NIR news

Near infrared spectroscopy (NIR) spectroscopy is a routine measurement and analysis tool for both liquid and solid samples in a wide variety of industries and locations, both process and laboratory. Studies in gas phase measurement are not as common, but highlight some of the capabilities of the technique. This short article will review some gas phase measurements of pure materials and look at different pressure broadening effects.

Near infrared spectroscopy and hyperspectral imaging are fast-growing, rapid, powerful, and non-destructive optical technologies that can be used especially in quality and safety control of agro-food products. The Non-destructive Detecting Laboratory for Agricultural and Food Products in the College of Engineering, China Agricultural University in Beijing, China, has engaged in research on sensing and characterizing agro-food quality and safety attributes with the latest optical methods including near infrared spectroscopy and hyperspectral imaging for over five years. In this report, some of our latest research and developments through multidisciplinary international collaborations will be highlighted to demonstrate our contributions to this near infrared spectroscopy and hyperspectral imaging sensing area to improve non-destructive diagnosis and quality control of agricultural and food products.

Calibration transfer without standard samples is essential for practical applications of near infrared spectroscopy because, sometimes, it is difficult or even impossible to obtain the standard samples for measuring their spectra on the secondary instrument. In this work, a modified linear model correction method is proposed for improving the transfer accuracy and computational efficiency. The constraint of linear model correction was replaced by a robust convex equation to restrict the model similarity in the optimization. The near infrared dataset of pharmaceutical tablet measured with different instruments are used to test the performance of the method. The result shows that a modified linear model correction achieves a high efficiency of the transfer while the computational complexity can be considerably reduced. The method may provide a robust way in practical application.