基于移动GIS的家庭农场精准施肥系统设计
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摘要
【目的】家庭农场是目前中国大力发展的新型农业生产主体,精准施肥是满足家庭农场现代化生产管理需求的重要研究方向和技术难点。研究智能手机和移动GIS技术有助于实时、准确地对农场的养分进行便捷管理。【方法】智能手机端APP结合Web端管理系统成为实现家庭农场精准施肥的主要技术手段。文章对样本点的土壤养分数据进行Kriging插值,进而利用养分平衡法施肥模型对整个地块的土壤数据进行分析,得到精准施肥矢量图并同步到Web端,最终指导变量施肥机进行变量精准施肥作业。【结果】(1)整个系统通过移动端对地块进行管理并获取数据,利用数据管理层同步数据并上传至服务端生成推荐施肥方案,并导出至移动端和变量施肥机;(2)系统在河南、河北和北京3个实验基地进行了初步试验,从信息采集、录入到养分管理、生成施肥方案等过程均验证了系统的实用性;(3)相对于传统施肥,利用系统的精准施肥方案施氮肥可平均节约纯氮约18 kg/hm2。【结论】系统使用方式灵活、方便且对使用人员技术要求低,相对于传统管理模式,工作效率有显著提高。该系统的推广使用可降低化肥使用量,节约成本且可以减少环境压力,对促进农业信息化、现代化具有重要意义。
[Purpose]Family farm,a new type of agricultural production,is being developed vigorously in China.In this way,precision fertilization becomes an important research direction and technical difficulty to meet the needs of modern production management of family farm.With the development of smart phones and mobile Geographical Science Information(GIS)technology,it is more convenient to make real-time and accurate management of farm nutrients.[Method]Therefore,the mobile terminal APP combined with the website management system are the main technical means to achieve accurate fertilization on family farms.In this system,the Kriging interpolation is carried out on the soil nutrient data of the sample points,and then the soil data of the whole plot is analyzed by the nutrient balance fertilization model.Afterwards,the precise fertilization vector can be obtained and will be exported to the mobile terminal.Finally,the system can synchronize the fertilization decision to the Web and this would guide the variable fertilizer applicator to carry out the scheme.[Result](1)The whole system records data through the mobile terminal and manages the land parcel.And then the system uses the data management layer to synchronize the data and upload it to the server in order to generate the recommended fertilization scheme which will be exported to the phone APP and the variable fertilizer applicator;(2)The system carried out preliminary experiments in three experimental bases in Henan Province,Hebei Province and Beijing,and verified the practicality of the system from information collection,entry to nutrient management,and generation of fertilization programs;(3)Relative to traditional fertilization utilization,the precise fertilization scheme of the system can save an average of about 1.2 kg/mu of pure nitrogen.[Conclusion]Compared with the traditional management system,this system is more flexible,more convenient,more efficiency and requires lower skills for users.In this way,the widespread of this system can reduce chemical fertilizer dosage,save costs and reduce environmental pressure,which is of great significance to promote the informatization and modernization of agricultural.
[Purpose]Family farm,a new type of agricultural production,is being developed vigorously in China.In this way,precision fertilization becomes an important research direction and technical difficulty to meet the needs of modern production management of family farm.With the development of smart phones and mobile Geographical Science Information(GIS)technology,it is more convenient to make real-time and accurate management of farm nutrients.[Method]Therefore,the mobile terminal APP combined with the website management system are the main technical means to achieve accurate fertilization on family farms.In this system,the Kriging interpolation is carried out on the soil nutrient data of the sample points,and then the soil data of the whole plot is analyzed by the nutrient balance fertilization model.Afterwards,the precise fertilization vector can be obtained and will be exported to the mobile terminal.Finally,the system can synchronize the fertilization decision to the Web and this would guide the variable fertilizer applicator to carry out the scheme.[Result](1)The whole system records data through the mobile terminal and manages the land parcel.And then the system uses the data management layer to synchronize the data and upload it to the server in order to generate the recommended fertilization scheme which will be exported to the phone APP and the variable fertilizer applicator;(2)The system carried out preliminary experiments in three experimental bases in Henan Province,Hebei Province and Beijing,and verified the practicality of the system from information collection,entry to nutrient management,and generation of fertilization programs;(3)Relative to traditional fertilization utilization,the precise fertilization scheme of the system can save an average of about 1.2 kg/mu of pure nitrogen.[Conclusion]Compared with the traditional management system,this system is more flexible,more convenient,more efficiency and requires lower skills for users.In this way,the widespread of this system can reduce chemical fertilizer dosage,save costs and reduce environmental pressure,which is of great significance to promote the informatization and modernization of agricultural.
引文
[1]中央农办,农业农村部.中央农村工作领导小组办公室农业农村部关于做好2019年农业农村工作的实施意见.农民日报,2019.
[2]于合龙,赵新子,陈桂芬,等.基于改进的BP神经网络集成的作物精准施肥模型.农业工程学报,2010,26(12):193~198.
[3]Francesco N,Roberto C,Alberto C,et al.An operational workflow to assess rice nutritional status based on satellite imagery and smartphone apps.Computers and Electronics in Agriculture,2018,154:80~92.
[4]田文俊.面向家庭农场的移动精准施肥辅助决策系统研究与应用.武汉:湖北大学,2017.
[5]苏昕,王可山,张淑敏.我国家庭农场发展及其规模探讨--基于资源禀赋视角.农业经济问题,2014,35(5):8~14.
[6]Chen C,Pan J,Shu K L.A review of precision fertilization research.Environmental Earth Sciences,2014,71(9):4073~4080.
[7]Walker T,Friday J,Casimero M,et al.The early economic impact of a nutrient management decision support system(NuMaSS)on small farm households cultivating maize on acidic,upland soils in the Philippines.Agricultural Systems,2009,101(3):162~172.
[8]Elprince A M.Prediction soil fertilization maps using logistic modeling and a geographical information system.Soil Science Society of America Journal,2009,73(6):2032~2042.
[9]陈云坪,赵春江,王秀,等.基于知识模型与WebGIS的精准农业处方智能生成系统研究.中国农业科学,2007,40(6):1190~1197.
[10]许鑫,张浩,席磊,等.基于WebGIS的小麦精准施肥决策系统.农业工程学报,2011,27(S2):94~98.
[11]陈小虎,蒋佐升,黄铁平,等.主要农作物推荐施肥智能手机专家系统的开发应用.作物研究,2014(5):527~532.
[12]苗孝可,夏克俭,王秀.精准农业变量施肥智能决策支持系统的研究.计算机应用,2004,24(11):153~155.
[13]孙波,严浩,施建平,等.基于组件式GIS的施肥专家决策支持系统开发和应用.农业工程学报,2006,22(4):75~79.
[14]司秀丽,李伟为.基于WebGIS的玉米精准施肥系统的研究与设计.安徽农业大学学报,2012,39(1):144~149.
[15]蒋红军,刘小军,等.基于模型和3S技术的数字麦作系统的设计与实现.麦类作物学报,2007,27(5):908~913.
[16]Downstream Services for Rice Crop Monitoring in Europe:From Regional to Local Scale.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017:1~19.
[17]汪小旵,陈满,孙国祥,等.冬小麦变量施肥机控制系统的设计与试验.农业工程学报,2015,31(S2):88~92.
[18]余洪锋,丁永前,刘海涛,等.小田块变量施肥系统优化设计与应用.农业工程学报,2018,34(3):35~41.
[19]杨硕,王秀,翟长远,等.支持种肥监测的变量施肥系统设计与试验.农业机械学报,2018,49(10):145~153.
[20]安晓飞,王晓鸥,付卫强,等.四要素变量施肥机肥箱施肥量控制算法设计与试验.农业机械学报,2018,49(S1):149~154.
[21]王秀,赵春江,孟志军,等.精准变量施肥机的研制与试验.农业工程学报,2004,20(5):114~117.
[22]耿向宇,李彦明,苗玉彬,等.基于GPRS的变量施肥机系统研究.农业工程学报,2007,23(11):164~167.
[23]马晓蕾,范广博,李永玉,等.精准施肥决策模型与数据库系统.农业机械学报,2011,42(5):193~197.
[24]侯彦林,陈守伦.施肥模型研究综述.土壤通报,2004,35(4):493~501.
[25]苏伟,聂宜民,胡晓洁,等.利用Kriging插值方法研究山东龙口北马镇农田土壤养分的空间变异.安徽农业大学学报,2004,31(1):76~81.
[2]于合龙,赵新子,陈桂芬,等.基于改进的BP神经网络集成的作物精准施肥模型.农业工程学报,2010,26(12):193~198.
[3]Francesco N,Roberto C,Alberto C,et al.An operational workflow to assess rice nutritional status based on satellite imagery and smartphone apps.Computers and Electronics in Agriculture,2018,154:80~92.
[4]田文俊.面向家庭农场的移动精准施肥辅助决策系统研究与应用.武汉:湖北大学,2017.
[5]苏昕,王可山,张淑敏.我国家庭农场发展及其规模探讨--基于资源禀赋视角.农业经济问题,2014,35(5):8~14.
[6]Chen C,Pan J,Shu K L.A review of precision fertilization research.Environmental Earth Sciences,2014,71(9):4073~4080.
[7]Walker T,Friday J,Casimero M,et al.The early economic impact of a nutrient management decision support system(NuMaSS)on small farm households cultivating maize on acidic,upland soils in the Philippines.Agricultural Systems,2009,101(3):162~172.
[8]Elprince A M.Prediction soil fertilization maps using logistic modeling and a geographical information system.Soil Science Society of America Journal,2009,73(6):2032~2042.
[9]陈云坪,赵春江,王秀,等.基于知识模型与WebGIS的精准农业处方智能生成系统研究.中国农业科学,2007,40(6):1190~1197.
[10]许鑫,张浩,席磊,等.基于WebGIS的小麦精准施肥决策系统.农业工程学报,2011,27(S2):94~98.
[11]陈小虎,蒋佐升,黄铁平,等.主要农作物推荐施肥智能手机专家系统的开发应用.作物研究,2014(5):527~532.
[12]苗孝可,夏克俭,王秀.精准农业变量施肥智能决策支持系统的研究.计算机应用,2004,24(11):153~155.
[13]孙波,严浩,施建平,等.基于组件式GIS的施肥专家决策支持系统开发和应用.农业工程学报,2006,22(4):75~79.
[14]司秀丽,李伟为.基于WebGIS的玉米精准施肥系统的研究与设计.安徽农业大学学报,2012,39(1):144~149.
[15]蒋红军,刘小军,等.基于模型和3S技术的数字麦作系统的设计与实现.麦类作物学报,2007,27(5):908~913.
[16]Downstream Services for Rice Crop Monitoring in Europe:From Regional to Local Scale.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017:1~19.
[17]汪小旵,陈满,孙国祥,等.冬小麦变量施肥机控制系统的设计与试验.农业工程学报,2015,31(S2):88~92.
[18]余洪锋,丁永前,刘海涛,等.小田块变量施肥系统优化设计与应用.农业工程学报,2018,34(3):35~41.
[19]杨硕,王秀,翟长远,等.支持种肥监测的变量施肥系统设计与试验.农业机械学报,2018,49(10):145~153.
[20]安晓飞,王晓鸥,付卫强,等.四要素变量施肥机肥箱施肥量控制算法设计与试验.农业机械学报,2018,49(S1):149~154.
[21]王秀,赵春江,孟志军,等.精准变量施肥机的研制与试验.农业工程学报,2004,20(5):114~117.
[22]耿向宇,李彦明,苗玉彬,等.基于GPRS的变量施肥机系统研究.农业工程学报,2007,23(11):164~167.
[23]马晓蕾,范广博,李永玉,等.精准施肥决策模型与数据库系统.农业机械学报,2011,42(5):193~197.
[24]侯彦林,陈守伦.施肥模型研究综述.土壤通报,2004,35(4):493~501.
[25]苏伟,聂宜民,胡晓洁,等.利用Kriging插值方法研究山东龙口北马镇农田土壤养分的空间变异.安徽农业大学学报,2004,31(1):76~81.