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      작물 표현체 플랫폼 기반 벼 이미지 분석 조건 확립 = Determination of the Conditions for Image Analysis of Rice Based on a Crop Phenomic Platform

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      https://www.riss.kr/link?id=A107936079

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      다국어 초록 (Multilingual Abstract)

      Fast and accurate selection is essential for breeding to cope with rapid climate changes and a steeply increasing population. Consequently, technologies for high-throughput phenotyping (HTP) are emerging. These technologies, unlike conventional phenot...

      Fast and accurate selection is essential for breeding to cope with rapid climate changes and a steeply increasing population. Consequently, technologies for high-throughput phenotyping (HTP) are emerging. These technologies, unlike conventional phenotyping methods,enable us to evaluate agronomic traits in a fast and massive manner. Thus, the HTP facility was built to acquire and analyze crop imagesusing RGB sensors at the National Institute of Agricultural Sciences, Republic of Korea. By testing various conditions to acquire images,we determined the conditions for phenotyping using the RGB sensor as follows: exposure 30,000 ms, gamma 75, and gain 100 using LEDlights in a blue background. Based on this condition, images from 96 individual plants of rice Dongjin cultivar were obtained every weekto measure plant height and shoot area, which are directly associated with yield. The results obtained from the image analysis were comparedwith the manually collected results. The r2 value between the projected plant height obtained from image analysis and the plant height obtainedfrom manual measurement was 0.989. Furthermore, the r2 value between the projected shoot area obtained from image analysis and the shootarea obtained from manual measurement was 0.981. These results show that image analysis is highly reliable and can be used for crop phenotyping. Therefore, we expect that the new method we developed will be used for breeding in the near future.

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      목차 (Table of Contents)

      • 서언 재료 및 방법 결과 및 고찰 적요 사사
      • 서언 재료 및 방법 결과 및 고찰 적요 사사
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      참고문헌 (Reference)

      1 이성곤, "작물육종 효율 극대화를 위한 피노믹스(phenomics) 연구동향: 화상기술을 이용한 식물 표현형 분석을 중심으로" 한국육종학회 43 (43): 233-240, 2011

      2 Ray DK, "Yield trends are insufficient to double global crop production by 2050" 8 : e66428-, 2013

      3 Kim SL, "The opening of phenome-assisted selection era in the early seedling stage" 9 : 9948-, 2019

      4 Liu F, "The genetic and molecular basis of crop height based on a rice model" 247 : 1-26, 2018

      5 Cao L, "Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform" 2015

      6 Ray DK, "Recent patterns of crop yield growth and stagnation" 3 : 1293-, 2012

      7 Fanourakis D, "Rapid determination of leaf area and plant height by using light curtain arrays in four species with contrasting shoot architecture" 10 : 9-, 2014

      8 Rajendran K, "Quantifying the three main components of salinity tolerance in cereals" 32 : 237-249, 2009

      9 Yang W, "Plant phenomics and high-throughput phenotyping : accelerating rice functional genomics using multidisciplinary technologies" 16 : 180-187, 2013

      10 Furbank RT, "Phenomics-technologies to relieve the phenotyping bottleneck" 16 : 635-644, 2011

      1 이성곤, "작물육종 효율 극대화를 위한 피노믹스(phenomics) 연구동향: 화상기술을 이용한 식물 표현형 분석을 중심으로" 한국육종학회 43 (43): 233-240, 2011

      2 Ray DK, "Yield trends are insufficient to double global crop production by 2050" 8 : e66428-, 2013

      3 Kim SL, "The opening of phenome-assisted selection era in the early seedling stage" 9 : 9948-, 2019

      4 Liu F, "The genetic and molecular basis of crop height based on a rice model" 247 : 1-26, 2018

      5 Cao L, "Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform" 2015

      6 Ray DK, "Recent patterns of crop yield growth and stagnation" 3 : 1293-, 2012

      7 Fanourakis D, "Rapid determination of leaf area and plant height by using light curtain arrays in four species with contrasting shoot architecture" 10 : 9-, 2014

      8 Rajendran K, "Quantifying the three main components of salinity tolerance in cereals" 32 : 237-249, 2009

      9 Yang W, "Plant phenomics and high-throughput phenotyping : accelerating rice functional genomics using multidisciplinary technologies" 16 : 180-187, 2013

      10 Furbank RT, "Phenomics-technologies to relieve the phenotyping bottleneck" 16 : 635-644, 2011

      11 Houle D, "Phenomics : the next challenge" 11 : 855-866, 2010

      12 Junker A, "Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems" 5 : 770-, 2015

      13 Matthies L, "Kalman filter-based algorithms for estimating depth from image sequences" 3 : 209-236, 1989

      14 Campbell MT, "Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice" 168 : 1476-1489, 2015

      15 Hairmansis A, "Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice" 7 : 16-, 2014

      16 Knecht AC, "Image Harvest : an open-source platform for high-throughput plant image processing and analysis" 67 : 3587-3599, 2016

      17 Berger B, "High-throughput shoot imaging to study drought responses" 61 : 3519-3528, 2010

      18 Tilman D, "Global food demand and the sustainable intensification of agriculture" 108 : 20260-20264, 2011

      19 Foley JD, "Fundamentals of Interactive Computer Graphics" Addison-Wesley 1982

      20 Moeckel T, "Estimation of vegetable crop parameter by multi-temporal UAV-borne images" 10 : 805-, 2018

      21 Chen WY, "Efficient depth image based rendering with edge dependent depth filter and interpolation" IEEE 2005

      22 Easlon HM, "Easy leaf area : automated digital image analysis for rapid and accurate measurement of leaf area" 2 : 1400033-, 2014

      23 Picon A, "Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild" 161 : 280-290, 2019

      24 Yang W, "Crop phenomics and highthroughput phenotyping : Past decades, current challenges and future perspectives" 13 : 187-214, 2020

      25 Zhao C, "Crop phenomics : Current status and perspectives" 10 : 714-, 2019

      26 Yang W, "Combining heih-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice" 5 : 5087-, 2014

      27 Parent B, "Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat" 66 : 5481-5492, 2015

      28 Fischer RAT, "Breeding and cereal yield progress" 50 : S85-S98, 2010

      29 Sritarapipat T, "Automatic rice crop height measurement using a field server and digital image processing" 14 : 900-926, 2014

      30 Chuanlei Z, "Apple leaf disease identification using genetic algorithm and correlation based feature selection method" 10 : 74-83, 2017

      31 Reynolds M, "Achieving yield gains in wheat" 35 : 1799-1823, 2012

      32 Golzarian M, "Accurate inferenece of shoot biomass from high-throughtput images of cereal plants" 7 : 2-, 2011

      33 La Fuente De GN, "Accelerating plant breeding" 18 : 667-672, 2013

      34 Harrois BN, "A water centred framework to assess the effects of salinity on the growth and yield of wheat and barley" 336 : 377-389, 2010

      35 Salas Fernandez MG, "A high-throughput, field-based phenotyping technology for tall biomass crops" 174 : 2008-2022, 2017

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2025 평가예정 재인증평가 신청대상 (재인증)
      2022-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2021-12-01 평가 등재후보로 하락 (재인증) KCI등재후보
      2018-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2015-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2014-01-01 평가 등재후보학술지 유지 (계속평가) KCI등재후보
      2013-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2011-01-01 평가 등재 1차 FAIL (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-04-07 학술지명변경 외국어명 : KOREAN JOURNAL OF BREEDING -> KOREAN JOURNAL OF BREEDING SCIENCE KCI등재
      2007-01-01 평가 등재 1차 FAIL (등재유지) KCI등재
      2005-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2002-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1999-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.6 0.6 0.49
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.45 0.41 0.952 0.07
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