Virtual Research Environments (VREs) bridge the gap between the compute and storage infrastructure becoming available as the ‘cloud’, and the needs of researchers for tools supporting open science and analytics on ever larger datasets. In the AGINFRA PLUS project such a VRE, based on the D4Science platform, was examined to improve and test its capabilities for running large numbers of crop simulations at field level, based on the WOFOST-WISS model and Dutch input datasets from the AgroDataCube. Using the gCube DataMiner component of the VRE, and based on the Web Processing Service standard, a system has been implemented that can run such workloads successfully on an available cluster, and with good performance, providing summarized results to agronomists for further analysis. The methods used and the resulting implementation are briefly described in this paper. Overall the approach seems viable and opening the door to many follow-up implementation opportunities and further research. Some of them are indicated in more detail in the conclusions.