Qualitative and quantitative near infrared spectroscopic (NIRS) methods require the application of multivariate calibration algorithms to model NIR spectral response to chemical or physical properties of a calibration sample set. The identification of unique wavelength regions where changes in the response of the near infrared spectrometer are proportional to changes in the concentration of chemical components, or in the physical characteristics of samples under analysis is referred to as practical interpretive spectroscopy. Recent refinements of the NIR measurement technique include the emergence of chemometrics as a bona fide scientific discipline, and the diminishing distinction between near infrared, and infrared as measurement techniques. Rather the techniques are complementary, with each spectral region providing unique advantages for the analyst. This paper describes the use of classic infrared interpretive tools combined with chemometric tools for use in near infrared interpretive spectro...

Interpretive Spectroscopy for Near Infrared

Over the last two decades, near-infrared spectroscopy (NIRS) has established itself as a non-destructive analytical technique in a variety of disciplines. However, recent technological advancements in hardware design and data mining techniques have unleashed the potential of NIRS to become a tool of choice for routine analyses of agricultural products. The current paper synthesizes the status of NIRS in the agri-food industry in terms of hardware and software development as well as the direction in which the NIRS research is headed. An extensive review of literature reveals that the emphasis on hardware development is focused on developing compact, robust, and portable spectrometers and hyperspectral imaging (HSI) systems. The software development on the other hand is geared towards developing better preprocessing, analyses, and modeling techniques using chemometrics, support vector machines, and artificial neural networks. The four main agri-food sectors identified to be the beneficiaries of this research revolution are grain quality monitoring; post-harvest handling of fruits and vegetables; identification of contaminants in animal produce and feed; and food safety and authenticity. Apart from discussing the aforementioned topics, the paper also provides food scientists some working knowledge on parameters crucial to the performance of spectral and imaging systems. It is expected that further development of NIRS will help agricultural and food scientists to enhance the quality and safety of our food.

Near-infrared spectroscopy and imaging in food quality and safety

Short-wavelength near-infrared (SW-near-IR) spectroscopy (700-1100 nm) is used for the determination of ethanol during the time course of a fermentation Measurements are performed noninvasively by means of a photodiode array spectrometer equipped with a fiber-optic probe placed on the outside of the glass-wall fermentation vessel Pure ethanol/water and ethanol/yeast/water mixtures are studied to establish the spectral features that characterize ethanol and to show that determination of ethanol is independent of the yeast concentration Analysis of the second-derivative data is accomplished with multilinear regression (MLR) The standard error of prediction (SEP) of ethanol in ethanol/water solutions is approximately 02% over a range of 0-15%; the SEP of ethanol in ethanol/yeast/water solutions is 027% (w/w) Results from the mixture experiments are then applied to actual yeast fermentations of glucose to ethanol By use of a gas chromatographic method for validation, a good correlation is found between the intensity of backscattered light at 905 nm and the actual ethanol Additional experiments show that a calibration model created for one fermentation can be used to predict ethanol production during the time course of others with a prediction error of 04%

Noninvasive method for monitoring ethanol in fermentation processes using fiber-optic near-infrared spectroscopy

Short-wave near-infrared spectroscopy analysis of major compounds in milk powder and wavelength assignment.

Nondestructive assessment of freshness in packaged sliced chicken breasts using SW-NIR spectroscopy

We describe a silicon photodiode-array (PDA)-based near-infrared spectrophotometer for making molecular absorption/diffuse reflectance measurements in the 600-1100 nm wavelength range. Absorptions in this spectral region arise from both low-lying electronic states and vibrational overtones of CH, NH, and OH functional groups and combination bands. One disadvantage of silicon-based array detectors is their decreasing quantum efficiency at wavelengths longer than 950 nm. For transmission measurements, this can be compensated for by the technique of spectral plane masking, which markedly improves the consistency and overall level of baseline noise as well as the dynamic range. The instrument's performance is evaluated in the areas of spectral resolution, baseline noise, stray light, and dynamic range, and a comparison is made with a state-of-the-art mechanically scanned instrument. In the study, the PDA spectrometer attained a signal-to-noise ratio two times better than that of the commercial instrument with a time efficiency advantage of twelve, while achieving a spectral resolution three times greater. Finally, the application of analyzing caustic brine solutions by rapid-scanning NIR spectroscopy is illustrated.

David M. Mayes

Papers

A Photodiode-Array-Based Near-Infrared Spectrophotometer for the 600–1100 nm Wavelength Region: