茶叶夹杂昆虫异物THz光谱检测研究

doi:10.3964/j.issn.1000-0593(2021)09-2723-06

Abstract
References
Related Citation (15)

Download: PDF (2884 KB)
Export: BibTeX | EndNote (RIS)

Abstract Chinese black tea is widely respected for its long-term cultural heritage and multiple health benefits. Black tea uses fresh leaves of tea trees as raw materials and is finished by finishing, kneading, drying, screening, and drying. These traditional techniques create a mellow, varied, and rich taste of the famous tea. However, the complex processing technology also increases the risk of physical pollution, and non-tea and foreign tea matter will inevitably be mixed during the processing. Physical contamination is a random event, accounting for 19.8% of food safety complaints. Physical pollution can only be reduced, and it is difficult to eliminate it. It is the key to future disputes between manufacturers and consumers and import and export trade. X-rays use the density difference between the food matrix and foreign objects to detect foreign metal objects effectively and extend to high-density plastics. Organic foreign bodies such as insects are still food foreign bodies that X-rays cannot detect. Insect foreign bodies are mixed with a high frequency, which causes sensory discomfort and easily introduces pathogenic bacteria. There is an urgent need to develop corresponding non-destructive testing methods. As an emerging detection technology, Terahertz time-domain spectroscopy (THz-TDS) technology has good application potential in non-destructive testing of agricultural products, food and medicines. THz has good low-energy transmission and fingerprint spectrum characteristics and has no ionizing radiation damage. It can obtain the spectrum and image information of hidden foreign objects through the food matrix. It is a better choice for non-destructive testing of agricultural products and food. In order to realize the high-efficiency detection of low-density organic foreign matter in tea, this paper explores a new method of the non-destructive detection of black tea-infested insect foreign matter based on THz spectroscopy. In the range of 0.2~3.0 THz, the THz spectra of black tea matrix, insect foreign matter, and black tea mixed with foreign insect matter were collected. The THz absorption coefficient and dielectric loss response characteristics of the tea matrix and insect foreign bodies are analyzed. From the spectrogram, it can be seen that there are significant differences between the THz absorption coefficient and dielectric loss of the tea matrix and the foreign insect bodies, mainly caused by the protein and fat of the foreign insect bodies. The ingredients are caused, laying the foundation for the THz spectrum detection of black tea mixed with insects and foreign bodies. However, the absorption coefficients of tea and insects have no obvious characteristic peaks, and there is more obvious noise in the high-frequency band of 2.0~3.0 THz. The principal component analysis method is used to reduce the dimensionality of the absorption coefficient and the dielectric loss. The score map shows that there is a clear difference between the black tea matrix and the black tea with insect foreign bodies, and the clustering effect of the absorption coefficient is better than that of the dielectric loss factor. The THz absorption coefficient and dielectric loss in the range of 0.5~1.0 THz were selected as input vectors, and support vector machine (SVM) and linear discriminant analysis (LDA) discriminant models were established. The experimental results show that the LDA discrimination model based on the THz absorption coefficient has the highest accuracy, and the correct recognition rate of new samples is 73.68%. It shows that applying THz time-domain spectroscopy for non-destructive detection of black tea inclusions of foreign insect bodies is feasible. At the same time, THz spectrum combined with pattern recognition algorithm provides a new method for non-destructive detection of tea inclusions of foreign insect bodies and can also provide a reference for other agricultural products and food detection.

Key words：Terahertz; Spectra; Tea; Foreign body of insects; Discriminant analysis

Received: 2020-07-18 Accepted: 2020-11-09

ZTFLH:

O439

Cite this article:

URL:

https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2021)09-2723-06 OR https://www.gpxygpfx.com/EN/Y2021/V41/I09/2723