Aiming at the inspection of genetically modified product is mainly based on visible or near infrared spectroscopy at present, the support vector machine (SVM) modeling parameter is difficult to determine and the problem of the large amount of spectrum data calculation, a support vector machine (SVM) algorithm based on terahertz spectroscopy and adaptive particle swarm optimization (APSO) is proposed to distinguish genetically modified cotton seed. To achieve distinguish genetically modified cotton seed, the present invention is train of thought collect 165 samples of three kinds of latest genetically modified cotton seed of terahertz spectroscopy in range of 150 μm~3 mm wavelength and identification of 165 genetically modified cotton seeds based on APSOSVM. The experiment results show that the comprehensive recognition rate reached 97.3%. It can provide a precise, fast, convenient, and nondestructive detection method to distinguish genetically modified cotton seed by using terahertz spectroscopy couple to APSOSVM.