Consumers often criticize the sensory quality of modern strawberry cultivars. Therefore, a new and fast workflow for cultivar selection was developed to aid in the development of cultivars with enhanced aroma. This workflow consists of Headspace (HS) solid-phase microextraction (SPME) fast GC-MS used for high-throughput aroma analysis of parents and hybrids. For data analysis, a chemometrical workflow was created. With a principal component analysis (PCA), the aroma similarity between the samples and a target aroma was evaluated. In order to know how the aroma profiles of the parents and hybrids are situated towards this target aroma, the Euclidean distances were calculated. These were then further used for a partial least-squares (PLS) regression analysis to determine which aroma compounds are responsible for the observed distance to the target. By using this new approach, hybrids showing aroma profiles similar to the target aroma can be identified as most suitable candidates for further breeding cycles. Besides being time-saving, the suggested workflow introduces aroma analysis as an integral part of breeding programmes. It prevents losing the coherence within the aroma profile and subsequently the loss of important information.