NIR Spectroscopy for Chemical Composition and Internal Quality in Foods

2011 ◽  
pp. 145-180
Keyword(s):  
Chemical Composition ◽  
Nir Spectroscopy ◽  
Internal Quality

scholarly journals Ability of NIR spectroscopy to predict meat chemical composition and quality – a review

2011 ◽  
Vol 49 (No. 11) ◽  
pp. 500-510 ◽  
Author(s):  
M. Prevolnik ◽  
M. Čandek-Potokar ◽  
D. Škorjanc
Keyword(s):  
Chemical Composition ◽  
Meat Quality ◽  
Quality Evaluation ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
The Other ◽  
Meat Composition ◽  
Feeding Regimes ◽  
Simultaneous Assessment

In contrast to conventional methods for the determination of meat chemical composition and quality, near infrared spectroscopy (NIRS) enables rapid, simple and simultaneous assessment of numerous meat properties. The present article is a review of published studies that examined the ability of NIRS to predict different meat properties. According to the published results, NIRS shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. On the other hand, NIRS is less accurate for predicting different attributes of meat quality. In view of meat quality evaluation, the use of NIRS appears more promising when categorizing meat into quality classes on the basis of meat quality traits for example discriminating between feeding regimes, discriminating fresh from frozen-thawed meat, discriminating strains, etc. The performance of NIRS to predict meat properties seems limited by the reliability of the method to which it is calibrated. Moreover, the use of NIRS may also be limited by the fact that it needs a laborious calibration for every purpose. In spite of that, NIRS is considered to be a very promising method for rapid meat evaluation.    

scholarly journals From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

2019 ◽  
Vol 8 (4) ◽  
pp. 21
Author(s):  
Aoife Power ◽  
Vi Khanh Truong ◽  
James Chapman ◽  
Daniel Cozzolino
Keyword(s):  
Chemical Composition ◽  
Hyperspectral Imaging ◽  
High Throughput ◽  
Analytical Methods ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Chemical Compounds ◽  
Spectroscopic Techniques ◽  
High Throughput Analysis ◽  
Laboratory Methods

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectral imaging) provide analysts with an innovative and improved understanding of complex issues by determining several chemical compounds and metabolites at once, allowing for the collection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition.

Light distribution inside mandarin fruit during internal quality assessment by NIR spectroscopy

2003 ◽  
Vol 27 (2) ◽  
pp. 185-196 ◽  
Author(s):  
Daniel G Fraser ◽  
Robert B Jordan ◽  
Rainer Künnemeyer ◽  
V.Andrew McGlone
Keyword(s):  
Quality Assessment ◽  
Nir Spectroscopy ◽  
Light Distribution ◽  
Internal Quality

Rapid analysis of chemical composition in intact and milled rice cookies using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 330-337 ◽  
Author(s):  
Latthika Wimonsiri ◽  
Pitiporn Ritthiruangdej ◽  
Sumaporn Kasemsumran ◽  
Nantawan Therdthai ◽  
Wasaporn Chanput ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Near Infrared ◽  
Wheat Gluten ◽  
Nir Spectroscopy ◽  
Rice Flour ◽  
Coefficient Of Determination ◽  
Gluten Free ◽  
Least Squares Regression ◽  
Milled Rice ◽  
Control Programs

This study has investigated the potential of near infrared (NIR) spectroscopy to predict the content of moisture, protein, fat and gluten in rice cookies in different sample forms (intact and milled samples). Gluten-free (n = 48) and gluten (n = 48) rice cookies were formulated with brown and white rice flours in which butter was substituted with fat replacer at 0, 15, 30 and 45%. With regard to gluten cookies, rice flour was substituted with wheat gluten at 1, 3 and 5%. Partial least squares regression modeling produced models with coefficient of determination (R2) values greater than 0.88 from NIR spectra of intact samples and greater than 0.92 for milled samples. These models were able to predict the four components with a ratio of prediction to deviation greater than 2.7 and 3.8 in intact and milled samples, respectively. The results suggest that the models obtained from the intact samples can be successfully applied for chemical composition of rice cookies and are reliable enough use for potential quality control programs.

Evaluation of Fourier transform-NIR spectroscopy for integrated external and internal quality assessment of Valencia oranges

2013 ◽  
Vol 31 (1) ◽  
pp. 144-154 ◽  
Author(s):  
Lembe Samukelo Magwaza ◽  
Umezuruike Linus Opara ◽  
Leon A. Terry ◽  
Sandra Landahl ◽  
Paul J.R. Cronje ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Quality Assessment ◽  
Nir Spectroscopy ◽  
Internal Quality

Using NIR and ATR-FTIR spectroscopy to rapidly detect compression wood inPinus radiata

2014 ◽  
Vol 44 (7) ◽  
pp. 820-830 ◽  
Author(s):  
J. Paul McLean ◽  
Guangwu Jin ◽  
Maree Brennan ◽  
Michél K. Nieuwoudt ◽  
Philip J. Harris
Keyword(s):  
Chemical Composition ◽  
Compression Wood ◽  
Near Infrared ◽  
Water Saturation ◽  
Nir Spectroscopy ◽  
Analytical Techniques ◽  
Gradual Change ◽  
Least Squares Regression ◽  
Dimensional Changes ◽  
Discriminatory Analysis

Compression wood has undesirable properties for structural timber and for paper production. Traditional methods of detecting it are often time consuming and subjective. This study aimed to rapidly and impartially detect compression wood through the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and diffuse reflectance near infrared (NIR) spectroscopy. Compression wood and non-compression wood samples were obtained from young Pinus radiata D. Don trees grown in New Zealand. Longitudinal dimensional changes were measured during drying or water saturation of the samples; lignin and galactose contents were determined using conventional analytical techniques. Chemical composition was here a more reliable discriminator between wood types than longitudinal dimensional changes. It was shown that partial least-squares regression (PLS-R) or discriminatory analysis (PLS-DA) could be used to build models on the training samples that could discriminate between wood types of the independently grown validation samples. Ultimately, both types of spectroscopies could be used to discriminate between compression wood and non-compression wood either through prediction or discriminatory analysis with equal success. Investigation into spectral differences between wood types, including sequential mixtures of wood types, showed that for the mid-IR region absorbance at a well-resolved lignin band could be used to discriminate compression wood from non-compression wood. For NIR, a similar investigation showed that absorbance values at four separate wavenumbers or the 6000–5600 cm−1region of the first derivative spectra were required for that discrimination. It is proposed that if there is a gradual change in the chemical composition of compression wood with its severity, then IR spectroscopy could feasibly be used to rapidly determine compression wood severity.

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