Benzoyl peroxide is a common flour additive that improves the whiteness of flour and the storage properties of flour products. However, benzoyl peroxide adversely affects the nutritional content of flour, and excess consumption causes nausea, dizziness, other poisoning, and serious liver damage. This study was focus on detection of the benzoyl peroxide added in wheat flour. A Raman scattering spectroscopy system was used to acquire spectral signal from sample data and identify benzoyl peroxide based on Raman spectral peak position. The optical devices consisted of Raman spectrometer and CCD camera, 785 nm laser module, optical fiber, prober, and a translation stage to develop a real-time, nondestructive detection system. Pure flour, pure benzoyl peroxide and different concentrations of benzoyl peroxide mixed with flour were prepared as three sets samples to measure the Raman spectrum. These samples were placed in the same type of petri dish to maintain a fixed distance between the Raman CCD and petri dish during spectral collection. The mixed samples were worked by pretreatment of homogenization and collected multiple sets of data of each mixture. The exposure time of this experiment was set at 0.5s. The Savitzky Golay (S-G) algorithm and polynomial curve-fitting method was applied to remove the fluorescence background from the Raman spectrum. The Raman spectral peaks at 619 cm-1, 848 cm-1, 890 cm-1, 1001 cm-1, 1234 cm-1, 1603cm-1, 1777cm-1 were identified as the Raman fingerprint of benzoyl peroxide. Based on the relationship between the Raman intensity of the most prominent peak at around 1001 cm-1 and log values of benzoyl peroxide concentrations, the chemical concentration prediction model was developed. This research demonstrated that Raman detection system could effectively and rapidly identify benzoyl peroxide adulteration in wheat flour. The experimental result is promising and the system with further modification can be applicable for more products in near future.