SOIL MOISTURE OF CORN CROPS IN A CONSERVATION AGRICULTURE SYSTEMS CAN BE ESTIMATED WITH RGB AND INFRARED IMAGES

Abstract

ABSTRACT Agriculture consumes the largest amount of water resources in the world; for this reason, developing technologies aimed at efficiently using these resources for food production is necessary. In the present work, red-green-blue (RGB) and infrared (IR) images of plots with corn (Zea mays L.) were used to estimate the changes in soil moisture. These images were obtained by cameras installed in an unmanned aerial vehicle (drone), which flew over the plots on different dates. The results showed that both RGB and IR images of corn plants can be used to estimate soil moisture with minimum and acceptable levels of root mean square error (with RMSEs of 1.02 and 1.58 for RGB and IR images, respectively); however, the optical response of plants can be altered by different factors in addition to changes in soil moisture; thus, the training of mathematical models to estimate this variable should preferably be performed with validation data at the plot level.

Keywords

• Unmanned aerial vehicle
• infrared images
• soil moisture
• corn cultivation