Seed respiration is a key metabolic process linked to physiological status. Q2 respiration analysis enables detailed profiling of individual seeds, and combined with multispectral imaging, allows to explore seed-to-seed relationships between respiration and spectral or morphological traits. Thus,the study aims to investigate the relationship between the respiration profiles of individual soybean seeds and their morphological and spectral characteristics, using single-seed respiration analysis and multispectral imaging. Multispectral images were captured from 1,808 seeds using the VideometerLab system, from which 75 features were extracted. The seeds were placed in vials with 0.4% (w/v) agar to induce germination and sealed with caps containing a fluorescent polymer dot. The Q2 analyzer, tracked the oxygen consumption of each seed during germination. Both the VideometerLab and Q2 analyzer data were categorized through hierarchical clustering, and a subpopulation of seeds was selected from three categories of respiration profiles due to computational limitations. The association between respiration patterns and biometric features was analyzed using contingency tables and entropy analysis. The results revealed significant differences in respiration patterns, particularly in autofluorescence excitation-emission at 365/600, 430/700, 450/700 and 470/700 nm, as well as in reflectance at 365, 690 and 405 nm. Notably, 75% of seeds with similar respiration profiles were grouped based on similarities in their biometric characteristics, suggesting a relationship between respiration patterns and biometric features. Additionally, patterns of certain biometric traits indicated that different combinations can lead to similar respiration profiles, highlighting the complexity of evaluating this association.