Leveraging Machine Learning And Process-based Models For Soil Organic Carbon Prediction: A Comparative Study And The Role Of Chatgpt In Soil Science

A study in Austria compared machine learning algorithms with process-based models for predicting soil organic carbon levels. While ML algorithms performed better with larger datasets, process-based models provided a better understanding of the underlying mechanisms. Combining these approaches can lead to more accurate and adaptable predictions for effective soil management.