Near‐Infrared Spectroscopy of Biomaterials

Abstract

The sections in this article are Introduction Historical Perspective Biological Samples Qualitative NIR Spectroscopy Fundamental Components Water, Oil, Protein and Starch Water Oil Protein Starch Plant Materials Grains Wheat and Wheat Components Other Grains Tea Coffee Tobacco Food and Drink Food Cereals Meats, Poultry and Fish Fresh Fruit Additives: Molasses, Honey, Corn Syrup and Lemon Extract Sweets: Sucrose, Saccharin, Extra and Chocolate Drink Milk and Water Ethanol–Water Mixtures Spirits Fiber Cotton, Flax and Wool Human Samples Skin Hair Blood Urine Future Trends in NIR Spectroscopy Hyphenated Systems Imaging Spectrometry and Remote Sensing Hand‐Held Spectrometry Dedication

A Digital Approach to Model Quality and Sensory Traits of Beers Fermented under Sonication Based on Chemical Fingerprinting

“…The NIR curve developed with raw absorbance values (Figure 3a) is consistent with that reported by McClure and Stanfield for beers [25]. According to Wilson et al [26], the peak at 1927 nm corresponds to an overtone of protein-bound water, while other authors have identified water at 1932 [25] and 1940 nm [27], which are also within the range of the major peak observed in the curve for the three beer treatments. Ethanol, which is one of the main components in beer, has been identified at 2270 nm [22,25], which was observed in both the raw and first derivative curves.…”

Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms

“…Similarly, the ethanol curve (green line) shows the peak values for the absorbance around the wavelengths corresponding to alcohol overtones (2090, 2270 and 2304 nm). 21,23 As shown in Fig. 3 the measurements made for five different samples, representing the three fermentation types and using the whole spectra for both the filter paper (x axis) and the silica sand (y axis) presented similar errors, with consistent difference values (50-52%) and high correlation between the two methods.…”

“…As further shown in this figure, after subtracting the filter values, the peak of water overtones (1940 nm) was enhanced and the absorbance in the wavelengths corresponding to cellulose and starch overtones were minimised (blue line). Similarly, the ethanol curve (green line) shows the peak values for the absorbance around the wavelengths corresponding to alcohol overtones (2090, 2270 and 2304 nm) …”

Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening

“…Among the four other spectral features important for classification, the 1935 nm band is most likely influenced by the combination band of water at 1940 nm and the hydroxyl stretch/HOH deformation combination of starch and cellulose (Shenk et al, 2007). The 2090 nm band can be assigned as the ''carbohydrate band'', always present in plant tissues, and resulting from both starch and cellulose (McClure and Stanfield, 2006;Shenk et al, 2007). As in Tigabu et al (2004), our results show that the spectral differences are mainly due to the storage compounds, such as proteins, carbohydrates and fatty acids.…”