2015, 143.
    • (2015) BMC Bioinformatics , vol.16 , pp. 143
    • Klodt, M.1    Herzog, K.2    Töpfer, R.3    Cremers, D.4
  • 20
    • 85025070759 scopus 로고    scopus 로고
    • 3D laser triangulation, a simple and robust method for automated growth determination of crop plants in challenging environments
    • Kjær, K.H., Ottosen, C.-O., 3D laser triangulation, a simple and robust method for automated growth determination of crop plants in challenging environments. Sensors, 15, 2015, 2.
    • (2015) Sensors , vol.15 , pp. 2
    • Kjær, K.H.1    Ottosen, C.-O.2
  • 21
    • 84956689620 scopus 로고    scopus 로고
    • Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions
    • Friedli, M., Kirchgessner, N., Grieder, C., Liebisch, F., Mannale, M., Walter, A., Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions. Plant Methods, 12, 2016, 9.
    • (2016) Plant Methods , vol.12 , pp. 9
    • Friedli, M.1    Kirchgessner, N.2    Grieder, C.3    Liebisch, F.4    Mannale, M.5    Walter, A.6
  • 22
    • 85019682833 scopus 로고    scopus 로고
    • High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing
    • Holman, F.H., Riche, A.B., Michalski, A., Castle, M., Wooster, M.J., Hawkesford, M.J., High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing. Rem Sens, 8, 2016, 1031.
    • (2016) Rem Sens , vol.8 , pp. 1031
    • Holman, F.H.1    Riche, A.B.2    Michalski, A.3    Castle, M.4    Wooster, M.J.5    Hawkesford, M.J.6
  • 23
    • 84930955524 scopus 로고    scopus 로고
    • LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget
    • Vadez, V., Kholová, J., Hummel, G., Zhokhavets, U., Gupta, S., Hash, C.T., LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget. J Exp Bot, 2015, erv251.
    • (2015) J Exp Bot , pp. erv251
    • Vadez, V.1    Kholová, J.2    Hummel, G.3    Zhokhavets, U.4    Gupta, S.5    Hash, C.T.6
  • 24
    • 85011919241 scopus 로고    scopus 로고
    • Detection of disease symptoms on hyperspectral 3D plant models
    • These authors demonstrate that the combination of 3D point cloud data with hyperspectral imaging data results in improved detection of Cercospora leaf spot disease symptoms in sugar beet. This study highlights how using multiples layers of sensor data can improve the resolution and accuracy of HTP data.
    • Roschera, R., Behmanna, J., Mahlein, A.-K., Dupuis, J., Kuhlmann, H., Plümer, L., Detection of disease symptoms on hyperspectral 3D plant models. ISPRS Ann Photogramm Rem Sens Spatial Inform Sci 3 (2016), 89–96 These authors demonstrate that the combination of 3D point cloud data with hyperspectral imaging data results in improved detection of Cercospora leaf spot disease symptoms in sugar beet. This study highlights how using multiples layers of sensor data can improve the resolution and accuracy of HTP data.
    • (2016) ISPRS Ann Photogramm Rem Sens Spatial Inform Sci , vol.3 , pp. 89-96
    • Roschera, R.1    Behmanna, J.2    Mahlein, A.-K.3    Dupuis, J.4    Kuhlmann, H.5    Plümer, L.6
  • 25
    • 85025085748 scopus 로고    scopus 로고
    • Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques
    • Khosrokhani, M., Khairunniza-Bejo, S., Pradhan, B., Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques. Geocarto Int, 2016, 1–17.
    • (2016) Geocarto Int , pp. 1-17
    • Khosrokhani, M.1    Khairunniza-Bejo, S.2    Pradhan, B.3
  • 27
    • 4344559689 scopus 로고    scopus 로고
    • Thermal and chlorophyll-fluorescence imaging distinguish plant–pathogen interactions at an early stage
    • Chaerle, L., Hagenbeek, D., De Bruyne, E., Valcke, R., Van Der Straeten, D., Thermal and chlorophyll-fluorescence imaging distinguish plant–pathogen interactions at an early stage. Plant Cell Physiol 45 (2004), 887–896.
    • (2004) Plant Cell Physiol , vol.45 , pp. 887-896
    • Chaerle, L.1    Hagenbeek, D.2    De Bruyne, E.3    Valcke, R.4    Van Der Straeten, D.5
  • 28
    • 84904429218 scopus 로고    scopus 로고
    • Fusion of sensor data for the detection and differentiation of plant diseases in cucumber
    • Berdugo, C., Zito, R., Paulus, S., Mahlein, A.K., Fusion of sensor data for the detection and differentiation of plant diseases in cucumber. Plant Pathol 63 (2014), 1344–1356.
    • (2014) Plant Pathol , vol.63 , pp. 1344-1356
    • Berdugo, C.1    Zito, R.2    Paulus, S.3    Mahlein, A.K.4
  • 29
    • 33745615630 scopus 로고    scopus 로고
    • Thermal imaging of cucumber leaves affected by downy mildew and environmental conditions
    • Oerke, E., Steiner, U., Dehne, H., Lindenthal, M., Thermal imaging of cucumber leaves affected by downy mildew and environmental conditions. J Exp Bot 57 (2006), 2121–2132.
    • (2006) J Exp Bot , vol.57 , pp. 2121-2132
    • Oerke, E.1    Steiner, U.2    Dehne, H.3    Lindenthal, M.4
  • 30
    • 80052289471 scopus 로고    scopus 로고
    • Thermographic assessment of scab disease on apple leaves
    • Oerke, E.-C., Fröhling, P., Steiner, U., Thermographic assessment of scab disease on apple leaves. Precis Agric 12 (2011), 699–715.
    • (2011) Precis Agric , vol.12 , pp. 699-715
    • Oerke, E.-C.1    Fröhling, P.2    Steiner, U.3
  • 31
    • 84930019319 scopus 로고    scopus 로고
    • Early detection and quantification of Verticillium wilt in olive using hyperspectral and thermal imagery over large areas
    • Calderón, R., Navas-Cortés, J.A., Zarco-Tejada, P.J., Early detection and quantification of Verticillium wilt in olive using hyperspectral and thermal imagery over large areas. Rem Sens 7 (2015), 5584–5610.
    • (2015) Rem Sens , vol.7 , pp. 5584-5610
    • Calderón, R.1    Navas-Cortés, J.A.2    Zarco-Tejada, P.J.3
  • 32
    • 84962701763 scopus 로고    scopus 로고
    • Field phenotyping of water stress at tree scale by UAV-sensed imagery: new insights for thermal acquisition and calibration
    • Gómez-Candón, D., Virlet, N., Labbé, S., Jolivot, A., Regnard, J.-L., Field phenotyping of water stress at tree scale by UAV-sensed imagery: new insights for thermal acquisition and calibration. Precis Agric 17 (2016), 786–800.
    • (2016) Precis Agric , vol.17 , pp. 786-800
    • Gómez-Candón, D.1    Virlet, N.2    Labbé, S.3    Jolivot, A.4    Regnard, J.-L.5
  • 33
    • 85025074176 scopus 로고    scopus 로고
    • High-throughput phenotyping of maize leaf physiology and biochemistry using hyperspectral reflectance
    • 01447.02016 This study highlights the practical use of hyperspectral imaging for a major commercial crop species (maize) in determining the plant response to changing environmental conditions and stress (ambient versus elevated O3).
    • Yendrek, C., Tomaz, T., Montes, C.M., Cao, Y., Morse, A.M., Brown, P.J., McIntyre, L., Leakey, A., Ainsworth, E., High-throughput phenotyping of maize leaf physiology and biochemistry using hyperspectral reflectance. Plant Physiol, 2016 01447.02016 This study highlights the practical use of hyperspectral imaging for a major commercial crop species (maize) in determining the plant response to changing environmental conditions and stress (ambient versus elevated O3).
    • (2016) Plant Physiol
    • Yendrek, C.1    Tomaz, T.2    Montes, C.M.3    Cao, Y.4    Morse, A.M.5    Brown, P.J.6    McIntyre, L.7    Leakey, A.8    Ainsworth, E.9
  • 35
  • 36
    • 84921900726 scopus 로고    scopus 로고
    • Metro maps of plant disease dynamics — automated mining of differences using hyperspectral images
    • The reduction of massive HTP datasets into simple and intuitive visualizations is necessary to inform crop breeding and management decisions. Inspired by public transport networks, the authors of this article developed an easily interpretable visualization of hyperspectral data for crop disease dynamics.
    • Wahabzada, M., Mahlein, A.-K., Bauckhage, C., Steiner, U., Oerke, E.-C., Kersting, K., Metro maps of plant disease dynamics — automated mining of differences using hyperspectral images. PLOS ONE, 10, 2015, e0116902 The reduction of massive HTP datasets into simple and intuitive visualizations is necessary to inform crop breeding and management decisions. Inspired by public transport networks, the authors of this article developed an easily interpretable visualization of hyperspectral data for crop disease dynamics.
    • (2015) PLOS ONE , vol.10 , pp. e0116902
    • Wahabzada, M.1    Mahlein, A.-K.2    Bauckhage, C.3    Steiner, U.4    Oerke, E.-C.5    Kersting, K.6
  • 37
    • 1242265184 scopus 로고    scopus 로고
    • Detecting sugarcane ‘orange rust'disease using EO-1 Hyperion hyperspectral imagery
    • Apan, A., Held, A., Phinn, S., Markley, J., Detecting sugarcane ‘orange rust'disease using EO-1 Hyperion hyperspectral imagery. Int J Rem Sens 25 (2004), 489–498.
    • (2004) Int J Rem Sens , vol.25 , pp. 489-498
    • Apan, A.1    Held, A.2    Phinn, S.3    Markley, J.4
  • 38
    • 79551687553 scopus 로고    scopus 로고
    • Early detection of Fusarium infection in wheat using hyper-spectral imaging
    • Bauriegel, E., Giebel, A., Geyer, M., Schmidt, U., Herppich, W., Early detection of Fusarium infection in wheat using hyper-spectral imaging. Comput Electron Agric 75 (2011), 304–312.
    • (2011) Comput Electron Agric , vol.75 , pp. 304-312
    • Bauriegel, E.1    Giebel, A.2    Geyer, M.3    Schmidt, U.4    Herppich, W.5
  • 39
    • 34249099341 scopus 로고    scopus 로고
    • Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: non-parametric statistical approaches and physiological implications
    • Delalieux, S., Van Aardt, J., Keulemans, W., Schrevens, E., Coppin, P., Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: non-parametric statistical approaches and physiological implications. Eur J Agron 27 (2007), 130–143.
    • (2007) Eur J Agron , vol.27 , pp. 130-143
    • Delalieux, S.1    Van Aardt, J.2    Keulemans, W.3    Schrevens, E.4    Coppin, P.5
  • 40
    • 84971641326 scopus 로고    scopus 로고
    • Early detection and quantification of almond red leaf blotch using high-resolution hyperspectral and thermal imagery
    • López-López, M., Calderón, R., González-Dugo, V., Zarco-Tejada, P.J., Fereres, E., Early detection and quantification of almond red leaf blotch using high-resolution hyperspectral and thermal imagery. Rem Sens, 8, 2016, 276.
    • (2016) Rem Sens , vol.8 , pp. 276
    • López-López, M.1    Calderón, R.2    González-Dugo, V.3    Zarco-Tejada, P.J.4    Fereres, E.5
  • 41
    • 84944461891 scopus 로고    scopus 로고
    • Detection of laurel wilt disease in avocado using low altitude aerial imaging
    • de Castro, A.I., Ehsani, R., Ploetz, R.C., Crane, J.H., Buchanon, S., Detection of laurel wilt disease in avocado using low altitude aerial imaging. PLOS ONE, 10, 2015, e0124642.
    • (2015) PLOS ONE , vol.10 , pp. e0124642
    • de Castro, A.I.1    Ehsani, R.2    Ploetz, R.C.3    Crane, J.H.4    Buchanon, S.5
  • 42
    • 85025074061 scopus 로고    scopus 로고
    • Development of a multiband sensor for citrus black spot disease detection
    • Pourreza, A., Lee, W., Lu, J., Roberts, P., Development of a multiband sensor for citrus black spot disease detection. 2016.
    • (2016)
    • Pourreza, A.1    Lee, W.2    Lu, J.3    Roberts, P.4
  • 43
    • 84960336204 scopus 로고    scopus 로고
    • Detection and classification of mosaic virus disease in cassava plants by proximal sensing of photochemical reflectance index
    • Raji, S.N., Subhash, N., Ravi, V., Saravanan, R., Mohanan, C.N., MakeshKumar, T., Nita, S., Detection and classification of mosaic virus disease in cassava plants by proximal sensing of photochemical reflectance index. J Indian Soc Rem Sens 44 (2016), 875–883.
    • (2016) J Indian Soc Rem Sens , vol.44 , pp. 875-883
    • Raji, S.N.1    Subhash, N.2    Ravi, V.3    Saravanan, R.4    Mohanan, C.N.5    MakeshKumar, T.6    Nita, S.7
  • 44
    • 85025100391 scopus 로고    scopus 로고
    • Detecting the early stage of phaeosphaeria leaf spot infestations in maize crop using in situ hyperspectral data and guided regularized random forest algorithm
    • Adam, E., Deng, H., Odindi, J., Abdel-Rahman, E.M., Mutanga, O., Detecting the early stage of phaeosphaeria leaf spot infestations in maize crop using in situ hyperspectral data and guided regularized random forest algorithm. J Spectrosc, 2017, 2017.
    • (2017) J Spectrosc , pp. 2017
    • Adam, E.1    Deng, H.2    Odindi, J.3    Abdel-Rahman, E.M.4    Mutanga, O.5
  • 45
    • 84920948267 scopus 로고    scopus 로고
    • Leaf gas exchange and chlorophyll a fluorescence imaging of rice leaves infected with Monographella albescens
    • Tatagiba, S.D., DaMatta, F.M., Rodrigues, F.Á., Leaf gas exchange and chlorophyll a fluorescence imaging of rice leaves infected with Monographella albescens. Phytopathology 105 (2015), 180–188.
    • (2015) Phytopathology , vol.105 , pp. 180-188
    • Tatagiba, S.D.1    DaMatta, F.M.2    Rodrigues, F.Á.3
  • 46
    • 84940723312 scopus 로고    scopus 로고
    • Sequential application of hyperspectral indices for delineation of stripe rust infection and nitrogen deficiency in wheat
    • Through improved quantification of stripe rust infection and N deficiency in wheat, this study highlights the application and underscores the potential of using multiple hyperspectral vegetation indices for improving the identification and quantification of biotic and abiotic stresses.
    • Devadas, R., Lamb, D., Backhouse, D., Simpfendorfer, S., Sequential application of hyperspectral indices for delineation of stripe rust infection and nitrogen deficiency in wheat. Precis Agric 16 (2015), 477–491 Through improved quantification of stripe rust infection and N deficiency in wheat, this study highlights the application and underscores the potential of using multiple hyperspectral vegetation indices for improving the identification and quantification of biotic and abiotic stresses.
    • (2015) Precis Agric , vol.16 , pp. 477-491
    • Devadas, R.1    Lamb, D.2    Backhouse, D.3    Simpfendorfer, S.4
  • 47
    • 79960300577 scopus 로고    scopus 로고
    • Use of blue–green and chlorophyll fluorescence measurements for differentiation between nitrogen deficiency and pathogen infection in winter wheat
    • Bürling, K., Hunsche, M., Noga, G., Use of blue–green and chlorophyll fluorescence measurements for differentiation between nitrogen deficiency and pathogen infection in winter wheat. J Plant Physiol 168 (2011), 1641–1648.
    • (2011) J Plant Physiol , vol.168 , pp. 1641-1648
    • Bürling, K.1    Hunsche, M.2    Noga, G.3
  • 49
    • 84939489005 scopus 로고    scopus 로고
    • Advanced multi-color fluorescence imaging system for detection of biotic and abiotic stresses in leaves
    • Konanz, S., Kocsányi, L., Buschmann, C., Advanced multi-color fluorescence imaging system for detection of biotic and abiotic stresses in leaves. Agriculture 4 (2014), 79–95.
    • (2014) Agriculture , vol.4 , pp. 79-95
    • Konanz, S.1    Kocsányi, L.2    Buschmann, C.3
  • 51
    • 84899939712 scopus 로고    scopus 로고
    • Chlorophyll fluorescence imaging to facilitate breeding of Bremia lactucae-resistant lettuce cultivars
    • Bauriegel, E., Brabandt, H., Gärber, U., Herppich, W., Chlorophyll fluorescence imaging to facilitate breeding of Bremia lactucae-resistant lettuce cultivars. Comput Electron Agric 105 (2014), 74–82.
    • (2014) Comput Electron Agric , vol.105 , pp. 74-82
    • Bauriegel, E.1    Brabandt, H.2    Gärber, U.3    Herppich, W.4
  • 52
    • 84910070038 scopus 로고    scopus 로고
    • Ф PSII and NPQ to evaluate Bremia lactucae-infection in susceptible and resistant lettuce cultivars
    • Brabandt, H., Bauriegel, E., Gärber, U., Herppich, W., Ф PSII and NPQ to evaluate Bremia lactucae-infection in susceptible and resistant lettuce cultivars. Sci Horticult 180 (2014), 123–129.
    • (2014) Sci Horticult , vol.180 , pp. 123-129
    • Brabandt, H.1    Bauriegel, E.2    Gärber, U.3    Herppich, W.4
  • 53
    • 85009788169 scopus 로고    scopus 로고
    • Detection of Huanglongbing in Florida using fluorescence imaging spectroscopy and machine-learning methods
    • Wetterich, C.B., de Oliveira Neves, R.F., Belasque, J., Ehsani, R., Marcassa, L.G., Detection of Huanglongbing in Florida using fluorescence imaging spectroscopy and machine-learning methods. Appl Opt 56 (2017), 15–23.
    • (2017) Appl Opt , vol.56 , pp. 15-23
    • Wetterich, C.B.1    de Oliveira Neves, R.F.2    Belasque, J.3    Ehsani, R.4    Marcassa, L.G.5
  • 54
    • 84930271268 scopus 로고    scopus 로고
    • Metabolic responses of avocado plants to stress induced by Rosellinia necatrix analysed by fluorescence and thermal imaging
    • Granum, E., Pérez-Bueno, M.L., Calderón, C.E., Ramos, C., de Vicente, A., Cazorla, F.M., Barón, M., Metabolic responses of avocado plants to stress induced by Rosellinia necatrix analysed by fluorescence and thermal imaging. Eur J Plant Pathol 142 (2015), 625–632.
    • (2015) Eur J Plant Pathol , vol.142 , pp. 625-632
    • Granum, E.1    Pérez-Bueno, M.L.2    Calderón, C.E.3    Ramos, C.4    de Vicente, A.5    Cazorla, F.M.6    Barón, M.7
  • 55
    • 84934323993 scopus 로고    scopus 로고
    • Detection of mosaic virus disease in cassava plants by sunlight-induced fluorescence imaging: a pilot study for proximal sensing
    • Raji, S.N., Subhash, N., Ravi, V., Saravanan, R., Mohanan, C.N., Nita, S., Kumar, T.M., Detection of mosaic virus disease in cassava plants by sunlight-induced fluorescence imaging: a pilot study for proximal sensing. Int J Rem Sens 36 (2015), 2880–2897.
    • (2015) Int J Rem Sens , vol.36 , pp. 2880-2897
    • Raji, S.N.1    Subhash, N.2    Ravi, V.3    Saravanan, R.4    Mohanan, C.N.5    Nita, S.6    Kumar, T.M.7
  • 56
    • 84989315292 scopus 로고    scopus 로고
    • The quest for understanding phenotypic variation via integrated approaches in the field environment
    • Pauli, D., Chapman, S.C., Bart, R., Topp, C.N., Lawrence-Dill, C.J., Poland, J., Gore, M.A., The quest for understanding phenotypic variation via integrated approaches in the field environment. Plant Physiol 172 (2016), 622–634.
    • (2016) Plant Physiol , vol.172 , pp. 622-634
    • Pauli, D.1    Chapman, S.C.2    Bart, R.3    Topp, C.N.4    Lawrence-Dill, C.J.5    Poland, J.6    Gore, M.A.7
  • 57
    • 85007437412 scopus 로고    scopus 로고
    • Mahotas: Open source software for scriptable computer vision
    • arXiv:1211.4907
    • Coelho, L.P., Mahotas: Open source software for scriptable computer vision. 2012 arXiv:1211.4907.
    • (2012)
    • Coelho, L.P.1
  • 61
    • 84929485542 scopus 로고    scopus 로고
    • Automatic detection of diseased tomato plants using thermal and stereo visible light images
    • Prince, G., Clarkson, J.P., Rajpoot, N.M., Automatic detection of diseased tomato plants using thermal and stereo visible light images. PLOS ONE, 10, 2015, e0123262.
    • (2015) PLOS ONE , vol.10 , pp. e0123262
    • Prince, G.1    Clarkson, J.P.2    Rajpoot, N.M.3
  • 65
    • 84988564472 scopus 로고    scopus 로고
    • Using deep learning for image-based plant disease detection
    • A major highlight of this paper is the use of a public image dataset of healthy and diseased plants, utilizing the growing resources in the plant community. They also demonstrate remarkable accuracy (greater than 99%) with their convolutional neural network to identify 14 crops species and the presence/absence of 26 disease states. Of particular note is the focus given to the use of smartphone technology to implement early and accurate detection of plant disease in the field.
    • Mohanty, S.P., Hughes, D.P., Salathé, M., Using deep learning for image-based plant disease detection. Front Plant Sci, 7, 2016 A major highlight of this paper is the use of a public image dataset of healthy and diseased plants, utilizing the growing resources in the plant community. They also demonstrate remarkable accuracy (greater than 99%) with their convolutional neural network to identify 14 crops species and the presence/absence of 26 disease states. Of particular note is the focus given to the use of smartphone technology to implement early and accurate detection of plant disease in the field.
    • (2016) Front Plant Sci , vol.7
    • Mohanty, S.P.1    Hughes, D.P.2    Salathé, M.3
  • 66
    • 84981314135 scopus 로고    scopus 로고
    • An investigation into machine learning regression techniques for the leaf rust disease detection using hyperspectral measurement
    • The authors demonstrate the effectiveness of spectral vegetation indices (SVIs) versus machine learning (ML) approaches for the detection of plant disease. This paper highlights that other approaches, such as SVIs, can be suitable alternative to ML for high-throughput phenotyping (HTP) and can outperform ML in terms of specificity for plant disease detection.
    • Ashourloo, D., Aghighi, H., Matkan, A.A., Mobasheri, M.R., Rad, A.M., An investigation into machine learning regression techniques for the leaf rust disease detection using hyperspectral measurement. IEEE J Sel Top Appl Earth Observ Rem Sens 9 (2016), 4344–4351 The authors demonstrate the effectiveness of spectral vegetation indices (SVIs) versus machine learning (ML) approaches for the detection of plant disease. This paper highlights that other approaches, such as SVIs, can be suitable alternative to ML for high-throughput phenotyping (HTP) and can outperform ML in terms of specificity for plant disease detection.
    • (2016) IEEE J Sel Top Appl Earth Observ Rem Sens , vol.9 , pp. 4344-4351
    • Ashourloo, D.1    Aghighi, H.2    Matkan, A.A.3    Mobasheri, M.R.4    Rad, A.M.5
  • 68
    • 84959467829 scopus 로고    scopus 로고
    • Envirotyping for deciphering environmental impacts on crop plants
    • Xu, Y., Envirotyping for deciphering environmental impacts on crop plants. Theoret Appl Genet 129 (2016), 653–673.
    • (2016) Theoret Appl Genet , vol.129 , pp. 653-673
    • Xu, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.