Remote sensing of soybean canopy as a tool to map high pH, calcareous soils at field scale

Abstract

Soybean (Glycine max Merr.) is extensively grown in areas of the US Corn Belt where soils often range from relatively acid (pH < 6) to alkaline, calcareous. Iron availability decreases with increase in pH, consequently, soybean can suffer from iron deficiency chlorosis on high pH, calcareous areas of the field. The extent of those areas sometimes can be significant, but they often occur in complex and discontinuous patterns. The objective of the research was to explore how remote sensing of soybean canopies and GIS technologies could be used to map and quantitatively describe the extent of high pH, calcareous soils at field scale. Aerial images that consisted of visible red, green, blue, and near infrared bands were used to calculate green normalized difference vegetative index (GNDVI) and to guide plant and soil sampling at 10 fields during 2003 and 2004 growing seasons. Ten to 18 sampling areas were selected on each field to include a wide range in GNDVI values. Soil samples were analyzed for pH and calcium carbonate equivalent (CCE). Plant samples were used to estimate grain yields. Soil pH and CCE were significantly correlated with GNDVI values in eight and seven sites, respectively. A previously developed alkalinity stress index (ASI), which combines pH and CCE in one value, was significantly related to GNDVI at all 10 sites. Remote sensing of soybean canopy was shown to be a promising tool that can be used to quantitatively describe distribution of alkaline soils at field scale.