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Current status and prospects of plant diagnosis and phenomics research by using ICT remote sensing system
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  • Journal title : Journal of Plant Biotechnology
  • Volume 43, Issue 1,  2016, pp.21-29
  • Publisher : The Korean Society of Plant Biotechnology
  • DOI : 10.5010/JPB.2016.43.1.21
 Title & Authors
Current status and prospects of plant diagnosis and phenomics research by using ICT remote sensing system
Jung, Yu Jin; Nou, Ill Sup; Kim, Yong Kwon; Kim, Hoy Taek; Kang, Kwon Kyoo;
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Remote Sensing (RS) is a technique to obtain necessary information in a non-contact and non-destructive method by using various sensors on the surface, water or atmospheric phenomena. These techniques combine elements such as sensors, and platform and information communication technology (ICT) for mounting the sensor. ICT has contributed significantly to the success of smart agriculture through quantification and measurement of environmental factors and information such as weather, crop and soil management to distribution and consumption stage, as well as the production stage by the cloud computer. Remote sensing techniques, including non-destructive non-contact bioimaging (remote imaging) is required to measure the plant function. In addition, bioimaging study in plant science is performed at the gene, cellular and individual plant level. Recently, bioimaging technology is considered the latest phenomics that identifies the relationship between the genotype and environment for distinguishing phenotypes. In this review, trends in remote sensing in plants, plants diagnostics and response to environment and status of plants phonemics research were presented.
Bioimaging;Information communication technology (ICT);Phenomics;Remote sensing;
 Cited by
Berger B, Parent B, Tester M (2010) High-throughput shoot imaging to study drought responses. Journal of Experimental Botany 61:3519-3528 crossref(new window)

Furbank RT (2009) Plant phenomics. Funct Plant Biol 36:845-1026 crossref(new window)

Granier C, Aguirrezabal L, Chenu K, Cookson SJ, Dauzat M, Hamard P, Thioux JJ, Rolland G, Bouchier-Combaud S, Lebaudy A, Muller B, Simonneau T, Tardieu F (2006) PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit. New Phytologist 169:623-635 crossref(new window)

Hartmann A, Czauderna T, Hoffmann R, Stein N, Schreiber F (2011) HTPheno: An image analysis pipeline for high-throughput plant phenotyping. BMC Bioinformatics 12:148 crossref(new window)

Ishimura A, SHimizu Y, Rahimzadeh Bajairan P, Omasa K (2011) Remote sensing of Japanese beech forest decline using an improved Temperatur Vegetation Dryness Index(iTVDI). iForest 4:195-199 crossref(new window)

Iyer-Pascuzzi AS, Symonova O, Mileyko Y, Hal Y, Belcher H, Harer j, Weitz JS, Benfey PN (2010) Imaging and Analysis Platform for Automatic Phenotyping and Trait Ranking of Plant Root Systems. Plant Physiology 152:1148-1157 crossref(new window)

Jones HG (2004) Application of thermal imaging and infrared sensing in plant physiology and ecophysiology. Adv Bot Res 41:107-163 crossref(new window)

Jones HG, Morison J (2007) Imaging Stress Responses in Plants. J Exp Bot 58:743-898

Jones HG, Serraj R, Loveys BR, Xiong L, Wheaton A, Price AH (2009) Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field. Functional Plant Biology 36:978-989 crossref(new window)

Kim JW (2010) Trend and direction for plant factory system. J Plant Biotechnol 37:442-455 crossref(new window)

Kolukisaoglu U, Thurow K (2010) Future and frontiers of automated screening in plant sciences. Plant Science 178:476-484 crossref(new window)

Lee JY, Kim SH, Lee SB, Choi HJ, Jung JJ (2014) A study on the necessity and construction plan of the internet of things platform for smart agriculture. J Korea Multimedia Society 17(11):1313-1324 crossref(new window)

Lee SY, Kim JM, Hwang DH (2014) A Study of Big-Data System Based on Data Stream. J Korea Multimedia Society 18(1):8-15

Megan AH, Amit KS, Parvesh S, Scott CB, Brij MM (2011) Nanoparticles as contrast agents for in-vivo bioimaging:current status and future perspectives. Anal Bioanal Chem 399:3-27 crossref(new window)

Montes JM, Technow F, Dhillon BS, Mauch F, Melchinger AE (2011) High-throughput non-destructive biomass determination during early plant development in maize under field conditions. Field Crops Research 121:268-273 crossref(new window)

Omasa K (2014) Remote sensing of plant functioning -Applications in plant diagnosis and phenomics researches. Eco-Engineering 26(2):51-61

Omasa K, Hashimoto Y, Aiga I (1981) A quantitative analysis of the relationships between $O_3$ Sorption and its acute effects on plant leaves using image instrumentation. Environ Control Biol 19:85-92 crossref(new window)

Omasa K, Onoe M, Yamada H (1985) NMR imaging for measuring root system and soil water content. Environ Control Biol 23:99-102 crossref(new window)

Omasa K, Shimazaki K, Aiga I, Larcher W, Onoe M (1987) Image analysis of chlorophyll fluorescence transients for diagnosing the photosynthetic system of attached leaves. Plant Physiol 84:748-752 crossref(new window)

Omasa K, Takayama K (2003) Simultaneous measurement of stomatal conductance, non-photochemical quenching, and photochemical yield of photosystem II in intact leaves by thermal and chlorophyll fluorescence imaging. Plant Cell Physiol 44:1290-1300 crossref(new window)

Riedelsheimer C, Czedik-Eysenberg A, Grieder C, Lisec J, Technow F, Sulpice R, Altmann T, Stitt M, Willmitzer L, Melchinger AE (2012) Genomic and metabolic prediction of complex heterotic traits in hybrid maize. NATURE GENETICS 44:271-222

Robert AH, Rebecca LP (2009) Hypertriglyceridemia: phenomics and genomics. Mol Cell Biochem 326:35-43 crossref(new window)

Sirault XRR, James RA, Furbank RT (2009) A new screening method for osmotic component of salinity tolerance in cereals suing infrared thermogrphy. Functional Plant Biology 36:970-977 crossref(new window)

Tracy SR, Roberts JA, Black CR, McNeill A, Davidson R, Mooney SJ (2010) The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography. Journal of Experimental Botany 61:311-313 crossref(new window)