基于云服务架构的田间信息采集与分析系统设计
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摘要
为了满足农田作物信息采集和分析服务的需求,将智能手机终端硬件、微信小程序软件与云服务平台相结合,设计了一款基于云服务架构的田间信息采集与分析系统。系统主要包括腾讯云服务器模块和手机微信小程序模块,其中,云服务器端使用MySQL搭建数据库,用于存储、处理和下载数据;使用CSS和Java Script语言及小程序封装的组件开发微信小程序,用于交互实现数据的采集、上传与信息反馈。以田间小麦作物生物量指征参数调查为例,针对冠层覆盖度和植株行间距计算进行了系统应用测试。采集100幅出苗期的小麦冠层图像,由小程序端上传样本图像到后台处理。使用霍夫变换、图像掩膜和图像腐蚀获取定位图像后,利用HSV彩色空间突出样本像素点,计算冠层覆盖度;采用投影法和滤波法提取峰值,获取株行中心线,从而计算植株行间距。建立了图像识别像素株行间距与实测株间行距间的一元线性回归模型,建模精度R~2达到0. 911,可为田间作物信息检测和调查提供技术支持。
In order to meet the demands of collecting and analyzing services of farmland crop information,a crop information collection and analysis tool was designed based on cloud service architecture with the combination of the smart phone terminal hardware,WeChat applet software and cloud service platform.The system mainly included Tencent-cloud server module and mobile phone WeChat applet module. The My SQL was used to build a database for data storing,processing and download on cloud server. The WeChat applet was developed by CSS,JavaScript and applet packaged components. It was used to realize the interaction between collecting and uploading data and information feedback. In order to apply and test the system,the survey of biomass indication parameters of wheat in the field was taken as an example.The researches were carried out for the calculation of canopy coverage and plant row-spacing. More than 100 sampling images of wheat were captured at seedling period,and they were uploaded from applet to background and processing. After the image preprocessing following the target area detection by using Hough transform,image mask segmentation and image enhancement with erosion processing,the canopy of wheat was segmented and the canopy coverage was calculated by using HSV color space to highlight the pixel of sampling plants. The algorithms were proposed to extract the peak line of plant by projection and filtering method. Then,it was used to calculate the plant line spacing in the row. The linear regression model was established to indicate the fitting accuracy between the line spacing of the image recognition pixels and the measured values. The result showed that the modeling accuracy R~2 reached 0. 911. It could provide a technical support for crop information detection and investigation in the field.
In order to meet the demands of collecting and analyzing services of farmland crop information,a crop information collection and analysis tool was designed based on cloud service architecture with the combination of the smart phone terminal hardware,WeChat applet software and cloud service platform.The system mainly included Tencent-cloud server module and mobile phone WeChat applet module. The My SQL was used to build a database for data storing,processing and download on cloud server. The WeChat applet was developed by CSS,JavaScript and applet packaged components. It was used to realize the interaction between collecting and uploading data and information feedback. In order to apply and test the system,the survey of biomass indication parameters of wheat in the field was taken as an example.The researches were carried out for the calculation of canopy coverage and plant row-spacing. More than 100 sampling images of wheat were captured at seedling period,and they were uploaded from applet to background and processing. After the image preprocessing following the target area detection by using Hough transform,image mask segmentation and image enhancement with erosion processing,the canopy of wheat was segmented and the canopy coverage was calculated by using HSV color space to highlight the pixel of sampling plants. The algorithms were proposed to extract the peak line of plant by projection and filtering method. Then,it was used to calculate the plant line spacing in the row. The linear regression model was established to indicate the fitting accuracy between the line spacing of the image recognition pixels and the measured values. The result showed that the modeling accuracy R~2 reached 0. 911. It could provide a technical support for crop information detection and investigation in the field.
引文
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[20]MUKHOPADHYAY P,CHAUDHURI B B.A survey of Hough transform[J].Pattern Recognition,2015,48(3):993-1010.
[21]王思乐,杨文柱,卢素魁.大田作物长势监控图像中绿色植物的识别方法[J].江苏农业科学,2015,43(11):487-492.WANG Sile,YANG Wenzhu,LU Sukui.Identification method of green plants in field crop growth monitoring image[J].Jiangsu Agricultural Sciences,2015,43(11):487-492.(in Chinese)
[2]JAT R D,JAT H S,NANWAL R K,et al.Conservation agriculture and precision nutrient management practices in maize-wheat system:effects on crop and water productivity and economic profitability[J].Field Crops Research,2018,222:111-120.
[3]孙红,文瑶,赵毅,等.基于图像颜色特征的密植冬小麦覆盖指数反演[J].农业机械学报,2015,46(增刊):240-245.SUN Hong,WEN Yao,ZHAO Yi,et al.Retrieving vegetation coverage index of winter wheat based on image colour characteristic[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(Supp.):240-245.(in Chinese)
[4]LIU J,PATTEY E,ADMIRAL S.Assessment of in situ crop LAI measurement using unidirectional view digital photography[J].Agricultural&Forest Meteorology,2013,169(1):25-34.
[5]MAJASALMI T,KORHONEN L,KORPELA I,et al.Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index[J].International Journal of Applied Earth Observation&Geoinformation,2017,59:53-62.
[6]GUI Y P,LIAN Q Z,ZHOU S.Estimating rice LAI based on digital camera and image processing[J].Key Engineering Materials,2012,500:586-591.
[7]TAO Zhiqiang,CHEN Yuanquan,ZOU Juanxiu,et al.Spectral characteristics of spring maize varieties with different heat tolerance to high temperature[J].Spectroscopy and Spectral Analysis,2016,36(2):520-526.
[8]CARRASCO-BENAVIDES M,MORA M,MALDONADO G,et al.Assessment of an automated digital method to estimate leaf area index(LAI)in cherry trees[J].New Zealand Journal of Experimental Agriculture,2016,44(4):15-30.
[9]FAN X,KAWAMURA K,XUAN T D,et al.Low-cost visible and near-infrared camera on an unmanned aerial vehicle for assessing the herbage biomass and leaf area index in an Italian ryegrass field[J].Grassland Science,2017,64(2):145-150.
[10]关林芳.基于“互联网+”的农田灌溉预约系统设计[D].太原:太原理工大学,2017.GUAN Linfang.Farmland irrigating reservation system based on“The Internet Plus”[D].Taiyuan:Taiyuan University of Technology,2017.(in Chinese)
[11]刘剑.基于Android平台的玉米田间杂草的识别系统设计[D].太原:山西农业大学,2016.LIU Jian.The design of the corn weed identification system based on Android platform[D].Taiyuan:Shanxi Agricultural University,2016.(in Chinese)
[12]乐羿成.基于Android的作物冠层抓拍传输及其图像自动管理系统开发[D].杭州:浙江理工大学,2017.YUE Yicheng.Development of Android based capture&transmission of crop canopy and automatic system on its image management[D].Hangzhou:Zhejiang Sci-Tech University,2017.(in Chinese)
[13]何东,宁文慧.基于云服务器和Zig Bee无线传感网络的茶园远程监控系统的设计[J].安徽农业科学,2018,46(10):189-190.HE Dong,NING Wenhui.Design of remote monitoring system for tea garden based on cloud server and Zig Bee wireless sensor network[J].Journal of Anhui Agricultural Sciences,2018,46(10):189-190.(in Chinese)
[14]韩国鑫,谭峰,马志欣,等.基于Android的水稻生长田间管理辅助决策系统[J].江苏农业科学,2019,47(2):221-225.HAN Guoxin,TAN Feng,MA Zhixin,et al.An assistant decision system for rice growing field management based on Android[J].Jiangsu Agricultural Sciences,2019,47(2):221-225.(in Chinese)
[15]张小斌,杨素,郑可锋,等.基于微信小程序的水稻减药增效信息服务平台实践与应用[J].农业网络信息,2018(2):77-80.ZHANG Xiaobin,YANG Su,ZHENG Kefeng,et al.Practice and application on information service platform for pesticide usage reduction and efficiency enhancement in rice based on We Chat mini program[J].Agriculture Network Information,2018(2):77-80.(in Chinese)
[16]彭奎,邓亚辉,赵星标,等.基于微信小程序的田间作物管理系统开发与应用[J].农村科技,2018,400(10):56-60.PENG Kui,DENG Yahui,ZHAO Xingbiao,et al.Development and application of field crop management system based on We Chat[J].Rural Science&Technology,2018,400(10):56-60.(in Chinese)
[17]武睿,乐丽红,朱安繁,等.作物营养拍照诊断服务系统设计与开发[J].江西农业学报,2018,30(8):55-59.WU Rui,LE Lihong,ZHU Anfan,et al.Design and development of crop nutrition photographing diagnosis service system[J].Acta Agricultural Jiangxi,2018,30(8):55-59.(in Chinese)
[18]雷磊.微信小程序开发入门与实践[M].北京:清华大学出版社,2017.
[19]孙建成,曾培峰,禹素萍,等.二值图像的区域标识与噪声去除[J].天津工业大学学报,2006,25(1):45-47.SUN Jiancheng,ZENG Peifeng,YU Suping,et al.Component labeling and noise eliminating of binary image[J].Journal of Tianjin Polytechnic University,2006,25(1):45-47.(in Chinese)
[20]MUKHOPADHYAY P,CHAUDHURI B B.A survey of Hough transform[J].Pattern Recognition,2015,48(3):993-1010.
[21]王思乐,杨文柱,卢素魁.大田作物长势监控图像中绿色植物的识别方法[J].江苏农业科学,2015,43(11):487-492.WANG Sile,YANG Wenzhu,LU Sukui.Identification method of green plants in field crop growth monitoring image[J].Jiangsu Agricultural Sciences,2015,43(11):487-492.(in Chinese)