The Grant Lab has developed an innovative approach that combines Raman spectroscopy and PulpEye’s real-time physical metrics to predict paper properties instantly, transforming pulp quality control. By using machine learning, especially eXtreme Gradient Boosting (XGBoost), their method achieves lab-level accuracy in predicting paper properties from pulp attributes, reducing reliance on time-consuming manual testing and providing valuable insights into the factors influencing pulp quality.