To improve the accuracy and reproducibility of the previous near infrared reflectance spectroscopy (NIRS) model for glycogen in the oyster species Crassostrea virginica, a new model using freeze-dried samples was developed. The NIRS glycogen calibration model was developed using 380 individual oyster samples collected between 2014 and 2016 from several locations in the Chesapeake Bay. Homogenized freeze-dried samples were scanned in the near infrared region between 1,000 and 2,500 nm. In parallel, glycogen concentration (GC), measured as percent dry weight, was determined using laboratory-based methods. The two sets of data allowed us to build a NIRS model based on freeze-dried oyster meats, and the model gave a strong prediction of GC [coefficient of determination for validation (R²_val) = 0.96 and residual predictive deviation (RPD) = 5.2]. The second part of the study applied the model to determine GC among 39 diploid and 40 triploid C. virginica and determined the strength of the relationship between the GC of tissues excised for histological sampling to the remaining tissue (corpus) to verify assumptions made throughout the literature. There was an estimated R² = 0.99 between the GC in the corpus and the tissues of whole oyster meat. Among the samples, two factors, ploidy and size (shell height), had a significant effect on GC.