Time series analysis of soybean response to varying atmospheric conditions for precision agriculture

摘要

Four time-lapse cameras, Bushnell Nature View HD Camera (Bushnell, Overland Park, KS, USA) were installed in a soybean field to track the response of soybean plants to changing weather conditions. The purpose was to confirm if visible spectroscopy can provide useful data for tracking the condition of crops and, if so, whether game and trail time-lapse cameras can serve as reliable crop sensing and monitoring devices. Using the installed cameras, images were taken at 30-min intervals between July 22 and August 1, 2015. Using the RGBExcel software application developed in-house, image data from the R (red), G (green), and B (blue) bands were exported to Microsoft Excel for further processing and analysis. Daytime adjusted green red index data for the plant, based on the R and G data, were plotted against time of image acquisition and also regressed with selected weather parameters. The former showed a rise-and-fall trend with daily peaks around 13:00, while the latter showed a decreasing order of correlation with weather variables as follows: log of solar radiation&log of soil surface temperature&log of air temperature&log of soil temperature at 50-mm depth&log of relative humidity. Despite some low correlations, the potential for using game and trail cameras with time-lapse capability to track changes in crop vegetation response under varying conditions is established. The resulting data can be used to develop models that can aid precision agriculture applications. This can be further explored in future studies.