The scientists studied how to predict soil moisture levels by sampling soil at different depths and using soil texture and density as inputs. They used artificial neural networks to make these predictions. The results showed that linear regression can help reduce prediction errors. The accuracy of predicting saturated water capacity was better than predicting other water capacities. More information like soil structure and organic matter content is needed to improve accuracy.