Guayule (Parthenium argentatum), a plant native of semi-arid regions of northern Mexico and south-ern Texas, United States, is an under-used source of hypoallergenic latex, a solution to the serious latex allergy IgE problem worldwide. This study aimed to develop near infrared spectroscopy (NIRS) calibra-tions to assess resin and rubber contents in guayule plants. For achieving this goal a reference method (ASE; accelerated solvent extraction) was selected and optimized among three alternatives also including Soxhlet and Polytron. First resin (lipids, terpenes) was extracted with acetone from ground biomass at 40 ?C, and then rubber was extracted with hexane from left solid at 120 ?C. A set of 215 samples of guayule biomass (stems and branches) was collected from plants in two experimental fields located in France and in Spain and was analyzed for moisture, rubber and resin contents using the two solvent selected ASE methods. Near infrared spectra were recorded for all samples. Two thirds of the samples were randomly selected for calibration, the remaining being used for validation. For each constituent, calibration equa-tions were developed using modified partial least squares regression. The equation performances were evaluated using the performance to deviation ratio (RPDp) and R2pparameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture content (RPDp = 6.91; R2p = 0.98) calibration enabled accurate determination of these traits. NIR models for hexane extract (rubber content) (RPDp = 4.59; R2p = 0.96) and acetone extract (resin content) (RPDp = 4.87; R2p = 0.96) were highly efficient and enabled accurate characterization of guayule biomass. On the other hand, this analysis showed that both laboratory tools, coupled with multivariate analytical techniques, could be used to differentiate the samples and accurately predict the chemical composition of this disparate set of agricultural biomass samples. This