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基于调亏理论和模糊控制的寒地水稻智能灌溉策略

张伶鳦, 王润涛, 张长利, 王树文, 徐天龙

张伶鳦, 王润涛, 张长利, 王树文, 徐天龙. 基于调亏理论和模糊控制的寒地水稻智能灌溉策略[J]. 农业工程学报, 2016, 32(13): 52-58. DOI: 10.11975/j.issn.1002-6819.2016.13.008
引用本文: 张伶鳦, 王润涛, 张长利, 王树文, 徐天龙. 基于调亏理论和模糊控制的寒地水稻智能灌溉策略[J]. 农业工程学报, 2016, 32(13): 52-58. DOI: 10.11975/j.issn.1002-6819.2016.13.008
Zhang Lingyi, Wang Runtao, Zhang Changli, Wang Shuwen, Xu Tianlong. Intelligent irrigation strategy based on regulated deficit theory and fuzzy control for rice in cold region[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(13): 52-58. DOI: 10.11975/j.issn.1002-6819.2016.13.008
Citation: Zhang Lingyi, Wang Runtao, Zhang Changli, Wang Shuwen, Xu Tianlong. Intelligent irrigation strategy based on regulated deficit theory and fuzzy control for rice in cold region[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(13): 52-58. DOI: 10.11975/j.issn.1002-6819.2016.13.008

基于调亏理论和模糊控制的寒地水稻智能灌溉策略

基金项目: 国家“863”项目(AA2013102303);黑龙江省博士后科研启动基金(LBH-Q13022);东北农业大学研究生科技创新基金(yjscx14003);省自然科学基金面上项目(C2015006);哈尔滨市科技创新人才项目(2015RQQXJ020)
详细信息
    通讯作者:

    张伶鳦, Email: 398160005@qq.com

    王树文, Email: wswtr@163.com

Intelligent irrigation strategy based on regulated deficit theory and fuzzy control for rice in cold region

  • 摘要: 为了精确判断寒地水稻需水量并建立合适的智能灌溉策略,进行适时适量灌溉,实现寒地水稻优质高产,设计了基于调亏理论和模糊控制的寒地水稻智能灌溉策略。该智能灌溉策略主要包括模糊控制灌溉和预测灌溉两部分。其中,模糊灌溉模块是二级模糊控制过程,通过一级模糊控制确定当前土壤最佳湿度,二级模糊控制器以当前土壤湿度与最佳土壤湿度的差值和环境温度作为模糊控制器的输入量,建立多因素控制规则库,实现灌溉时间模糊控制。预测灌溉设计通过实时环境数据计算出农田蒸发蒸腾量和土壤渗透系数,建立土壤水分含量变化函数,预测何时需要灌溉。在黑龙江省方正县水稻研究院的田间试验发现,调亏灌溉节水率为20.5%,水稻的结实率和产量也高于人工灌溉,分别提高了4%和8%,说明该策略能有效防止水资源浪费,对降低农业生产成本、提高产量、改善寒地水稻品质有重要的意义。
    Abstract: Heilongjiang Province is the largest rice production base in China, but traditional irrigation method causes severe water waste and nutrient loss. Intelligent irrigation strategy based on regulated deficit irrigation and fuzzy control is a water-saving and energy-efficient method to increase rice yield and quality. Regulated deficit irrigation is a technology that based on the water requirement of rice during different growth stage rather than farmers’ experience, which can effectively improve the utilization of water resources. Automatic irrigation system is a time delay and nonlinear process, which is influenced by many factors(temperature, soil moisture, etc.) and is difficult to establish accurate mathematical models, while fuzzy control is an artificial intelligence method that based on the people’s experience and imitating people’s way of thinking to control complex system with multiple parameters. In this study, the irrigation strategy was composed by fuzzy control module and forecasting irrigation module. Fuzzy irrigation module is a two stage fuzzy control. The first stage fuzzy control determined the optimal current soil moisture. The difference between current soil moisture and optimal current soil moisture, and temperature were taken as input variables for the second stage fuzzy control, to establish the multiple-factor controlled regular database and to realize a fuzzy control of the irrigation time. Soil water loss is mainly caused by evaporation-transpiration and soil water infiltration, which could be estimated by linear regression analysis of environmental parameters. Double loop method was used to measure soil permeability coefficient. The forecasting irrigation module established the soil moisture changing function to forecast when to irrigate by fusing evaporation-transpiration, soil permeability coefficient and meteorological factors. A field research was carried out in Fangzheng County, Heilongjiang Province, and the result showed the water saving rate of regulated deficit irrigation was 20.5%, and the seed setting rate and yield was improved by 4% and 8%, respectively, compared to manual irrigation, which indicated the irrigation strategy used in this study could decrease water waste efficiently and also play critical roles in reducing agriculture production cost, increasing rice yield and improving rice quality.
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出版历程
  • 收稿日期:  2016-01-20
  • 修回日期:  2016-04-08
  • 发布日期:  2016-06-30

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