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Background: Chlorophyll is a major component of chloroplasts and a better understanding of the genetic basis of chlorophyll in soybean [Glycine max (L.) Merr.] might contribute to improving photosynthetic capacity and yield in regions with adverse environmental conditions. A collection of 332 diverse soybean genotypes were grown in 2 years (2009 and 2010) and chlorophyll a (eChl_A), chlorophyll b (eChl_B), and total chlorophyll (eChl_T) content as well as chlorophyll a/b ratio (eChl_R) in leaf tissues were determined by extraction and spectrometric determination. Total chlorophyll was also derived from canopy spectral reflectance measurements using a model of wavelet transformed spectra (tChl_T) as well as with a spectral reflectance index (iChl_T). Results: A genome-wide associating mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify loci associated with the extract based eChl_A, eChl_B, eChl_R and eChl_T measurements and the two canopy spectral reflectance-based methods (tChl_T and iChl_T). A total of 23 (14 loci), 15 (7 loci) and 14 SNPs (10 loci) showed significant association with eChl_A, eChl_B and eChl_R respectively. A total of 52 unique SNPs were significantly associated with total chlorophyll content based on at least one of the three approaches (eChl_T, tChl_T and iChl_T) and likely tagged 27 putative loci for total chlorophyll content, four of which were indicated by all three approaches. Conclusions: Results presented here show that markers for chlorophyll traits can be identified in soybean using both extract-based and canopy spectral reflectance-based phenotypes, and confirm that high-throughput phenotyping-amenable canopy spectral reflectance measurements can be used for association mapping. [ABSTRACT FROM AUTHOR]