What should be measured in near infrared spectral imaging?

Near-infrared spectral imaging obtains the relevant information of the sample by measuring the absorption and reflection characteristics of the object in near-infrared band.

1 and near infrared spectral imaging are widely used in agriculture. By measuring and analyzing the near infrared spectrum of crops or fruits and vegetables, we can evaluate the growth, nutrition and diseases and insect pests of crops and provide accurate agricultural management guidance for farmers. In addition, near infrared spectral imaging can also be used for quality detection and variety identification of agricultural products to ensure the safety and quality of agricultural products.

2. In the food industry, near infrared spectral imaging can be used to analyze the composition and quality of food. By scanning the near infrared spectrum of food samples, we can quickly and accurately detect the water content, fat content, protein content and other important indicators of food, and realize the rapid quality detection and classification of food. This is of great significance to quality control and food safety management in food production.

3. Near infrared spectral imaging is also widely used in medical field. Near infrared light can penetrate human tissues, so it can be used for non-invasive detection of tissues. For example, near infrared spectral imaging can be used for early diagnosis and monitoring of breast cancer, and whether the tissue is abnormal can be judged by measuring the spectral reflection characteristics of breast tissue. Similarly, near infrared spectral imaging can also be used in medical applications, such as the diagnosis of skin diseases and the study of brain function.

4. In the field of materials science, near infrared spectroscopy imaging can be used for the analysis and detection of material surfaces. For example, the quality and uniformity of coating materials can be evaluated by near infrared spectral imaging, and parameters such as water content and temperature distribution of materials can be detected. This is of great significance to quality control and fault diagnosis in industrial production.