Abstract
The purpose of this paper is to use chemometric method to analyze the seed production. Based on the hyperspectral image recognition, the carrier of agricultural technology and agricultural production materials is studied. With the wide application of hybrid technology and the influence of many factors in the process of seed production, the phenomenon resulting in seed mixing often occurs, which is a serious threat to the interests of farmers. Therefore, it is of great significance to improve the accuracy and reliability of seed purity testing in order to ensure seed quality and high yield. By analyzing the chemometric methods, a reasonable measurement method is designed and selected to analyze the data, so as to achieve the most effective information in the spectral data. The experiment results show that hyperspectral image technology can reflect the spectral features and image features of the seeds. In addition, a fast and accurate classification model is developed to solve the problems of seed purity detection based on the combination of hyperspectral image technology and chemometric methods. Based on the above findings, it can be concluded that the research has a great significance for the application of hyperspectral imaging technology in the field of non-destructive testing of agricultural products.
