Abstract Coral reef ecosystems face increasing threats from microbial diseases, especially those induced by bacterial infections. Conventional diagnostic techniques often require invasive sampling, extended processing time and are limited in their spatial applicability. Spectral reflectance analysis offers a non-invasive means for detecting subtle physiological alterations associated with coral disease; however, its application in characterizing microbiological changes remains largely unexplored. This research aimed to differentiate healthy from diseased coral colonies by analyzing the spectral fingerprints of the disease and their associated bacterial communities, using hyperspectral data, microbial profiling, and multivariate statistical analysis. The bacterial species identified in healthy coral samples included Bacillus subtilis , Cytobacillus firmus , Bacillus amyloliquefaciens , and Bacillus sporothermodurans . In contrast, the bacteria associated with diseased coral samples were Vibrio pelagius and Vibrio fortis . Healthy corals demonstrate consistently lower reflectance across all bands in comparison to diseased corals. The reflectance of diseased Favia lacuna showed a notable increase when compared to healthy specimens, especially at wavelengths of 594 nm, 649 nm, and 702 nm. In contrast, Acropora humilis exhibited heightened peaks at wavelengths of 580 nm, 693 nm, and 702 nm. The analysis of the second derivative revealed that coral colonies affected by disease exhibited distinct negative peaks at wavelengths of 450–460 nm, 580–590 nm, and 700–800 nm. The identified peaks are likely associated with tissue thinning, skeletal exposure, or microbial biofilm accumulation rather than pigment absorption, given that this region is dominated by scattering effects. In contrast, healthy colonies exhibited stable characteristics at approximately 675 nm, indicating the presence of intact symbiotic chlorophyll and preserved physiological structure. The present study demonstrates that hyperspectral reflectance profiling of bacterially infected corals shows promising potential as a non-invasive approach for differentiating healthy and diseased coral microbiomes. The integration of spectral indicators with microbial community data provides preliminary insights into coral health assessment and may contribute to the development of improved strategies for disease detection and understanding coral–microbe interactions under environmental stress.
Khalifa et al. (Mon,) studied this question.