Deployed the validated model as the CeresAI-nano web application on the Enalos Cloud Platform. Predicting Nano-Enabled Agriculture Impacts Computationally. Nanoparticles are increasingly used in agriculture as fertilisers, biostimulants, and pesticides to support sustainable food production. However, the interaction between NP properties, soil systems, and plant species is highly complex, and conventional assessment of NP–plant interactions requires long, resource-intensive experiments. 85% Model Accuracy - XGBoost model achieves high accuracy on external validation 83% Balanced Accuracy - Strong performance across all plant response classes No Lab - Virtual Screening - Predictions require no experimental input data QMRF - Documented Model - Standardised QSAR model reporting format for regulatory use FAIR - Open Data - Curated dataset available through nanoPharos database SSbD - Sustainable Design - Supports safe and sustainable development of nano-agrochemicals
