Design and Application of Data Acquisition and Analysis System for CropSense

Abstract

In view of the demand of small and medium-sized farms for rapid monitoring and accurate diagnosis of crop growth, the National Engineering Research Center for Information Technology in Agriculture (NERCITA) designed a crop growth monitoring device which named CropSense. It is a portable crop health analysis instrument based on dual-channel high-throughput spectral signals which derived from the incident and reflected light intensity of the crop canopy at red and near-infrared bands. A data collecting and analyzing system for CropSense was designed and implemented. It consisted of a mobile application for collecting data of CropSense and a server-side system for data and model management. The system could implement data collecting, processing, analyzing and management completely calculate normalized differential vegetation index (NDVI) based on the two-channels spectral sampling data from CropSense which connects smart phone by Bluetooth, then generats crop growth parameters about nitrogen content, chlorophyll content and Leaf Area Index with the built-in spectral inversion model in the server. Meanwhile, it could calculate vegetation coverage, density and color content by images captured from the camera of smart phone. When the sampling program was finished , it could generate growth parameter thematic maps by Kriging interpolation based on all sampling data of the selected fields. Considering the target yield of the plot, it could provide expert advice visually. Users could get diagnostic information and professional guiding scheme of crop plots immediately after collecting data by touch a button. Now the device and system have been applied in some experimental farms of research institutes. This paper detailed discribed the application of the system in Xiaotangshan farm of NERCITA. Compared with the traditional corn flare period samples and fertilize schemes, users could avoid errors caused by manual recording. Besides, with the same corn yield, the fertilization amount had reduced 16.67% when using the generation of the variable fertilization scheme by this system. The result showed that the system could get the crop growth status efficiently and produced reasonable fertilization collecte and analyze crop growth efficiently and conveniently. It is suitable for various farmers without expertise to obtain the information of the crop growth timely and can guide them to operate more effectively and economically in the field. The system can save data to web server through the Internet which improves the shortcoming of poor sharing in the traditional data exporting mode. And this system is practical and promising, and will be widely applied in the explosion of family farms in China.

Keywords

• data collection
• growth analysis
• real-time diagnosis
• expert decision