At present, although the near-infrared (NIR) spectroscopy analysis technology has been widely used in many fields, it is mainly used as laboratory instruments, and the spectrometer used in the laboratory has the problems of large volume, high power consumption and high price. The main units that can purchase and use the NIR spectrometer are universities, scientific research institutes, large and medium-sized enterprises, etc. The price of a spectrometer based on the Fourier or grating principle is usually as high as several hundred thousand Yuan, which is beyond the affordability of small and medium-sized enterprises and ordinary people. Therefore, the application of NIR spectrometer is far away from ordinary people’s daily life. The high price and large volume of near-infrared spectrometers restrict the large-scale application of near-infrared spectroscopy analysis technology. The reason is that the near-infrared spectrometer itself is expensive and the volume has not yet been portable and miniaturized. Reducing the cost of the NIR spectrometer and miniaturizing the spectrometer is an important direction to promote NIR spectroscopy technology. The efforts of miniaturization of NIR spectrometer include CT orthogonal grating technology and micro electro mechanical system technology. However, the volume reduction of the spectrometer by these two technical solutions is limited, and there are still some problems, such as high price, internal moving parts and real hard miniaturization. For a specific qualitative analysis task, a small number of characteristic wavelength points are selected from full spectra and used to build models which can recognize testes samples. The method mentioned above can reduce the cost of instrument manufacturing and difficulty of spectrometer miniaturization, and it is also conducive to the large-scale promotion and application of NIR analysis technology. Near infrared spectra of Haploid and diploid maize seeds are collected by diffuse transmission method in several days. The collected data are divided into five data sets in chronological order. For the first data set, 10 characteristic wavelength points are extracted by genetic algorithm, and then 10 characteristic wavelength points are extracted for the remaining four data sets In order to test the validity of the method, the haploid and diploid identification was carried out. The experimental results show that using 10 characteristic wavelength points can obtain the identification effect, which is consistent with the full spectrum, indicating that using a small number of characteristic wavelength points can also effectively identify haploids, which can provide a reference for the development of low-cost portable NIR spectrometer for a specific task in other fields.