Adulteration detection of corn oil, rapeseed oil and sunflower oil in camellia oil by in situ diffuse reflectance near-infrared spectroscopy and chemometrics

Food Control ◽  
2021 ◽  
Vol 121 ◽  
pp. 107577
Author(s):  
QianWen Du ◽  
MengTing Zhu ◽  
Ting Shi ◽  
Xiang Luo ◽  
Bei Gan ◽  
...  
2016 ◽  
Vol 56 (9) ◽  
pp. 1504 ◽  
Author(s):  
J. P. Keim ◽  
H. Charles ◽  
D. Alomar

An important constraint of in situ degradability studies is the need to analyse a high number of samples and often with insufficient amount of residue, especially after the longer incubations of high-quality forages, that impede the study of more than one nutritional component. Near-infrared spectroscopy (NIRS) has been established as a reliable method for predicting composition of many entities, including forages and other animal feedstuffs. The objective of this work was to evaluate the potential of NIRS for predicting the crude protein (CP) and neutral detergent fibre (NDF) concentration in rumen incubation residues of permanent and sown temperate pastures in a vegetative stage. In situ residues (n = 236) from four swards were scanned for their visible-NIR spectra and analysed for CP and NDF. Selected equations developed by partial least-squares multivariate regression presented high coefficients of determination (CP = 0.99, NDF = 0.95) and low standard errors (CP = 4.17 g/kg, NDF = 7.91 g/kg) in cross-validation. These errors compare favourably to the average concentrations of CP and NDF (146.5 and 711.2 g/kg, respectively) and represent a low fraction of their standard deviation (CP = 38.2 g/kg, NDF = 34.4 g/kg). An external validation was not as successful, with R2 of 0.83 and 0.82 and a standard error of prediction of 14.8 and 15.2 g/kg, for CP and NDF, respectively. It is concluded that NIRS has the potential to predict CP and NDF of in situ incubation residues of leafy pastures typical of humid temperate zones, but more robust calibrations should be developed.


2021 ◽  
Author(s):  
◽  
Timothy Schwab

Transcutaneous near infrared spectroscopy (NIRS) of muscle requires coupling between the device and the skin. An unfortunate by-product of this coupling is contact force artefact, where the amount of contact force between the device and the skin affects measurements. Contact force artefact is well known, but largely ignored in most NIRS research. We performed preliminary investigations of contact force artefact to quantify tissue behaviour to inform future NIRS designs. Specifically, we conducted three studies on contact force artefact: (i) an experimental investigation of static load at varied levels of contact force and muscle activation, (ii) an experimental investigation of oscillating load at varied levels of contact force and frequency, and (iii) a Monte Carlo simulation of photon propagation through skin, adipose tissue, and muscle. Our results confirmed that contact force artefact is a confounding factor in NIRS muscle measurements because contact force affects measured hemoglobin concentrations in a manner consistent with muscle contractions. Further, the effects of contact force are not altered by muscle contraction and a likely candidate for the mechanism responsible for contact force artefact is the viscoelastic compression of superficial tissues (skin and adipose) during loading. Simulation data suggests that adipose tissue plays a key role in diffuse reflectance of photons, so any compression of the superficial tissues will affect the reflected signal. Further research is required to fully understand the mechanisms behind contact force artefact, which will, in turn, inform future NIRS device designs.


2007 ◽  
Author(s):  
Donald Dahm ◽  
Kevin Dahm

A jar of sweets may not appear to be a serious introduction to the attempt to progress the understanding of the challenging nature of what is usually termed "diffuse reflection". However, this book by the father and son team of Don and Kevin Dahm is the first such attempt since the famous book by Wendlandt and Hecht some forty year ago. The sweets are not only useful models, they also indicate the desire of the authors to make this a readable and entertaining book as well as a very serious attempt to advance our theoretical understanding of this complex and confusing topic. The Dahms have been developing and advancing a new theory for the last few years. This book brings it together. It explains the nature of reflected radiation and then the problem of finding a mathematical description of it. In their quest, they have rediscovered and used mathematics that was invented by Sir George Strokes in the 1860s! Much of the current use of near infrared spectroscopy utilizes diffuse reflection or transmission. According to Karl Norris "The development of NIR analysis is being restricted by our lack of a theoretical understanding of diffuse reflection" and he should know!


2010 ◽  
Vol 45 (8) ◽  
pp. 1427-1431 ◽  
Author(s):  
Emma Petiot ◽  
Patrick Bernard-Moulin ◽  
Thierry Magadoux ◽  
Cécile Gény ◽  
Hervé Pinton ◽  
...  

Talanta ◽  
2021 ◽  
Vol 222 ◽  
pp. 121511
Author(s):  
Dolores Pérez-Marín ◽  
Tom Fearn ◽  
Cecilia Riccioli ◽  
Emiliano De Pedro ◽  
Ana Garrido

2018 ◽  
Vol 64 (No. 2) ◽  
pp. 70-75 ◽  
Author(s):  
Romsonthi Chutipong ◽  
Tawornpruek Saowanuch ◽  
Watana Sumitra

Soil organic matter (SOM) is a major index of soil quality assessment because it is one of the key soil properties controlling nutrient budgets in agricultural production systems. The aim of the in situ near-infrared spectroscopy (NIRS) for SOM prediction in paddy area is evaluation of the potential of SOM and prediction of other soil properties. There are keys for soil fertility and soil quality assessments. A spectral reflectance of 130 soil samples was collected by field spectroradiometer in a region of near-infrared. Spectral reflectance collections were processed by the first derivative transformation with the Savitsky-Golay algorithms. Partial least square regression method was used to develop a calibration model between soil properties and spectral reflectance, which was used for prediction and validation processes. Finally, the results of this study demonstrate that NIRS is an effective method that can be used to predict SOM (R<sup>2</sup> = 0.73, RPD (ratio of performance to deviation) = 1.82) and total nitrogen (R<sup>2</sup> = 0.72, RPD = 1.78). Therefore, NIRS is a potential tool for soil properties predictions. The use of these techniques will facilitate the implementation of soil management with a decreasing cost and time of soil study in a large scale. However, further works are necessary to develop more accurate soil properties prediction and to apply this method to other areas.


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