A novel combined approach of diffuse reflectance UV–Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application

2017 ◽  
Vol 175 ◽  
pp. 67-75 ◽  
Author(s):  
Raj Kumar ◽  
Vishal Sharma
Keyword(s):  
Multivariate Analysis ◽  
Diffuse Reflectance ◽  
Nir Spectroscopy ◽  
Combined Approach ◽  
Forensic Application ◽  
Non Destructive ◽  
Ballpoint Pen Inks

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baselines for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non-destructive quantification of quality parameters in peanuts.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

Identification prediction moisture content of Thai coconut sugar (Cocos nucifera L.) using FT-NIR spectroscopy

Food Research ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 382-385
Author(s):  
D. Thumrongchote
Keyword(s):  
Moisture Content ◽  
Cocos Nucifera ◽  
Nir Spectroscopy ◽  
Grocery Stores ◽  
Absorbance Spectrum ◽  
Coconut Tree ◽  
Cocos Nucifera L ◽  
The Cost ◽  
Non Destructive ◽  
Low Glycemic Index

Coconut sugar is a local sugar from the blossoms of a coconut tree. It has been considered a healthy sugar due to its low glycemic index. There is an attempt to add other sugar to it to lower the cost. Thus, this research aimed to identify Thai coconut sugar and to establish models for predicting the moisture content of coconut sugar by using FT-NIR spectroscopy. Thai coconut sugar samples were purchased from local grocery stores in four provinces, online, and the community market. Their moisture contents were varied and equilibrated for 24 hrs prior to the measurements of moisture and FT-NIR spectra. The results showed that FT-NIR spectra of Thai coconut sugar differ from sucrose, glucose and fructose at the absorbance spectrum of 5379-5011 cm-1 . FT-NIR spectroscopy of 54 known moisture samples of Thai coconut sugar was used to obtain a model to predict moisture content. The predicted equation, using the PLS technique with the Spectrum Quant program, was found to give a standard error of prediction (SEP) 0.077% (less than 0.10%), indicating a non-destructive method of accurately and precisely predicting moisture levels in the coconut sugar. The results obtained suggested that FTNIR spectroscopy has the potential to be used as a tool to identify Thai coconut sugar accurately. It can rapidly predict the moisture content in the sample which will be useful in quality control standards.

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