苏南地区变量施肥电子处方图系统的构建与应用

发布时间：2018-04-05 02:06

本文选题：百度地图API　切入点：电子处方图变量施肥　出处：《中国农业大学学报》2017年08期

【摘要】：为在苏南地区农村推广变量施肥技术提供一种可能的实施途径,根据苏南地区的农业生产实践经验,探讨一种简易的农田施肥处方的获取途径,并结合百度地图API构建变量施肥电子处方图系统,对系统结构和实现方法进行了详细介绍,重点讨论农田电子地图的构建与应用普通精度GPS模块实现田块快速定位识别的方法。以江苏省南京市双鱼龙庄13.3hm2试验田为测试对象,在Android设备上构建相应的电子处方图系统,并进行基于自然田块的定位识别性能测定试验和变量施肥试验。试验结果表明:系统测试数据稳定,定位信息经过卡尔曼滤波算法处理后,当测试点距离农田边界2m时,定位识别正确率达到86.8%,距离边界2m时,定位识别正确率达到100%。系统指导变量施肥机施肥,其实际播量相对误差小于5.9%。说明本系统能够有效识别作业位置,具备指导田间变量施肥的能力。具备在苏南地区农村推广应用的前景。
[Abstract]:In order to provide a possible way to popularize variable-rate fertilization technology in rural areas of southern Jiangsu province, a simple way to obtain fertilizer prescription for farmland is discussed according to the practical experience of agricultural production in southern Jiangsu province.Combined with Baidu map API to construct variable rate fertilization electronic prescription map system, the system structure and realization method are introduced in detail. The construction of farmland electronic map and the method of realizing field block fast location identification by using common precision GPS module are discussed emphatically.Taking Pisces Longzhuang 13.3hm2 experimental field in Nanjing, Jiangsu Province as the test object, the corresponding electronic prescription map system was constructed on Android equipment, and the performance measurement test and variable rate fertilization test based on natural field were carried out.The experimental results show that the system test data is stable and the location information is processed by Kalman filter algorithm. When the test point is 2 m from the farmland boundary, the accuracy rate of location recognition reaches 86.8%, and when the distance boundary is 2m m, the accuracy rate of location recognition reaches 100%.The relative error of sowing quantity is less than 5.9.It shows that the system can effectively identify the working position and has the ability to guide the field variable fertilization.It has the prospect of popularizing and applying in the rural areas of southern Jiangsu.
【作者单位】：南京农业大学工学院;
【基金】：“十二五”国家科技支撑计划资助项目(2013BAD08B04-1) 大学生创新创业训练项目(201510307091)
【分类号】：S147;TP311.52

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