The invention provides a detection method for producing areas of Xihulongjing tea based on genetic algorithm optimization. The method is characterized in that an electronic nose is utilized to acquire fingerprints of the smell of Xihulongjing tea from different producing areas, sensors having special contribution to modeling of the producing areas are screened out based on analysis of average fingerprints and a principal component score chart through three key techniques of genetic algorithm, i.e., a roulette selection method, a single-point crossover method and a simple mutation method, with an integral recognition rate as a fitness function, optimization is carried out so as to reduce the amount of sensors needed in modeling, and fingerprint response values of the sensors are subjected to matrix analysis through an F value obtained through variance analysis and principal component load.