The quality of fruits and vegetables is an important indicator of their quality control, and it is also a key link in the quality and safety control of fruits and vegetables. Traditional testing methods are cumbersome, time-consuming, and damaging to samples. In order to quickly, non-destructively, qualitatively and quantitatively detect the quality of fruits and vegetables, hyperspectral imaging technology can be used. This paper introduces the application of hyperspectral imager in the nondestructive testing of the internal and external quality of fruits and vegetables.
Fruits and vegetables are indispensable foods in life, they can provide vitamins, fiber, inorganic salts and various trace elements that humans need. The quality and safety of fruits and vegetables have always been a hot issue of social concern. The external quality of fruits and vegetables is mainly evaluated according to their color, texture, size, shape and surface defects, and the external quality is their most intuitive quality characteristics, which directly affect their market** and consumers' desire to buy; Internal quality is mainly determined by their sugar content, acidity, hardness, soluble solids content, starch content, moisture and maturity and other nutrients, and internal quality is the embodiment of their value; Quality and safety are mainly detected and evaluated through foreign contamination such as animal feces, various diseases, quality deterioration, bacterial infections and pesticide residues, which are related to the dietary safety and health of consumers and are the most important quality characteristics of fruits and vegetables.
At present, the quality and safety of fruits and vegetables are mainly tested by traditional chemical methods, which are a time-consuming and laborious destructive testing technology. With the rapid development of imaging and spectroscopy technology, hyperspectral imaging technology has been widely used in the rapid non-destructive testing of the quality and safety of agricultural products, and a large number of successful cases have also proved that hyperspectral imaging technology is a scientific and effective tool for the quality and safety detection of food and agricultural products. Hyperspectral imaging technology combines the advantages of traditional imaging technology and spectral technology, and the obtained hyperspectral images have the characteristics of "atlas integration", that is, they contain image information and spectral information at the same time. Image information can be used to detect the external quality of fruits and vegetables, while spectral information can be used to detect their internal quality and safety.
As a non-invasive, non-contact, and non-traditional technology, hyperspectral imaging technology provides spatial information and spectral information of research objects. The basic characteristics of this technology are high spectral resolution; The spectral response range is wide, and the bands are many and narrow; "Spectrum and image integration" and large amount of data and rich information; There are many data description models and flexible analysis. These characteristics determine the unique advantages of hyperspectral image technology in the internal and external quality inspection of food. Since the image data can reflect the external characteristics of the product, and the spectral data can analyze the internal physical structure and chemical composition of the object, it can be said that hyperspectral imaging technology is the perfect combination of image technology and spectral technology. The data generated by hyperspectral imaging technology can be described visually as "three-dimensional data blocks", which are more reliable than traditional machine vision or spectroscopic technologies. Its application in fruit and vegetable quality testing is as follows:
1.Non-destructive testing of fruits and vegetables.
The traditional fruit and vegetable quality testing method has a certain damage to fruits and vegetables, and it takes more time, manpower and material resources, which can not meet the requirements of modern society for fruit and vegetable quality testing. Hardness and soluble solids content are important internal indicators to determine the ripeness of fruits and vegetables and the harvest season. In addition, important indicators of fruit and vegetable quality include taste, appearance, aroma and chemical composition. However, the determination of the above indicators based on hyperspectral imaging technology only requires a small number of samples, and can realize the rapid and non-destructive determination of relevant quality indicators. The inspector only needs to extract a "three-dimensional" image block from the model sample, which includes two-dimensional image pixel information and third-dimensional wavelength information. Then, a multivariate analysis model was established to correlate the extracted spectral data with the measured values of the sample attributes, and a quantitative relationship model was established, so that the quality of fruit and vegetable samples could be detected and graded, and the quality of fruits and vegetables could be effectively evaluated.
2.Detect contaminants on the surface of fruits and vegetables.
According to research, when inspectors irradiate fruits and vegetables with different wavelengths of light, fruits and vegetables will scatter, absorb, reflect and transmit light. Studies have shown that when some specific wavelengths of light are irradiated into fruits and vegetables, the spectral data collected through transmission and scattering will carry a wealth of information about the internal composition of the food. In recent years, hyperspectral technology has been applied to detect the damage of fruits and vegetables, and the application of hyperspectral imaging methods can not only achieve non-destructive detection, but also quickly and accurately obtain complete image information and spectral information of samples. Inspectors use image and spectroscopic analysis methods to detect the chemical composition, physical structure and surface characteristics of fruits and vegetables. In the spectral range of 400 to 1,000 nanometers of visible light and near-infrared, the inspector can collect "three-dimensional" image blocks including two-dimensional image pixel information and third-dimensional wavelength information by integrating information such as time, scanning speed and spectral correction. Due to the characteristics of hyperspectral data with multiple spectral channels, high spectral resolution and continuous spectrum, two different images at very close but different wavelengths can be resolved, and the continuous spectral curves of any pixel and different spectral curves of different substances can be obtained. This technology uses the spectral value of the normal area and the spectral value of the damaged area at some specific wavelengths, which will have a relatively large difference, and can achieve non-destructive detection of the surface of fruits and vegetables.
3.Detection of pesticide residues on the surface of fruits and vegetables.
In practice, pesticide residue detection technology is relatively abundant, and the traditional high-precision detection process has relatively high requirements for the operability of the inspector, and the detection time is long, which can only be used for the accurate analysis and detection of pesticide residues in the laboratory; Chemical detection methods are generally destructive tests, which have the disadvantages of consuming organic reagents, cumbersome sample preparation, and high detection costs. Hyperspectral imaging detection can achieve the purpose of efficient, real-time and rapid nondestructive testing. The inspector obtains the hyperspectral image of the food through the hyperspectrometer, applies the principal component analysis method to analyze the obtained hyperspectral image, and finds out the image at the characteristic wavelength. Inspectors use image processing technology to analyze these characteristic images, and can detect the pesticide residue content on the surface of fruits and vegetables.
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