Context or Problem: Soil constraints significantly impact crop productivity, however, the direct relationship between these constraints and crop yields remains unclear, creating a need for targeted soil management strategies to enhance agricultural output.Objective or Research Question: This study aims to clarify the influence of various soil constraints on crop productivity by examining soil indicators across distinct productivity zones on Queensland farms.Methods: Soil samples were collected from three productivity zones (consistently low, inconsistent, and consistently high) and five soil layers (D1-D5, 0-120 cm) on 21 farms in Queensland. We utilized the Constraint ID tool and applied mixed-effects models, principal component analysis, and machine learning model to soil chemical indicators including nitrate (NO3–), electrical conductivity (ECe), pH, Cl, exchangeable sodium percentage (ESP), exchangeable contents of Ca (ECa), K (EK), and Mg (EMg).Results: The results identified ECe, pH, Cl, and ESP as critical factors influencing soil fertility, particularly in the deeper layers (D3-D5, 30-120 cm), which indicate issues with salinity, alkalinity, and sodicity. However, subsoil constraints below 30 cm pose significant challenges for remediation, underscoring the importance of surface-level interventions and strategies that benefit the entire soil profile.Conclusions and Implications: This study highlights the importance of surface-level interventions that address the entire soil profile to improve soil health and crop productivity in Queensland’s agricultural systems. It underscores the need for site-specific management strategies to effectively mitigate soil constraints and optimize crop yields.