An Intelligent Strategy for Colony De-Replication Using Raman Spectroscopy and Hybrid Clustering

Efficient de-redundant colony picking is essential to accelerating strain screening in fermentation microbiology. Conventional random picking is inefficient, exhibits high redundancy, and often misses low-abundance but valuable strains. To address this, we present a high-efficiency de-redundant selection strategy based on colony Raman spectroscopy and a hybrid clustering algorithm. We directly acquire colony Raman spectra and combine the complementary strengths of k-means and hierarchical clustering (HCA) to achieve both balanced global partitioning and sensitivity to low-abundance taxa. Systematic application on pure colonies and complex plate settings shows that, by picking only 12–26% of colonies, the method attains 80–100% species coverage. Relative to manual random picking and image-based feature selection, picking efficiency increased by 116.8% and 44.5%, respectively, substantially shortening the screening cycle and reducing workload. Overall, Raman-guided hybrid clustering substantially reduces redundant picking and improves detection of low-abundance strains. It provides practical support for efficient strain discovery, library construction, and process optimization.