Environmental Microorganisms (EMs) are very diverse and live in every part of the biosphere (rivers, forests, mountains, etc.), playing critical roles in earth's biogeochemical cycles as they are responsible for the decomposition of waste. Currently, a lot of manual efforts through morphological analysis using microscopes have been put on looking for EMs; however, these methods are expensive and time-consuming. To enhance the effectiveness of EM information search, we propose a Content-based Image Retrieval approach by using multiple colour channels fusion and Particle Swarm Optimisation (PSO). First, a microorganism image is decomposed into different colour channels for a more discriminative and eventual representation. Then we extract SIFT features and compute the similarity between a query image and EM database images in terms of each colour channel. Finally, PSO is applied to launch weights fusion and obtain the final retrieval result, because it provides a valid space exploration function. Experiments on our EM dataset show the advantage of the proposed multiple colour channels fusion method over each single channel result.