In this study, a 400-1000nm hyperspectral camera was applied, and FS13, a product of Hangzhou CHNSpec Technology Co., Ltd, could be used for related research. The spectral range is 400-1000nm, the wavelength resolution is better than 2.5nm, and up to 1200 spectral channels can be reached. The acquisition speed can reach 128FPS in the full spectrum, and the maximum after band selection is 3300Hz (support multi-region band selection).
Medicinal gelatin hollow hard capsule is a kind of special medicinal excipients, in which chromium content is an important test index stipulated by the national health standard. Capsules with excessive chromium content are commonly known as "toxic capsules" and are very toxic to the human body. At present, chromium content is determined by traditional chemical analysis method. The traditional chromium detection method is time-consuming, the equipment is expensive, the use of a large amount of nitric acid digestion is easy to cause secondary pollution, and the instrument operation needs professional personnel to complete. Therefore, the development of a convenient and rapid method for the rapid detection of chromium content in medicinal capsules has important application significance and market prospect.
Based on the feasibility of hyperspectral detection of heavy metals, this paper uses conventional atomic absorption spectrometry to compare the collected results of normal MEHGC and MEHGC with excessive chromium content, then collects two kinds of MehGC data with hyperspectral analysis, and uses principal component analysis (PCA) and partial least square method to analyze the hyperspectral data, and finally establishes the relevant model. To realize the qualitative detection of "poison capsules".
Since hyperspectral data is composed of multiple band images, each image can be regarded as a feature. If the hyperspectral data is dimensionally reduced, the original data will be changed to a new coordinate system to maximize the difference between the image data, and the result will be very different from the original image. This technique is very effective for enhancing information content, isolating noise and reducing data dimensions. The first 4 principal components obtained after PCA dimensionality reduction of hyperspectral images are shown in Figure 1.
The advantage of hyperspectral images is that there is not only image information, but also spectral information. To obtain the spectral information, the region of interest is selected for each sample, and each region of interest has its spectral response curve. Due to the difference in color between the capsule cap and the capsule body, in order to eliminate the influence of color on the result, two regions of interest were selected for each capsule (one on the capsule cap and one on the capsule body). The regions of interest could be randomly selected on the hyperspectral image of the capsule, and the number of pixels in each region ranged from 2 to 6. The final spectral data for the region of interest is calculated as the average of all pixels in the region. The spectral curves of 4 different regions (capsules and caps of normal capsules and "toxic capsules" respectively) are shown in Figure 2.
In the hyperspectral data of 450~900 nm, the spectral data of normal capsule and "toxic capsule" were obtained by selecting the region of interest, which was normalized first, and then the data dimension reduction and discriminant analysis were conducted by PLS-DA. When four PLS operators were selected as input features, the recognition rate of normal capsule and "toxic capsule" reached 100%. Specificity and sensitivity are also 100%; It can be seen that normal capsules and "toxic capsules" can be distinguished by PLS-DA discrimination method. Using hyperspectral image technology to detect "poison capsules" can greatly reduce the complexity of traditional methods.
In addition, to improve confidence, samples must be examined in a wider spectrum, such as fluorescence or ultraviolet. While qualitatively conducting the "poison capsule", it is also necessary to conduct quantitative research on it, which can consider making gelatin templates with different chromium content, find out the correlation model between the chromium content of the template and the spectral data, and use this model to predict the heavy metal chromium content of the unknown "poison capsule". In view of the subsequent impact of the "poison capsule" incident, samples are difficult to find, but in order to improve the effectiveness of the test, it is necessary to use a variety of capsule samples with chromium content.