Identification and Management of Soil Constraints—A Case Study for Australia

Abstract Soil conditions are spatially variable. Some soil conditions can be constraining to plant growth, resulting in poor crop productivity. Well-known soil constraints include extremes in pH (low and high pH), high salinity, fertility rundown and presence of toxic elements. Identification of areas/sites affected by soil constraints can be based on yield data and visual observations. Modern approaches to identifying soil constraints include remote sensing using satellite data. Landsat satellite imagery is available with 30 × 30 m pixel resolution, and this imagery can be used to help identify areas where crop growth is consistently constrained using spectral data to calculate vegetation indices. By using vegetation indices to compare sites within a field with above-average and below-average growth, and conducting targeted soil sampling, it may be possible to identify causes of low yield. We have used remote-sensing data for 20 farms in Queensland, Australia, to determine areas within fields with relatively low yield and used targeted sampling to identify the soil constraints. In this case study, we report on results for one farm. The soil constraint was then ameliorated and yield differences were determined. Information © The Authors 2025