大田作物冠层无损检测设备应用及车载平台开发
发布时间：2018-10-18 21:28
【摘要】：为了响应国家转变农业发展方式,实施农业现代化改革号召,推行精细农业生产理念与管理方式,从根本上改变农民化肥的均匀播撒,引导其根据农作物生长情况及土壤养分情况适量播撒,避免形成浪费和环境污染。本课题针对大田作物冠层无损检测设备进行硬件开发及田间试验,仪器开发难度适中,试验结果精度较高,主要分为以三部分内容:(1)设计开发基于光谱分析技术及ZigBee无线网络技术的禾信通作物长势监测仪,包括采集节点与控制器两部分。采集节点包括ZigBee芯片的选取、硬件电路系统、光学结构和软件系统。控制器设计包括手持式内嵌PDA控制器与个人PC机USB协调器,完成两种控制器的硬件电路、软件设计,并针对PDA控制器进行玉米试验。试验计算NDVI、RVI、TVI、SAVI四种常用作物监测植被指数,分析高、中、低三个水平及大田整体长势水平下各植被指数与叶绿素指标相关性,选取RVI、及(R766,R550)和(R850,R550)波段组合NDVI建立玉米冠层叶绿素含量指标检测模型。通过比较三种不同参数组合方式的建模结果,确定采用NDVI(R850,R550)建立玉米冠层叶绿素含量指标检测模型(建模精度R2为0.508,验证建模精度R2为0.458),精度较高,应用其检测结果生成的田间玉米作物叶绿素水平空间分布图,可为玉米拔节期变量作业提供技术支持。(2)设计开发无损检测车载平台,包括车体框架结构设计、控制器设计及禾信通作物长势监测仪采集节点、Topcon CropSpec氮含量传感器的搭载设计,框架采用铝型材为主要材料,驱动电机采用一体轮无刷直流电机。控制器设计包括手持控制器与车载控制器两部分,车载控制器设计包括硬件与软件设计,手持控制器作为实验员操作使用,车载控制器作为车体控制使用,并针对平台可行性进行简单的验证试验。试验将禾信通采集节点与Topcon输出的植被生长信息光谱数据进行数据处理,选取NDVI与SAVI两种植被指数对两种设备的采集数据进行相关性分析,分析结果NDVI的相关性较高,对NDVI进行建模分析,建模精度R2为0.514,验证建模精度R2为0.373。结果精度较高,车载平台可行性较好,对绿色植被的生长信息获取较准确,可进行后期大田采集实验。(3)针对田间冬小麦试验设计使用ASD地物光谱仪(Analytical Spectral Devices.USA)采集冬小麦的冠层光谱反射率数据,使用SPAD-502Plus便携式叶绿素仪测量小麦倒一叶和倒二叶的叶绿素指标(SPAD值),以及G738CM型手持式GPS记录采样点的位置信息。分别进行冠层光谱反射率小麦倒一叶和倒二叶的预处理,结果表明冠层反射光谱倒二叶的SPAD值相关系数高于倒一叶。基于相关性分析,选取敏感波段538nm、661nm、740nm和850nm分别与预处理前、后的光谱数据进行多元线性回归分析,其预处理后的模型精度较高,建模精度R2为0.48,验证建模精度R2为0.32。进而绘制大田作物长势图,可为冬小麦追肥作业提供支持。
[Abstract]:In order to respond to the national transformation of the mode of agricultural development, to carry out the call for the reform of agricultural modernization, to promote the concept and management of fine agricultural production, and to fundamentally change the uniform distribution of chemical fertilizers among farmers, It can be spread according to crop growth and soil nutrient to avoid waste and environmental pollution. In this paper, the hardware development and field test of field crop canopy nondestructive testing equipment are carried out. The development of the instrument is moderate, and the precision of the test result is high. It is mainly divided into three parts: (1) designing and developing a crop growth monitor based on spectrum analysis and ZigBee wireless network technology, which includes two parts: acquisition node and controller. The acquisition node includes the selection of ZigBee chip, hardware circuit system, optical structure and software system. The controller design includes the hand-held embedded PDA controller and the USB coordinator of personal PC machine. The hardware circuit and software design of the two controllers are completed, and the corn experiment is carried out for the PDA controller. The vegetation index monitored by four common crops of NDVI,RVI,TVI,SAVI was calculated and the correlation between vegetation index and chlorophyll index was analyzed at the three levels of high, middle and low, and the whole field growth level. RVI, and (R766N R550) and (R850 R550) band combination NDVI were selected to establish a model for the detection of chlorophyll content in maize canopy. By comparing the modeling results of three different parameter combinations, NDVI (R850 R550) was used to establish the maize canopy chlorophyll content detection model (modeling precision R2 was 0.508, and the modeling precision R 2 was 0.458), and the precision was high. The horizontal spatial distribution map of chlorophyll produced by the test results can provide technical support for maize jointing variable operation. (2) Design and development of non-destructive testing vehicle platform, including the design of car-body frame structure. The controller design and the carrying design of the, Topcon CropSpec nitrogen sensor in the collecting node of the plant growth monitor are designed. Aluminum profile is used as the main material in the frame and the brushless DC motor is used as the driving motor. The controller design includes two parts: handheld controller and vehicle controller. The design of vehicle controller includes hardware and software design. Handheld controller is used as experimenter, vehicle controller is used as carbody control. And the feasibility of the platform to carry out a simple verification test. In the experiment, the spectral data of vegetation growth information produced by Topcon and the node of Hexintong were processed, and two kinds of vegetation indexes, NDVI and SAVI, were selected to analyze the correlation between the data collected by the two equipments. The results showed that the correlation of NDVI was high. The modeling precision R2 is 0.514, and the modeling precision R2 is 0.373. Results the accuracy was high, the vehicle platform was feasible, and the growth information of green vegetation was more accurate. (3) the ASD ground object spectrometer (Analytical Spectral Devices.USA) was used to collect the canopy spectral reflectance data of winter wheat. SPAD-502Plus portable chlorophyll meter was used to measure the chlorophyll index (SPAD value) of the first and second leaves of wheat and the position information of the sampling points recorded by G738CM hand-held GPS. The canopy spectral reflectance of wheat was pretreated with the first leaf and the second leaf, respectively. The results showed that the correlation coefficient of SPAD between the two leaves was higher than that in the first leaf. Based on the correlation analysis, the sensitive band of 538nm ~ 661nm ~ (740nm) and 850nm are selected respectively and the spectral data before and after pretreatment are analyzed by multivariate linear regression analysis. The model precision is high, the modeling precision is 0.48, and the modeling precision is 0.32. Furthermore, the plot of field crop growth can provide support for winter wheat topdressing.
【学位授予单位】：东北农业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S126
本文编号：2280402
[Abstract]:In order to respond to the national transformation of the mode of agricultural development, to carry out the call for the reform of agricultural modernization, to promote the concept and management of fine agricultural production, and to fundamentally change the uniform distribution of chemical fertilizers among farmers, It can be spread according to crop growth and soil nutrient to avoid waste and environmental pollution. In this paper, the hardware development and field test of field crop canopy nondestructive testing equipment are carried out. The development of the instrument is moderate, and the precision of the test result is high. It is mainly divided into three parts: (1) designing and developing a crop growth monitor based on spectrum analysis and ZigBee wireless network technology, which includes two parts: acquisition node and controller. The acquisition node includes the selection of ZigBee chip, hardware circuit system, optical structure and software system. The controller design includes the hand-held embedded PDA controller and the USB coordinator of personal PC machine. The hardware circuit and software design of the two controllers are completed, and the corn experiment is carried out for the PDA controller. The vegetation index monitored by four common crops of NDVI,RVI,TVI,SAVI was calculated and the correlation between vegetation index and chlorophyll index was analyzed at the three levels of high, middle and low, and the whole field growth level. RVI, and (R766N R550) and (R850 R550) band combination NDVI were selected to establish a model for the detection of chlorophyll content in maize canopy. By comparing the modeling results of three different parameter combinations, NDVI (R850 R550) was used to establish the maize canopy chlorophyll content detection model (modeling precision R2 was 0.508, and the modeling precision R 2 was 0.458), and the precision was high. The horizontal spatial distribution map of chlorophyll produced by the test results can provide technical support for maize jointing variable operation. (2) Design and development of non-destructive testing vehicle platform, including the design of car-body frame structure. The controller design and the carrying design of the, Topcon CropSpec nitrogen sensor in the collecting node of the plant growth monitor are designed. Aluminum profile is used as the main material in the frame and the brushless DC motor is used as the driving motor. The controller design includes two parts: handheld controller and vehicle controller. The design of vehicle controller includes hardware and software design. Handheld controller is used as experimenter, vehicle controller is used as carbody control. And the feasibility of the platform to carry out a simple verification test. In the experiment, the spectral data of vegetation growth information produced by Topcon and the node of Hexintong were processed, and two kinds of vegetation indexes, NDVI and SAVI, were selected to analyze the correlation between the data collected by the two equipments. The results showed that the correlation of NDVI was high. The modeling precision R2 is 0.514, and the modeling precision R2 is 0.373. Results the accuracy was high, the vehicle platform was feasible, and the growth information of green vegetation was more accurate. (3) the ASD ground object spectrometer (Analytical Spectral Devices.USA) was used to collect the canopy spectral reflectance data of winter wheat. SPAD-502Plus portable chlorophyll meter was used to measure the chlorophyll index (SPAD value) of the first and second leaves of wheat and the position information of the sampling points recorded by G738CM hand-held GPS. The canopy spectral reflectance of wheat was pretreated with the first leaf and the second leaf, respectively. The results showed that the correlation coefficient of SPAD between the two leaves was higher than that in the first leaf. Based on the correlation analysis, the sensitive band of 538nm ~ 661nm ~ (740nm) and 850nm are selected respectively and the spectral data before and after pretreatment are analyzed by multivariate linear regression analysis. The model precision is high, the modeling precision is 0.48, and the modeling precision is 0.32. Furthermore, the plot of field crop growth can provide support for winter wheat topdressing.
【学位授予单位】：东北农业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S126
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