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棉花适宜密度与播种量设计的动态知识模型 被引量:7

Dynamic Knowledge Model for Design of Population Density and Sowing Rate in Cotton
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摘要 通过分析和提炼有关棉花种植密度与播种量的最新研究资料,在综合量化气候条件、土壤类型、产量目标、管理水平和品种特性等影响因子的基础上,建立了具有时空适应性的棉花种植密度和播种量设计动态知识模型,可用于精确定量不同环境和不同产量目标下的种植密度和播种量。利用不同生态点、不同品种、不同土壤类型和不同产量目标等资料对知识模型进行了验证,结果表明模型具有较好的决策性和适用性。 By summarizing, analyzing and extracting the newest research data on planting density and sowing rate, and basing on the knowledge of many experts in cotton, a dynamic knowledge model for decision-making on planting density and sowing rate of cotton under different environments and yield targets with extensive suitability was developed by quantifying the effects of climate, soil, yield, management level and variety. On Windows 98 system, the knowledge model and parameters were translated into comp-uter program with the VC++6.0 programing language, tested and revised with experiment data in different plant environments. Case studies on the knowledge model with the experiment data sets of different eco-sites (Anyang, Nanjing, Shihezi and Taiyuan), varieties, soil types and yields indicated the prediction results were similar to the experiment with error below 10%.It suggested that the knowledge model was good for decision-making and application.In this paper, because boll rate was effected by many factors, such as diseases and insects, when the planting density decision knowledge model was developed, the affection of boll rate to planting density should be treated simply. In the future, in order to apply the planting density knowledge model accurately in practice, it should be revised and reinforced.
出处 《棉花学报》 CSCD 北大核心 2004年第3期156-161,共6页 Cotton Science
基金 国家自然科学基金重点项目(30030090) 国家863计划项目(2003AA209030)
关键词 棉花 栽培密度 播种量 设计 动态知识模型 气候条件 土壤类型 cotton planting density sowing rate knowledge model
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