Authors

Abstract

This paper combines the image processing and analysis technology of artificial intelligence to realize the function of farmland data acquisition and analysis. The data acquisition function is completed by different types of sensors. The collected information can be divided into two categories: meteorological information and image and GPS information. Based on cloud computing technology, an information collection system for rice regional experiment was established. The information collected by the sensor was analysed by cloud computing technology, which provided a basis for agronomic operation and result evaluation of regional experiment. The test results show that there is no significant difference between the rice data collected by cloud computing and the manually collected rice data. It can replace the manually collected rice information, reduce labour costs and improve experimental quality. Regional test of crop varieties is an intermediate link in the breeding and popularization of new varieties, and the results of regional test are the main basis for the approval of crop varieties. With the popularization and application of network, it brings opportunities for the networking of regional test management, statistics and variety evaluation. At the same time, with the help of network function, it can realize the online transmission of data, solve the delay problem of regional test results, and query the statistical analysis and evaluation results of regional test at any time.

Abstract in Chinese

本文结合人工智能的图像处理与分析技术，实现了农田数据采集与分析的功能。数据采集功能由不同类型的传感器完成，采集的信息可分为两类，一类是气象信息，另一类是图像和GPS信息。基于云计算技术，建立了水稻区域试验信息采集系统，利用云计算技术对传感器采集到的信息进行分析，为区域试验的农艺操作和结果评价提供依据。测试结果表明，云计算采集的大米数据与人工采集的大米数据没有明显差异，可以替代人工采集的大米信息，降低人工成本，提高实验质量。农作物品种区域试验是新品种选育和推广的中间环节，区域试验结果是农作物品种审定的主要依据。随着网络的普及和应用，给区域试验管理、统计和品种评价网络化带来了机遇。同时，借助网络功能，可以实现数据的在线传输，解决区域测试结果的延时问题，随时查询区域测试的统计分析和评价结果。