张智勇,马旭颖,龙耀威,李松,孙红,李民赞.作物叶片叶绿素动态监测系统设计与试验[J].农业机械学报,2019,50(Supp):115-121,166.
ZHANG Zhiyong,MA Xuying,LONG Yaowei,LI Song,SUN Hong,LI Minzan.Design and Development of Crop Chlorophyll Dynamic Monitoring System Based on Internet of Things[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(Supp):115-121,166.
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作物叶片叶绿素动态监测系统设计与试验   [下载全文]
Design and Development of Crop Chlorophyll Dynamic Monitoring System Based on Internet of Things   [Download Pdf][in English]
投稿时间:2019-04-25  
DOI:10.6041/j.issn.1000-1298.2019.S0.019
中文关键词:  叶绿素含量  动态监测  光谱分析  物联网
基金项目:国家重点研发计划项目(2018YFD0300505-1)、国家自然科学基金项目(31501219)、中国农业大学研究生实践教学基地建设项目(ZYXW037)和中国农业大学研究生课程建设项目(HJ2019029、YW2019018)
作者单位
张智勇 中国农业大学 
马旭颖 中国农业大学 
龙耀威 中国农业大学 
李松 中国农业大学 
孙红 中国农业大学 
李民赞 中国农业大学 
中文摘要:为了实现作物生长过程中叶绿素的动态在线监测,设计开发了一款叶绿素在线检测传感器系统。应用可见-近红外(660、880nm)波段光谱检测植物叶绿素含量的体积小、功耗低的模块,通过AD转换电路、数字滤波电路得到叶片反射光数字信号,利用灰度板对反射光信号进行反射率校准,660nm和880nm波段的反射率校正模型的R2分别为0.9996和0.9995;取10个不同等级叶绿素溶液样本共80个,使用国标法检测叶绿素含量后将溶液倒入无纺布开展叶绿素梯度仿真测量。叶绿素检测模块测量双波长反射率后,分别计算归一化差值植被指数(NDVI)和叶绿素指标SPAD指数值。建立相应的叶绿素含量检测数学模型,其决定系数R2分别为0.9557、0.9587。开展活体植株叶绿素检测验证试验,叶片原位光谱测量后,再将叶片剪碎,使用国标法测量叶绿素真实值,检测样本与真实值的相关系数分别为0.8887、0.8745。进而开展在线动态监测试验,实时监测水肥胁迫组和正常水肥管理对照组玉米幼苗植株,监测90h内的叶绿素含量变化,可知,相同管理条件下植株叶绿素含量变化规律大致相同,受水肥胁迫的影响,水肥胁迫组的叶绿素浓度呈下降趋势。证明了传感器系统在线监测作物叶绿素动态的可行性,可为农作物生长与胁迫动态监测提供技术支持。
ZHANG Zhiyong  MA Xuying  LONG Yaowei  LI Song  SUN Hong  LI Minzan
China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University and China Agricultural University
Key Words:chlorophyll content  dynamic monitoring  spectral analysis  internet of things
Abstract:In order to implement the agricultural IoT systems of chlorophyll dynamic monitoring the function, a visible near infrared (660nm, 880nm) band spectral module was designed with the characteristics of small volume and low power consumption for the chlorophyll content detection in plants. Through AD conversion circuit, digital filter circuit was designed to get the blade reflected light digital signal. The reflectivity of reflected light signal was calibrated by gray scale plate, the R2 of the reflectivity correction model at 660nm and 880nm were 0.9996 and 09995, respectively. A total of 80 samples of 10 different grades were taken, and the chlorophyll content was detected by national standard method. The solution was poured into non woven cloth and measured by chlorophyll detection module. The normalized vegetation index (NDVI) value and soil and plant analyzer development (SPAD) value were obtained by the calculation of dual bands spectral reflectance, and the corresponding mathematical model was established to monitor the chlorophyll content. As a result, the determination coefficient R2 was 0.9557 and 0.9587, respectively. An experiment was conducted to establish the chlorophyll content monitoring model. After the spectrum signal measurement by chlorophyll detection module in the living plants nondestructively, the leaves were sampled and measured to get the true value of chlorophyll with the national standard method. According to NDVI and SPAD parameter, the correlation coefficient between the detection value and the true value was 0.8887 and 0.8745. Furthermore, an online dynamic monitoring experiment was conducted to monitor maize seedlings in the water fertilizer stress group and the normal water fertilizer management control group in real time. The chlorophyll changes in the plants were detected within 90h. Under the same management conditions, the chlorophyll change rules of plants were roughly the same. Under the influence of water and fertilizer stress, the chlorophyll concentration in the water and fertilizer stress group showed a downward trend. It was showed that the sensor system was feasible to monitor the chlorophyll dynamics of crops online and can provide support for crop information acquisition.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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