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温室网纹甜瓜叶面积与光合生产模拟模型研究
  • ISSN号:1000-2030
  • 期刊名称:《南京农业大学学报》
  • 时间:0
  • 分类:S625.4[农业科学—园艺学]
  • 作者机构:[1]南京农业大学农学院,江苏南京210095, [2]上海市农业科学院上海市设施园艺技术重点实验室,上海201106, [3]江苏省农业科学院园艺研究所,江苏南京210014
  • 相关基金:国家自然科学基金资助项目(60073028);国家863计划资助项目(2001AA247023);上海市科技兴农重点攻关资助项目(农科字2002第3-1-1号)
中文摘要:

依据温室温光条件与甜瓜单株叶面积的关系,建立了甜瓜叶面积指数(LAI)模型,结合已有的光合作用驱动的作物生长模型,建立了适合我国种植技术的甜瓜光合作用与干物质积累动态模型。利用不同基质、品种和播期的试验资料对模型进行了检验。结果表明,本模型较用比叶面积和叶干重的SLA法及用积温与叶面积的函数的GDD法更能准确地模拟温室甜瓜的LAI和植株总干重。LAI的模拟值与实测值之间的决定系数(R^2)和回归估计标准误(RMSE)分别为0.867和0.404,植株总干重的模拟值与实测值之间的序和RMSE分别为0.887和645kg·hm^-2。用本模型模拟LAI的精度分别比SLA法和GDD法提高78%和40%;模拟植株总干重的精度分别比SLA法和GDD法提高57%和36%。本模型不仅改善了甜瓜叶面积和干物质生产的模拟精度,而且提高了模型的实用性。

英文摘要:

A greenhouse muskmelon leaf area simulation model was developed based on the relationship between leaf area per plant and the product of thermal effectiveness and photosynthetically active radiation (TEP). Then a process-based photosynthesis and dry matter production model of greenhouse muskmelon was developed by integrating the leaf area index (LAI) model into the exist- ing photosynthesis-driven crop growth model. Experiments with different sowing dates, varieties and substrates were carried out in Shanghai and Nanjing to collect data to calibrate and validate the model. The results show that the model can predict leaf area and total dry weight of greenhouse muskmelon more accurately than the traditional specific leaf area (SLA) and growing degree days (GDD) based models. The determination coefficient (R2) and the root mean squared error (RMSE) between the observed and the predicted LAI based on the 1 : 1 line are 0. 867 and 0. 404, respectively. The R^2 and RMSE between the predicted and the measured total biomass based on the 1 : 1 line are 0. 887 and 645 kg · hm^-2, respectively. Compared to the SLA and GDD based models, the prediction accuracy of the TEP based model is 78% and 40% higher, respectively, for LAI, and 57% and 36% higher, respectively, for total biomass. The model developed in this study improves not only the prediction accuracy of leaf area and dry matter production, but also the user-friendliness of the model.

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期刊信息
  • 《南京农业大学学报》
  • 北大核心期刊(2011版)
  • 主管单位:中华人民共和国教育部
  • 主办单位:南京农业大学
  • 主编:郑小波
  • 地址:江苏省南京市卫岗1号
  • 邮编:210095
  • 邮箱:nauxb@njau.edu.cn
  • 电话:025-84395214
  • 国际标准刊号:ISSN:1000-2030
  • 国内统一刊号:ISSN:32-1148/S
  • 邮发代号:28-53
  • 获奖情况:
  • 中国自然科学核心期刊,全国优秀科技期刊,第二届江苏省十佳科技期刊,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 美国化学文摘(网络版),英国农业与生物科学研究中心文摘,波兰哥白尼索引,英国动物学记录,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:22558