scholarly journals Comparison Of Linear And Non-Linear Calibration Models For Non-Destructive Firmness Determining Of ‘Mazafati’ Date Fruit By Near Infrared Spectroscopy

2014 ◽  
Vol 17 (6) ◽  
pp. 1199-1210 ◽  
Author(s):  
Seyed Ahmad Mireei ◽  
Seyed Saeid Mohtasebi ◽  
Morteza Sadeghi
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Linear Calibration ◽  
Date Fruit ◽  
Calibration Models ◽  
Non Linear ◽  
Non Destructive

scholarly journals Research Note: Non-destructive Detection of Super Grade Chick Embryos or Hatchlings using Near-infrared Spectroscopy

2021 ◽  
pp. 101189
Author(s):  
Alin Khaliduzzaman ◽  
Ayuko Kashimori ◽  
Tetsuhito Suzuki ◽  
Yuichi Ogawa ◽  
Naoshi Kondo
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Research Note ◽  
Chick Embryos ◽  
Non Destructive

Fast Non-Destructive Detection of Wool Content in Blended Fabrics Based on Near-Infrared Spectroscopy Technology

2015 ◽  
Vol 671 ◽  
pp. 356-362 ◽  
Author(s):  
Zhi Feng Chen ◽  
Yuan Quan Hong ◽  
Chang Jiang Wan ◽  
Lian Ying Zhao
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Detection Method ◽  
Quantitative Model ◽  
National Standard ◽  
Fast Detection ◽  
Significant Difference ◽  
Validation Set ◽  
Non Destructive

A fast non-destructive method of detection of wool content in blended fabrics was studied based on Near Infrared spectroscopy technology in order to avoid the time-consuming, tedious work and the destruction of samples in the traditional inspection. 621 wool/nylon, wool/polyester and wool/nylon/polyester blended fabrics were taken as research objects. To get the wool content, we established the wool near-infrared quantitative model by partial least squares (PLS) method after analyzing the color and composition of the samples. For verifying the validity and practicability of the model, 100 samples were chosen as an independent validation set. The variance analysis shows that there is no significant difference between Near Infrared fast detection method and national standard method (GB/T2910-2009),which indicates that this method is expected to be a means of fast non-destructive detection and will have extensive application future in the field of wool content detection.

scholarly journals Non-destructive assessment of the oxidative stability of intact macadamia nuts during the drying process by near-infrared spectroscopy

LWT ◽  
2019 ◽  
Vol 103 ◽  
pp. 101-107 ◽  
Author(s):  
Lívia C. Carvalho ◽  
Marcondes L. Leite ◽  
Camilo L.M. Morais ◽  
Kássio M.G. Lima ◽  
Gustavo H.A. Teixeira
Keyword(s):  
Infrared Spectroscopy ◽  
Oxidative Stability ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Drying Process ◽  
Macadamia Nuts ◽  
Non Destructive

Linear transformations of multivariate calibration models in near infrared spectroscopy: A comparative study

2017 ◽  
Vol 25 (4) ◽  
pp. 223-230 ◽  
Author(s):  
Joseph Dubrovkin
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Cetane Number ◽  
Total Protein Content ◽  
Prediction Errors ◽  
Calibration Data ◽  
Linear Transformations ◽  
Calibration Models

It was shown that linear transformations are suitable for use in multivariate calibration in near infrared spectroscopy as data compression tools. Partial Least Squares calibration models were built using spectral data transformed by expansion in the series of classical orthogonal polynomials, Fourier and wavelet harmonics. These models allowed effective prediction of the cetane number of diesel fuels, Brix and pol parameters of syrup in sugar production and fat and total protein content in milk. Depending on the compression ratio, prediction errors were no larger than 30% of corresponding errors obtained by the use of the non-transformed models. Although selection of the most suitable transformation depends on the calibration data and on the cross-validation method, in many cases Fourier transform gave satisfactory results.

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