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Data mining: Methodology for evaluating adaptive cultivars to climate change using simulation model

Research Project

Project/Area Number 15K14635
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Crop production science
Research InstitutionIwate University

Principal Investigator

Shimono Hiroyuki  岩手大学, 農学部, 准教授 (70451490)

Co-Investigator(Kenkyū-buntansha) 熊谷 悦史  国立研究開発法人農業・食品産業技術総合研究機構, 東北農業研究センター, 主任研究員 (80583442)
Project Period (FY) 2015-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2016: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords数理モデル / ビッグデータ / イネ / 品種 / 気候変動 / 表現型可塑性 / 成長モデル / 多収 / 気象
Outline of Final Research Achievements

Phenotype data of genotypes in yield and yield components obtained field trials is valuable data for future breeding. However, the data per se of different genotypes is a result of mixture of (1) ability of the genotype and (2) effect of environments, so it is required to develop new method to evaluate ability of genotypes with excluding the effects of environments.

We developed new method using simulation model for evaluating crop productivity, and screened three genotypes with different yielding ability. The method was confirmed by the field and pot trials at identical location. The developed method can be used for data mining from big data of field trials.

Report

(3 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • Research Products

    (5 results)

All 2017 2016 2015

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results,  Acknowledgement Compliant: 1 results) Presentation (4 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Mining a yield-trial database to identify high-yielding cultivars by simulation modeling: a case study for rice2017

    • Author(s)
      Masuya, Y. and Shimono, H.
    • Journal Title

      Journal of Agricultural Meteorology

      Volume: 73 Issue: 2 Pages: 51-58

    • DOI

      10.2480/agrmet.D-16-00004

    • NAID

      130005589265

    • ISSN
      0021-8588, 1881-0136
    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Presentation] 人工知能を用いたイネ育種法 1.データマイニング法の検証2017

    • Author(s)
      塩井健一朗・熊谷悦史・舛谷悠祐・黒田栄喜・下野裕之
    • Organizer
      日本農業気象学会 2017年全国大会
    • Place of Presentation
      北里大学(青森県十和田市)
    • Year and Date
      2017-03-27
    • Related Report
      2016 Annual Research Report
  • [Presentation] Artificial intelligence (AI) as a tool for rice breeding (1) Confirmation of mining method from big data2016

    • Author(s)
      Shioi, K., Kumagai, E., Kuroda, E. and Shimono, H.
    • Organizer
      1st UGAS, Iwate University International Symposium 2016
    • Place of Presentation
      Morioka, Japan
    • Year and Date
      2016-12-17
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 成長モデルを利用した気候変動への適応イネ品種の評価法の開発2016

    • Author(s)
      舛谷悠祐・長井和哉・黒田栄喜・下野裕之
    • Organizer
      第241回日本作物学会講演会
    • Place of Presentation
      茨城大学 水戸キャンパス(茨城県水戸市)
    • Year and Date
      2016-03-28
    • Related Report
      2015 Research-status Report
  • [Presentation] データマイニング:成長モデルを用いた気候変動への適応品種の新たな評価法の開発2015

    • Author(s)
      舛谷悠祐・下野裕之
    • Organizer
      農業環境工学関連5学会 2015年合同大会
    • Place of Presentation
      岩手大学(岩手県盛岡市)
    • Year and Date
      2015-09-15
    • Related Report
      2015 Research-status Report

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Published: 2015-04-16   Modified: 2018-03-22  

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