The analyses concern 291 cassava genotypes harvested. in 2019 in Namulonge, Uganda. Genotypes came from NaCRRI Cassava breeding program. For this study 291 cassava roots were analysed; 3 uniformly sized non-necrotic roots per clone were sampled. Among the 281 genotypes, 282 were analysed one time and 9 genotypes were analysed 2 times, the total number of spectra is 300. Dry matter (DM) quantification was achieved in NaCRRI physico-chemical laboratory in Namulonge. Near infrared spectra were scanned in NIR laboratory of NaCRRI in Namulonge. The protocol measurement follows the SOP protocol described for fresh grated cassava: https://doi.org/10.18167/agritrop/00669. DM content, expressed as % of total weight, vary between 10,74% and 45,00% with an average value of 29,42%. On the basis of the 300 samples 2 data sets were constituted using the Kennard- Stone algorithm: one training set (n = 210) and one test set (n =90). DM content was calibrated using Modified Partial Least Squares Regression, for the spectral range: 400 nm - 2500nm, that is to say Visible and NIR regions. Calibrations were done on non-pretreated spectra and pretreated spectra using different pre-treatments. The best model was obtained with no pre-treatment applied to the spectra, the R² was 0,973 with an SECV equal to 0,894%. This model was applied to predict samples from the test set, the standard error of prediction (SEP) is equal to SEP = 0,815% and the R² for prediction is 0,953. The ratio performance to deviation RPD is equal to 4,63. The developed NIRs model for quantification of DM content of cassava root presents an accuracy good enough to enable cassava selection based on DM content. The error of the model is SEP = 0,815% which means that a predicted value could be defined with a confidence interval of +/- 1,63 % associated with 95 % of confidence. Furthermore, the database refers to 291 different genotypes representative of the variability of the DM content, thus the model is robust enough f