## 1 Introduction  
_Astragalus_ is a large genus of plants in the botanical family Fabaceae, several species of which have been historically used in traditional Chinese medicine. As used here, \"_Astragalus_\" mainly refers to the species _Astragalus_ _mongholicus_ and _A. membranaeus_. _Astragalus_ is one of the most popular medicinal herbs in China, and it has a long history of use as a medicinal material. _Astragalus_ is one of 40 commonly used bulk medicinal materials, and the demand for it is increasing daily [1, 2]. However, the quality of traditional Chinese medicinal plant seeds is far behind that of crop seeds, and there are many problems, such as mixed provenance, low purity, inconsistent maturity, low germination rate, and slow and irregular emergence. Seeds have become the weakest link in the production of traditional Chinese medicinal plants and are the \"bottleneck\" that restricts the standardized production and development of traditional Chinese medicine. Seed maturity is closely related to seed vigor [3, 4]. The comprehensive features such as bud rate, bud potential, soil arching ability, seedling rate, and seedling uniformity of seeds with poor maturity decrease, which seriously affects the quality of seeds and the entire production system. Therefore, it is necessary to improve seed maturity. Chlorophylll content in the seeds of many species can be used as an indicator of seed maturity and is a major contributor to seed quality [5, 6, 7, 8]. Using chlorophylll fluorescence (CF) to determine seed maturity is a relatively new technology. CF seed detectors are used to detect the chlorophylll fluorescence (blue) gen erated by pulsed light. Fluorescence emissions at wavelengths of 600 nm and above from all fluorescent substances will be detected. The pulsed light emitted by the detector can separate the fluorescence from the surrounding light. Therefore, the detector can calculate the rough chlorophyll concentration by measuring chlorophyll fluorescence. [PERSON] et al. [9] classified the different stages of maturity in four varieties of pepper seeds based on CF. After classification, the germination percentage and vigor of the seeds with low CF were shown to be the highest. [PERSON] et al. [10, 11] used the magnitude of the CF to judge and grade seed maturity in cabbage. These authors found that the smaller the signal value, the higher the seed germination rate. Although CF is widely used and is highly portable, it still has the problem of high cost. Digital image analysis technology is a low-cost and non-destructive technology. Images can be obtained by classical reflection technologies, such as optical and micrography methods, or by more modern technologies, such as thermal imaging, fluorescence and magnetic resonance [12, 13, 14, 15, 16]. This technology can obtain seed image information, extract the shape, color, and texture information of seeds, and is widely used in seed color feature determination [17, 18], the improvement of seed vigor and quality monitoring [19, 20, 21, 22], crop seed quality classification [23, 24, 25], variety identification [26, 27], purity determination [28], quantifying intraspecific genetic diversity [29] and evaluating crop and seed maturity [30, 31, 32]. Digital image analysis technology is a relatively mature technology, and its application to the prediction of chlorophyll content in _Astragalus_ seeds is highly feasible with excellent development prospects. Therefore, it is important to develop a fast, non-destructive, low-cost and efficient method to measure the chlorophyll content of _Astragalus_ seeds. In this study, we determined the chlorophyll content of _Astragalus_ seeds and the characteristic features of the seeds were extracted. The models were established by using the characteristic features as the input factor of the model, the chlorophyll content as the output parameter, and the multiple linear regression (MLR) and multi-layer perceptron (MLP) methods to establish the model.