For the development of a self-propelled crop spraying machine, a hybrid experimental and analytical Source-Path-Contribution (SPC) approach is utilized by a leading agricultural equipment manufacturer. The objective is to predict noise and sound quality in the cab before prototypes are assembled, so that dB(A) and SQ targets can be assessed early on and better specifications sent to suppliers to achieve these vehicle-level targets. The experimental SPC task is conducted on the current crop sprayer model, which has the same cab but different engine, transmission and hydraulics than the new model. A hybrid FE-SEA model of the current cab is developed and run at load cases derived from test data. The SEA approach is needed to evaluate the effect of cab acoustic treatments, which are not accounted for in the SPC experimental model. Contributions to in-cab noise for the current sprayer are estimated from both experimental and analytical SPC. Acoustic and structural loads to the cab in the new model are estimated from measurements on hardware components and from supplier provided data. The hybrid FE-SEA model is then updated with the new loads and re-run to predict total in-cab noise and contributions from each source in the new model, which is then used to identify the best countermeasures for noise reduction and SQ improvement.