Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms

Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It crucial to assess degree penetration resistance discover solutions consequences compaction. In order obtain appropriate value, using cone requires time labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, computer software help measure quickly easily within precision agriculture applications approach. The quantitative relationships between properties factors their diversity contribute digital mapping. Digital maps use machine learning algorithms determine above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector (SVR), cubist, random forest (RF), artificial neural networks (ANN). Machine made it possible predict from huge sets environmental data obtained onboard sensors on satellites other sources produce based classification slope, but whose output must be verified if they are trusted. This review presents new technological developments in contribution techniques prediction.