Near infrared spectroscopy: A mature analytical technique with new perspectives – A review

2018 ◽  
Vol 1026 ◽  
pp. 8-36 ◽  
Author(s):  
Celio Pasquini
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Analytical Technique

Using near infrared spectroscopy to determine moisture and starch content of corn processing products

2017 ◽  
Vol 25 (5) ◽  
pp. 348-359 ◽  
Author(s):  
Ye Chen ◽  
Lauren Delaney ◽  
Susan Johnson ◽  
Paige Wendland ◽  
Rogerio Prata
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Starch Content ◽  
Rapid Development ◽  
Partial Least Square ◽  
Least Square ◽  
Operational Parameters ◽  
Corn Flour ◽  
Analytical Technique

Due to the rapid development of the corn-to-ethanol industry, the demand for process monitoring has led to the gradual substitution of traditional analytical techniques with fast and non-destructive methods such as near infrared spectroscopy. In this study, the feasibility of using Fourier transform–near infrared technology as an analytical tool to predict operational parameters (dry solids, starch, carbohydrate, and ethanol content) was investigated. Corn flour, liquefied mash, fermented mash, and distiller’s dried grains with solubles were selected to represent the feedstock, two intermediate products, and one primary co-product of corn-to-ethanol plants, respectively. Multivariate partial least square calibration models were developed to correlate near infrared spectra to the corresponding analytical values. The validation results indicate that near infrared models can be developed that will predict various parameters accurately (root mean square error of prediction: 0.16–1.14%, residual predictive deviation: 3.0–6.3). Measurement of starch or carbohydrate content in corn flour or distiller’s dried grains with solubles is challenging due to low accuracy of wet chemistry methods as well as sample complexity. The study demonstrated that near infrared spectroscopy, a high-throughput analytical technique, has the potential to replace the enzymatic assay.

Plant analysis using near infrared reflectance spectroscopy: the potential and the limitations

1998 ◽  
Vol 38 (7) ◽  
pp. 697 ◽  
Author(s):  
G. D. Batten
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Cost Effective ◽  
International Standards ◽  
Routine Analysis ◽  
Near Infrared Reflectance ◽  
Analytical Technique ◽  
Hazardous Chemical ◽  
Skilled Operator

Summary. International Standards Committees have formally accepted methods using near infrared spectroscopy for the analysis of protein, moisture and hardness in grains, and protein, acid detergent fibre and moisture in forages. In addition, near infrared spectroscopy is used world-wide for the routine analysis of many constituents in various tissues of many plant species. The reasons for near infrared spectroscopy being adopted as the preferred analytical method in many laboratories include: minimal sample preparation is needed, analysis time is short, it is cost effective to analyse a single sample or large batches of samples, several constituents can be determined simultaneously, the samples are not destroyed during analysis, neither a laboratory nor a skilled operator are required for routine analyses, the use of hazardous chemical reagents is eliminated, and, depending on the method, the results are usually more precise and can be more accurate than, as accurate as, or of acceptable accuracy, when compared with the method usually employed. It is the responsibility of the analyst to choose the most appropriate analytical technique and to follow standard procedures in order to obtain accurate and precise results from routine analysis. This paper summarises some of the applications of near infrared spectroscopy which are being used to analyse plant samples and lists some of the criteria which can be used to decide if near infrared spectroscopy is the most appropriate technique.

scholarly journals Simultaneous Quantification of 14 Compounds in Achillea millefolium by GC-MS Analysis and Near-Infrared Spectroscopy Combined with Multivariate Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lan-Ping Guo ◽  
Jian Yang ◽  
Li Zhou ◽  
Sheng Wang ◽  
Chuan-Zhi Kang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Achillea Millefolium ◽  
Multivariate Techniques ◽  
Preparation Technique ◽  
Least Squares Regression ◽  
Plant Materials ◽  
Analytical Technique ◽  
Simultaneous Quantification

The proposed work is focused on the simultaneous quantification of 14 compounds in the medicinal plant Achillea millefolium based on Near-Infrared Spectroscopy (NIR). The regression model of single-compound models (SCMs) and multicompound model (MCM) were created by partial least-squares regression (PLSR). Also, these models were calibrated by gas chromatographic mass spectroscopy (GC-MS). The results showed that the averaged standard errors of prediction (SEP) for the SCMs and MCM were 0.49 and 0.62, respectively, and most of the 14 compounds were significantly correlated. 43 correlations were significant at the 0.01 level (47.25% of the total), and 11 correlations were significant at the 0.05 level (12.09% of the total). The first three principal components (PCs) of principal component analysis (PCA) can explain >78% of the total variance. According to the component matrix and the communality table, octadecanoic acid has the largest influence on PC 1 (extraction squared = 46.72%), whose extraction was 0.932. The communality of neophytadiene, Z,Z,Z-9,12,15-octadecatrienoic acid, and oleic acid was also found to be large, whose extractions were 0.955, 0.937, and 0.859, respectively. These results indicate that if one compound shows a linear relationship with the NIR absorbance signal (SCM) also, an MCM can be created due to the close interrelations of these compounds. In this context, the present work highlights a suitable sample preparation technique to perform NIR analysis of raw plant material to benefit from robust and precise calibrations. To sum up, this NIR spectroscopic approach offers a precise, rapid, and cost-effective high-throughput analytical technique to simultaneously and noninvasively perform quantitative analysis of raw plant materials.

Diffuse reflectance near-infrared spectroscopy as a nondestructive analytical technique for polymer implants

1999 ◽  
Vol 88 (12) ◽  
pp. 1348-1353 ◽  
Author(s):  
Ronald L. Brashear ◽  
Douglas R. Flanagan ◽  
Paul E. Luner ◽  
Jeffery J. Seyer ◽  
Mark S. Kemper
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Analytical Technique ◽  
Polymer Implants
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