International Conference on Computer and Computing Technologies in Agriculture

CCTA 2008: Computer and Computing Technologies in Agriculture II, Volume 3 pp 1585-1594

RESEARCHES OF OPTIMUM LEAF AREA INDEX DYNAMICMODELS FOR RAPE(BRASSICA NAPUS L.)

  • Hongxin Cao
  • Chunlei Zhang
  • Guangming Li
  • Baojun Zhang
  • Suolao Zhao
  • Baoqing Wang
  • Zhiqing Jin
  • Dawei Zhu
  • Juanjuan Zhu
  • Xiufang Wei
Conference paper

DOI: 10.1007/978-1-4419-0213-9_8

Volume 295 of the book series IFIP Advances in Information and Communication Technology (IFIPAICT)

Abstract

The objectives of developing optimum leaf area index dynamic models for rape (OLAIDM) was to develop Rape Cultivation Simulation-Optimization- Decision Making System(Rape-CSODS) , to design its planting , to regulate and control its growth and development, and to fulfill its high yield, good quality, high benefits and standard production eventually. The OLAIDM were developed based on field experiments with 3 cultivars, 6 sowing dates, 2 types of plant pattern and 4 sites from 2002 to 2007 in middle and lower valley of Yangtze river in China and relative data from references of rape researches, employed ideas of R/WCSODS (Rice/Wheat Cultivation Simulation- Optimization-Decision Making System), and in the same time, the OLAIMR and its parameters also were assessed, calibrated and tested. The average absolute deviation(de), correlation coefficients(r) and the standard errors of their absolute deviation(Sde) of between the observed and simulated values for LAI of two cultivars in Wuhan and Nanjing were -0.03~0.1533, 0.9707~0.9997 and0.1332~0.4032, respectively. 1:1 line of them were in Fig. 1 to 4. Multi-factors such as the ramification types, cultivars, and light et al. were taken into account in this study, therefore, the OLAIDM with general adaptability, clear yield aim, mechanism, and dynamic characteristic can simulate optimum LAI dynamic for rape under different sites, cultivars and ramification types, and yielding levels.

Keywords:

rapeoptimum LAI dynamicmodels
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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  • Hongxin Cao
    • 1
  • Chunlei Zhang
    • 2
  • Guangming Li
    • 2
  • Baojun Zhang
    • 3
  • Suolao Zhao
    • 3
  • Baoqing Wang
    • 3
  • Zhiqing Jin
    • 1
  • Dawei Zhu
    • 1
  • Juanjuan Zhu
    • 3
  • Xiufang Wei
    • 1
  1. 1.Institute of Agricultural Resources and Environment Research/Engineering Research Centerfor Digital AgricultureJiangsu Academy of Agricultural SciencesJiangsu ProvinceChina
  2. 2.Institute of Oil Crops ResearchChinese Academy of Agricultural SciencesHubei ProvinceChina
  3. 3.Northwest Sci-TechUniversity of Agriculture and ForestryShaanxi ProvinceChina