Journal of Plant Biotechnology

  • 제43권1호
  • /
  • Pages.21-29
  • /
  • 2016
  • /
  • 1229-2818(pISSN)
  • /
  • 2384-1397(eISSN)
한국식물생명공학회 (The Korean Society of Plant Biotechnology)
권호 표지
DOI QR코드

DOI QR Code

ICT 원격제어 system 이용 식물진단, Phenomics 연구현황 및 전망

Current status and prospects of plant diagnosis and phenomics research by using ICT remote sensing system

  • Jung, Yu Jin (Department of Horticultural Life Science, Hankyong National University) ;
  • Nou, Ill Sup (Department of Horticulture, Sunchon National University) ;
  • Kim, Yong Kwon (Department of life Science & Biotechnology, Shingyeong University) ;
  • Kim, Hoy Taek (Department of Horticulture, Sunchon National University) ;
  • Kang, Kwon Kyoo (Department of Horticultural Life Science, Hankyong National University)
  • 투고 : 2016.03.22
  • 심사 : 2016.03.23
  • 발행 : 2016.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Remote sensing는 각종 센서를 이용하여 지표면, 물, 요소 기술에 대해 비접촉, 비파괴적인 방법으로 필요한 정보를 얻어내는 기술이다. 이들 기술은 센서 등의 요소 기술 뿐만 아니라, 센서를 탑재하는 플랫폼과 정보 통신 기술(ICT) 등을 복합적으로 이용한다. 특히 농업 분야에서는 ICT를 중개로 기상이나 토양 등의 환경 정보와 작물 정보를 측정하여 수치화하고 클라우드 컴퓨팅에 의해 생산 단계뿐만 아니라 유통 및 소비 단계까지 관리하는 스마트 농업에 크게 기여한다. 식물을 측정하기 위해서는 비파괴 비접촉 bioimaging (remote imaging)을 포함한 식물기능 remote sensing 기술개발이 필요하다. 또한 식물 과학 분야에서도 유전자 세포 수준에서 개체 수준까지를 대상으로 한 bioimaging 연구가 활발히 진행되고 있다. 최근 들어 표현형 연구를 통해 환경과 유전자형의 관계를 구명하는 phenomics 연구가 활발히 진행되고 있다. 따라서 본 논문에서는 식물기능 원격탐사의 기술동향, 식물진단 및 식물환경응답해석과 식물 phenomics 연구현황에 대해 고찰하였다.

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.

키워드

참고문헌

  1. Berger B, Parent B, Tester M (2010) High-throughput shoot imaging to study drought responses. Journal of Experimental Botany 61:3519-3528 https://doi.org/10.1093/jxb/erq201
  2. Furbank RT (2009) Plant phenomics. Funct Plant Biol 36:845-1026 https://doi.org/10.1071/FP09185
  3. 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 https://doi.org/10.1111/j.1469-8137.2005.01609.x
  4. 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 https://doi.org/10.1186/1471-2105-12-148
  5. 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 https://doi.org/10.3832/ifor0592-004
  6. 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 https://doi.org/10.1104/pp.109.150748
  7. Jones HG (2004) Application of thermal imaging and infrared sensing in plant physiology and ecophysiology. Adv Bot Res 41:107-163 https://doi.org/10.1016/S0065-2296(04)41003-9
  8. Jones HG, Morison J (2007) Imaging Stress Responses in Plants. J Exp Bot 58:743-898
  9. 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 https://doi.org/10.1071/FP09123
  10. Kim JW (2010) Trend and direction for plant factory system. J Plant Biotechnol 37:442-455 https://doi.org/10.5010/JPB.2010.37.4.442
  11. Kolukisaoglu U, Thurow K (2010) Future and frontiers of automated screening in plant sciences. Plant Science 178:476-484 https://doi.org/10.1016/j.plantsci.2010.03.006
  12. 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 https://doi.org/10.9717/kmms.2014.17.11.1313
  13. 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
  14. 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 https://doi.org/10.1007/s00216-010-4207-5
  15. 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 https://doi.org/10.1016/j.fcr.2010.12.017
  16. Omasa K (2014) Remote sensing of plant functioning -Applications in plant diagnosis and phenomics researches. Eco-Engineering 26(2):51-61
  17. 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 https://doi.org/10.2525/ecb1963.19.85
  18. Omasa K, Onoe M, Yamada H (1985) NMR imaging for measuring root system and soil water content. Environ Control Biol 23:99-102 https://doi.org/10.2525/ecb1963.23.99
  19. 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 https://doi.org/10.1104/pp.84.3.748
  20. 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 https://doi.org/10.1093/pcp/pcg165
  21. 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
  22. Robert AH, Rebecca LP (2009) Hypertriglyceridemia: phenomics and genomics. Mol Cell Biochem 326:35-43 https://doi.org/10.1007/s11010-008-0005-1
  23. 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 https://doi.org/10.1071/FP09182
  24. 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 https://doi.org/10.1093/jxb/erp386